EP3649072A1 - Crane and method for controlling such a crane - Google Patents

Abstract

The invention relates to a crane, in particular a rotary tower crane, comprising a lifting cable (207) which runs out from a crane boom (202) and has a load receiving means (208), drive devices for moving multiple crane elements and displacing the load receiving means (208), a controller (3) for controlling the drive devices such that the load receiving means (208) is displaced along a movement path, and a pendulum damping device (340) for damping pendulum movements of the load receiving means (208) and/or of the lifting cable (207). The pendulum damping device (340) has a pendulum sensor system (60) for detecting pendulum movements of the lifting cable (207) and/or of the load receiving means (208) and a regulator module (341) comprising a closed control loop for influencing the actuation of the drive devices depending on a pendulum sensor system (60) signal returned to the control loop. The invention is characterized in that the pendulum damping device (340) has a structural dynamic sensor system (342) for detecting deformations and/or dynamic inherent movements of structural components of the crane, and the regulator module (341) of the pendulum damping device (340) is designed to take into consideration both the pendulum signal of the pendulum sensor system (60) as well as the structural dynamic signals which are returned to the control loop and specify deformations and/or dynamic inherent movements of the structural components, while influencing the actuation of the drive devices. The invention also relates to a corresponding method for controlling a crane, in particular a rotary tower crane, the load receiving means (208) of which, said means being attached to a lifting cable (207), are displaced by drive devices that are actuated by a controller (3) of the crane, wherein the actuation of the drive devices is influenced by a pendulum damping device (340) comprising a regulator module (341) with a closed control loop depending on pendulum-relevant parameters.

Description

 Crane and method for controlling such a crane

The present invention relates to a crane, in particular a tower crane, with a hoisting rope, which runs from a boom and carries a load receiving means, drive means for moving a plurality of crane elements and methods of lifting device, a control device for controlling the drive means such that the load receiving means moves along a travel path , and a pendulum damping device for damping oscillations of the load receiving means, said pendulum damping means a pendulum sensor for detecting oscillations of the hoisting rope and / or the load receiving means and a controller block with a closed loop for influencing the control of the drive means in response to pendulum signals from the pendulum sensors indicate detected oscillations and be returned to the control loop has. The invention further relates to a method for controlling a crane, in which the control of the drive means is influenced by a pendulum damping device as a function of pendulum-relevant parameters.

In order to be able to move the load hook of a crane along a travel path or between two target points, various drive devices usually have to be used. operated and controlled. For example, in a tower crane, in which the hoist rope runs off a trolley, which is movable on the boom of the crane, usually the slewing, by means of which the tower with the boom provided thereon or the boom are rotated relative to the tower about an upright axis of rotation and the cat drive, by means of which the trolley can be moved along the boom, and the hoist, by means of which the hoist rope adjusted and thus the load hook can be raised and lowered, respectively operated and controlled. In cranes with a tilting telescopic boom in addition to the slewing, the boom or the boom supporting the superstructure rotated about an upright axis, and the hoist for adjusting the hoisting rope, and the rocker drive for up and down rocking of the boom and the telescopic drive for - And extending the telescopic shots actuated, possibly also a Wippspitzenantrieb in the presence of a luffing tip on the telescopic boom. In mixed forms of such cranes and similar crane types, such as tower cranes with luffing boom or derrick cranes with luffing counter-jib more drive devices can be controlled in each case.

The said drive means are hereby usually actuated and controlled by the crane operator via appropriate controls, for example in the form of joysticks, toggle switches, knobs and sliders and the like, which experience has required a lot of feeling and experience to approach the target points quickly and yet smoothly without major pendulum movements of the load hook. While driving between the target points as quickly as possible in order to achieve a high performance, should be stopped gently at the respective target point, without the load hook nachpendelt with the load on it.

Such control of the drive means of a crane is tiring in view of the required concentration for the crane operator, especially since often recurring travels and monotonous tasks are to be done. In addition, with decreasing concentration or even with insufficient experience with the respective crane type, larger pendulum movements of the absorbed load and there- fore a corresponding hazard potential if the crane operator does not operate the control levers or elements of the crane sensitively enough. In practice, the control of the crane, sometimes even with experienced crane operators, sometimes produces large swaying oscillations of the load which decay only very slowly.

In order to counter the problem of unwanted pendulum movements, it has been proposed to provide the control device of the crane with pendulum damping devices which intervene by means of control blocks in the control and influence the driving of the drive means, for example, too large accelerations of a drive means by too fast or too strong actuation of the operating lever prevent or mitigate it, or limit certain travel speeds with larger loads or similarly actively intervene in the travel movements in order to prevent excessive swinging of the load hook.

Such pendulum damping devices for cranes are known in various designs, for example by controlling the slewing, rocker and trolley drives in response to certain sensor signals, such as inclination and / or gyroscope signals. For example, the documents DE 20 2008 018 260 U1 or DE 10 2009 032 270 A1 show known load pendulum damping on cranes, to the object of which in this respect, that is to say with regard to the principles of the pendulum damping device, is expressly referred to. In DE 20 2008 018 206 U1, for example, the cable angle is measured relative to the vertical and its change in the form of the cable angular velocity by means of a gyroscope unit, in order to automatically intervene in the control when a limit value for the cable angular velocity with respect to the vertical is exceeded.

Furthermore, the documents EP16 28 902 B1, DE 103 24 692 A1, EP25 62 125 B1, US 2013 01 61 279 A, DE 100 64 182 A1, or US 55 26 946 B each show concepts for closed-loop control of cranes, the the pendulum dynamics or the Consider pendulum and drive dynamics. However, the application of these known concepts to "soft", yielding cranes with elongated, exhausted structures such as, for example, a tower crane with structural dynamics usually leads quite quickly to a dangerous, unstable upswing of the stimulable structural dynamics.

Such close-loop controls on cranes with consideration of pendulum dynamics have already been the subject of various scientific publications, cf. For example, E. Arnold, O. Sawodny, J. Neupert and K. Schneider, "IEEE International Conference Mechatronics and Automation, 2005, Niagara Falls, Ont.," Anti-sway system for boom cranes based on a model predictive control approach. Canada, 2005, pp. 1533-1538 Vol. 3., as well as Arnold, E., Neupert, J., Sawodny, O., "Model-Predictive Trajectory Generation for Flat-Based Sequential Controls Using the Example of a Mobile Harbor Crane", at - Automatisierungstechnik, 56 (8/2008), or J. Neupert, E. Arnold, K. Schneider & O. Sawodny, "Tracking and anti-sway control for boom cranes", Control Engineering Practice, 18, pp. 31-44, 2010, doi: 10.1016 / j.conengprac .2009.08.003.

Furthermore, the company Liebherr is known under the name "Cycoptronic", a load oscillation damping system for maritime cranes, which calculates load movements and influences such as wind in advance and automatically initiates compensatory movements on the basis of this prediction, in order to avoid a swinging of the load detected in this system by means of gyroscopes, the cable angle relative to the vertical and its changes to intervene in dependence of the gyroscope signals in the control.

With long, slender crane structures with ambitious load-bearing design, as is the case in particular with tower cranes, but can also be relevant in other cranes with jibs rotatable about an upright axle, such as, for example, tiltable telescopic boom cranes, it is sometimes the case with conventional pendulum damping devices difficult to intervene in the proper way in the control of the drives to the desired, pendeldämpfende Effect. In the field of structural parts, in particular of the tower and cantilever, dynamic effects and elastic deformation of the structural parts occur when a drive is accelerated or decelerated, so that interferences with the drive devices-for example, braking or accelerating the cat drive or the slewing gear-are not direct in the desired way to affect the pendulum movement of the load hook.

On the one hand, dynamic effects in the structural parts can lead to delays in the transmission to the hoisting rope and the load hook when drives are operated in a pendulum-damping manner. On the other hand, the dynamic effects mentioned can also have excessive or even counterproductive effects on a load pendulum. If, for example, a load initially oscillates too quickly by actuating the trolley drive backwards towards the tower and counteracts the pendulum damping device by delaying the trolley drive, the boom may tilt as the tower deforms correspondingly, thereby impairing the desired pendulum damping effect can be.

Especially in tower cranes occurs due to the lightweight construction also the problem that, in contrast to certain other crane types, the vibrations of the steel structure are not negligible, but should be treated in a closed loop (closed loop) for security reasons, as otherwise usually to a dangerous unstable swinging up of the steel structure can occur.

On this basis, the present invention has the object to provide an improved crane and an improved method for its control, avoid the disadvantages of the prior art and further develop the latter in an advantageous manner. Preferably should be achieved to move the payload according to the setpoints of the crane operator and thereby actively dampen unwanted oscillations via a control, while not stimulating undesirable movements of the structural dynamics, but also be damped by the regulation in order to achieve an increase in security, ease of use and automation. In particular, an improved pendulum damping in tower cranes to be achieved, which takes better account of the manifold influences of the crane structure.

According to the invention, said object is achieved by a crane according to claim 1 and a method according to claim 22. Preferred embodiments of the invention are the subject of the dependent claims.

It is therefore proposed to take into account not only the actual pendulum motion of the rope per se in the pendulum damping measures, but also the dynamics of the crane structure or the steel structure of the crane and its drive trains. The crane is no longer assumed to be a rigid rigid body, the drive movements of the drive means directly and identically, i. 1: 1 in movements of the suspension point of the hoist converts. Instead, the pendulum damper regards the crane as a soft structure exhibiting elasticity and compliance in accelerations in its structural members such as the tower grid and cantilever and in its drive trains, and takes into account this dynamics of the structural members of the crane in the pendulum damping effect Control of the drive devices.

In this case, both the pendulum dynamics and the structural dynamics are actively damped by means of a closed loop. In particular, the entire system dynamics is actively controlled as coupling of the pendulum, drive and structural dynamics of the tower crane to move the payload according to the target specifications. Sensors are used on the one hand to measure system variables of pendulum dynamics and on the other hand to measure system variables of structural dynamics, whereby non-measurable system variables in a model-based observer can be estimated as system states. The control signals for the drives are calculated by a model-based control as a state feedback of the system states, whereby a control loop is closed and results in a changed system dynamics. The control is designed such that the system dynamics of the closed loop is stable and control errors are compensated quickly.

According to the invention, a closed control loop is provided on the crane, in particular tower crane, with structural dynamics by the feedback of measurements not only of the pendulum dynamics but also of the structural dynamics. The pendulum damping device comprises in addition to the pendulum sensor for detecting Hubseil- and / or lifting device movements also a structural dynamics sensor for detecting dynamic deformations and movements of the crane structure or at least structural components thereof, wherein the controller block of the pendulum damping device, which influences the driving of the drive means pendeldämpfend , Is designed to take into account when influencing the control of the drive means both the detected by the pendulum sensor pendulum movements as well as the detected by the structural dynamics sensors dynamic deformations of the structural components of the crane. The closed loop is fed back both the pendulum sensor signals and the structural dynamics sensor signals.

The pendulum damping device thus does not consider the crane or machine structure as a rigid, so to speak infinitely stiff structure, but is based on an elastically deformable and / or resilient and / or relatively soft structure, which - in addition to the Stellbewegungsachsen the machine such as the Auslegerwippachse or the tower axis of rotation - allows movements and / or position changes by deformations of the structural components.

Taking account of the inherent mobility of the machine structure as a result of structural deformations under load or dynamic loads is especially important for elongated, slim and static and dynamic boundary conditions - taking into account the necessary collateral - worn structures such as tower cranes or telescopic cranes, since here noticeable movement shares, for example, for the boom and thus the load hook position by the deformations of the structural components added. Around To better combat the causes of pendulum, the pendulum damping takes into account such deformations and movements of the machine structure under dynamic loads.

As a result, considerable advantages can be achieved:

First, the vibration dynamics of the structural components is reduced by the control behavior of the control device. The vibration is actively dampened by the driving behavior or not excited by the control behavior.

Likewise, the steel construction is spared and less stressed. In particular shock loads are reduced by the control behavior.

Furthermore, the influence of the driving behavior can be defined by this method.

Due to the knowledge of structural dynamics and the control method, in particular the pitching vibration can be reduced and damped. As a result, the load behaves calmer and no longer fluctuates up and down in the rest position. Also transverse pendulum movements in the circumferential direction about the upright boom rotation axis can be better controlled by considering tower twist and boom pivoting bending deformations.

The aforementioned elastic deformations and movements of the structural components and drive trains and the resulting self-motions can basically be determined in various ways.

In particular, the structural dynamics sensor system provided for this purpose can be designed to detect elastic deformations and movements of structural components under dynamic loads. Such a structural dynamic sensor system may comprise, for example, deformation sensors, such as strain gauges on the steel structure of the crane, for example the grid frameworks of the tower and / or the cantilever.

Alternatively or additionally, yaw rate sensors, in particular in the form of gyroscopes, gyro sensors and / or gyrometers, and / or acceleration and / or speed sensors may be provided in order to detect certain movements of structural components, such as pitching movements of the jib tip and / or rotational dynamic effects on the jib and / or torsion. and / or bending movements of the tower to capture.

Furthermore, tilt sensors may be provided to detect inclinations of the boom and / or inclinations of the tower, in particular deflections of the boom from the horizontal and / or deflections of the tower from the vertical.

Basically, the structural dynamics sensors can work with different types of sensors, and in particular combine different sensor types. Advantageously, strain gauges and / or gauging sensors and / or yaw rate sensors, in particular in the form of gyroscopes, gyro sensors and / or gyrometers, can be used to detect the deformations and / or dynamic internal movements of structural components of the crane, wherein the acceleration sensors and / or Rotation rate sensors are preferably designed to detect three axes.

Such structural dynamics sensors may be provided on the boom and / or on the tower, in particular on its upper portion on which the boom is mounted, be provided to detect the dynamics of the tower. For example, jerky strokes lead to pitching movements of the boom, which are accompanied by bending movements of the tower, wherein a ringing of the tower in turn leads to pitching oscillations of the boom, which is associated with corresponding load hook movements. In particular, an angle sensor for determining the differential rotational angle between an upper Turmendabschnitt and the boom may be provided, for example, at the upper Turmendabschnitt and on the boom each an angle sensor may be mounted, the signals can indicate the said differential rotation angle in a differential consideration. Furthermore, a yaw rate sensor for determining the rotational speed of the jib and / or of the upper tower end section can advantageously also be provided in order to be able to determine the influence of the tower torsional movement in conjunction with the aforementioned differential rotational angle. From this, on the one hand, a more accurate load position estimation, but on the other hand also an active damping of the tower torsion during operation can be achieved.

In an advantageous development of the invention, two- or three-axis rotation rate sensors and / or acceleration sensors can be attached to the jib tip and / or to the jib in the region of the upright crane rotation axis in order to be able to determine structural dynamic movements of the jib.

Alternatively or additionally, motion and / or acceleration sensors can also be assigned to the drive trains in order to be able to detect the dynamics of the drive trains. For example, the pulleys of the trolley for the hoist rope and / or pulleys for a guy rope of a luffing jib to be assigned rotary encoder to capture the actual rope speed at the relevant point can.

Advantageously, the drive devices themselves are assigned suitable motion and / or speed and / or acceleration sensors in order to detect the drive movements of the drive devices and set them in the drive trains in conjunction with the estimated and / or detected deformations of the structural components or of the steel structure and pliability to be able to. In particular, by adjusting the signals of the motion and / or acceleration sensors directly assigned to the drive devices with the signals of the structural dynamics sensors with knowledge of the structural geometry, the motion and / or acceleration component on a structural part can be determined which depends on dynamic deformation or acceleration Torsion of the crane structure goes back and in addition to the actual crane movement, as induced by the drive movement and also occurred in a completely rigid, rigid crane. If, for example, the slewing mechanism of a tower crane is adjusted by 10 °, but only one turn of 9 ° is detected at the cantilever tip, a torsion of the tower and / or a bending deformation of the cantilever can be deduced, which at the same time in turn, for example, with the twisting signal at the Spike mounted rotation rate sensor can be adjusted to differentiate between tower twist and cantilever bending can. If the load hook lifted by one hoist by the hoist, but at the same time a pitching downwards determined by, for example, 1 ° on the boom, the actual load hook movement can be concluded taking into account the unloading of the trolley.

Advantageously, the structural dynamics sensor system can detect different directions of movement of the structural deformations. In particular, the structural dynamics sensor system can have at least one radial dynamic sensor for detecting dynamic movements of the crane structure in an upright plane parallel to the crane boom, and at least one pivoting dynamics sensor for detecting dynamic movements of the crane structure about an upright crane rotation axis, in particular tower axis. The controller module of the pendulum damping device can be designed to control the drive devices, in particular a cat drive and slewing drive, depending on the detected dynamic movements of the crane structure in the upright, cantilever parallel plane, in particular parallel to the boom longitudinal direction, and the detected dynamic movements of the crane structure to the to influence upright crane rotation axis. Furthermore, the structural dynamics sensor system can have at least one stroke dynamic sensor for detecting vertical dynamic deformations of the crane jib and the control module of the pendulum damping device can be designed to influence the control of the drive devices, in particular a hoist drive, as a function of the detected vertical dynamic deformations of the crane jib.

Advantageously, the structural dynamics sensor is designed to detect all eigenmodes of the dynamic torsions of the crane jib and / or the crane tower whose natural frequencies lie in a predetermined frequency range. For this purpose, the structural dynamics sensor system at least one, preferably a plurality of tower sensor (s), which is spaced from a node of a tower oscillation, for detecting Turmverwindungen and at least one, preferably a plurality of cantilever sensor (s), the / spaced from a node a boom own vibration is arranged to detect Auslegerverwindungen.

In particular, a plurality of sensors for detecting a structure movement can be placed so that an observability of all eigenmodes is ensured whose natural frequencies lie in the relevant frequency range. In principle, one sensor per pendulum movement direction can suffice, but in practice the use of several sensors is recommended. For example, placing a single sensor in a node of the measure of a structure eigenmode (eg, position of the trolley at a rotation node of the first cantilever eigenmode) results in the loss of observability, which can be avoided by adding a sensor at another position , In particular, the use of three-axis rotation rate sensors or acceleration sensors on the jib tip as well as on the boom near the slewing gear is recommended.

The structural dynamics sensor technology can basically work with different types of sensors for detecting the eigenmodes, in particular also different sensor types. combine pen. Advantageously, the previously mentioned strain gauges and / or gauging sensors and / or yaw rate sensors, in particular in the form of gyroscopes, gyro sensors and / or gyrometers, can be used to detect the deformations and / or dynamic internal movements of structural components of the crane, the acceleration sensors and / or rotation rate sensors are preferably designed to detect three-axis.

In particular, the structural dynamics sensor system can have at least one yaw rate and / or acceleration sensor and / or strain gauges for detecting dynamic tower deformations and at least one yaw rate and / or acceleration sensor and / or strain gauges for detecting dynamic boom deformations. Advantageously, yaw rate and / or acceleration sensors can be provided at different tower sections, in particular at least at the tower tip and at the articulation point of the jib and possibly in a tower middle section below the jib. Alternatively or additionally, yaw rate and / or acceleration sensors may be provided on different sections of the boom, in particular at least on the jib tip and / or the trolley and / or the jib foot on which the boom is articulated, and / or on a boom section in the hoist. Advantageously, the said sensors are arranged on the respective structural component in such a way that they can detect the eigenmodes of its elastic twists.

In a further development of the invention, the pendulum damping device may also comprise an estimation device, the deformations and movements of the machine structure under dynamic loads, depending on the control commands entered control commands and / or in response to certain driving actions of the drive means and / or depending on certain speed and / or acceleration profiles of the drive devices, estimated taking into account conditions characterizing the crane structure. In particular, by means of such an estimating device System sizes of the structural dynamics, possibly also the pendulum dynamics are estimated, which can not or only with difficulty be detected by sensors.

Such an estimation device can, for example, access a data model in which structural variables of the crane such as tower height, boom length, stiffness, area moment of inertia and the like are stored and / or linked together, and then based on a specific load situation, ie weight of the load recorded on the load hook and instantaneous overhang to estimate what dynamic effects, ie deformations in the steel structure and in the drive trains for a specific operation of a drive device result. Depending on such an estimated dynamic effect, the pendulum damping device can then intervene in the control of the drive means and influence the manipulated variables of the drive controller of the drive means to avoid or reduce oscillations of the load hook and the hoisting rope.

In particular, the determination device for determining such structural deformations can have a calculation unit which calculates these structural deformations and resulting structural part movements on the basis of a stored calculation model as a function of the control commands entered at the control station. Such a model can be constructed similar to a finite element model or be a finite element model, but advantageously a model that is significantly simplified compared to a finite element model is used, for example empirically by detecting structural deformations under certain control commands and / or load conditions on the real crane or the real machine can be determined. Such a calculation model can, for example, work with tables in which specific deformations are assigned to specific control commands, wherein intermediate values of the control commands can be converted into corresponding deformations by means of an interpolation device. According to a further advantageous aspect of the invention, the controller module in the closed loop may include a filter device or an observer, on the one hand, the structural dynamic crane reactions and the Hubseilbzw. Load hook pendulum movements observed as they are detected by the structural dynamics sensor and the pendulum sensor and set at certain variables of the drive controller, so that the observer or filter device taking into account predetermined regularities of a dynamic model of the crane, which can be designed basically different and by analysis and simulation of the steel structure can be obtained, based on the observed Kranstruktur- and pendulum reactions can influence the manipulated variables of the controller.

Such a filter or observer device can be designed in particular in the form of a so-called Kalman filter, to which the manipulated variables of the drive controllers of the crane as an input variable and, on the other hand, both the pendulum signals of the pendulum sensor system and the structural dynamic signals which are returned to the control loop, the deformations and / or dynamic insufficiency. Specify movements of the structural components, supplied and influenced from these input variables by means of Kalman equations that model the dynamics system of the crane structure, in particular its steel components and drive trains, the manipulated variables of the drive controller accordingly to achieve the desired pendulum damping effect.

Advantageously, detected and / or estimated and / or calculated and / or simulated functions that characterize the dynamics of the structural components of the crane are implemented in the Kalman filter.

In particular, dynamic cantilever deformations and tower deformations detected by the structural dynamics sensor as well as the position of the load hook detected by means of the pendulum sensor system, in particular also its diagonal pull relative to the vertical, ie the deflection of the hoist cable relative to the vertical, are fed to said Kalman filter. The detection device for the position detection of the load hook can advantageously be an imaging Sensors include, for example, a camera that looks from the suspension point of the hoist, for example, the trolley, substantially vertically downwards. An image evaluation device can identify the crane hook in the image provided by the imaging sensor and determine its eccentricity or its displacement out of the image center, which is a measure of the deflection of the crane hook relative to the vertical and thus characterizes the load oscillation. Alternatively or additionally, a gyroscopic sensor can detect the haul rope extraction angle from the boom and / or from the vertical and feed it to the Kalman filter.

Alternatively or in addition to such pendulum detection of the load hook by means of an imaging sensor, the pendulum sensor system can also work with an Intertialerfas- sungseinrichtung attached to the load hook or the load receiving means and accelerating and rotation rate signals provides that represent translational accelerations and rotation rates of the load hook.

Such an inertial measuring device, which is sometimes also designated as IMU, may have acceleration and rotation rate sensor means for providing acceleration and yaw rate signals which indicate, on the one hand, translational accelerations along different spatial axes and, on the other hand, yaw rates or gyroscopic signals with respect to different spatial axes, include. Rotational speeds, but in principle also rotational accelerations or both, can be provided as rotation rates.

Advantageously, the inertial measuring device can detect accelerations in three spatial axes and rotation rates about at least two spatial axes. The acceleration sensor means may be triaxial and the gyroscope sensor means may be biaxial.

The inertial measuring device attached to the load hook can advantageously wire its acceleration and rotation rate signals and / or signals derived therefrom. transmit to a control and / or evaluation, which may be attached to a structural part of the crane or arranged separately in close proximity to the crane. In particular, the transmission may be to a receiver which may be attached to the trolley and / or to the suspension from which the hoist rope runs. Advantageously, the transmission can take place, for example, via a WLAN connection.

By such a wireless connection of an inertial measuring device, a pendulum damping can be easily retrofitted to existing cranes, without the need for complex retrofitting measures would be required. Essentially, only the inertial measuring device on the load hook and the receiver which communicates with it are to be attached, which transmits the signals to the control or regulating device.

From the signals of the Inertialmeßeinrichtung can advantageously be determined in a two-stage process, the deflection of the load hook or the hoisting rope relative to the vertical. First, the tilt of the load hook is determined, since this does not have to coincide with the deflection of the load hook relative to the trolley or the suspension point and the deflection of the hoisting rope relative to the vertical, then the desired deflection of the load hook or from the tilting of the load hook and its acceleration of the hoisting rope relative to the vertical. Since the inertial measuring device is attached to the load hook, the acceleration and rotation rate signals are influenced both by the pendulum movements of the hoisting rope as well as by the dynamics of the load hook tilting relative to the hoisting rope.

In particular, by three calculation steps, an accurate estimation of the load swing angle can be made, which can then be used by a controller for active swing damping. The three calculation steps may include in particular the following steps:

i. A determination of the hook tipping, for example by a complementary filter, the high-frequency components of the gyroscope signals and low-frequency Antei- determine le from the direction of the gravitational vector and combine them in addition to the determination of the HAkenkippung;

 ii. A rotation of the acceleration measurement or a transformation from the body-fixed into the inertial coordinate system;

 iii. Estimation of the load pendulum angle by means of an extended Kalman filter and / or by means of a simplified relation of the pendulum angle to the quotient of the lateral acceleration measurement and the gravitational constant.

Advantageously, the tilting of the load hook from the signals of the inertial measuring device is initially determined with the aid of a complementary filter, which makes use of the different features of the translational acceleration signals and the gyroscopic signals of the inertial measuring device, alternatively or additionally also a Kalman filter for determining the tilting of the load hook from the acceleration and yaw rate signals can be used.

From the determined tilting of the load receiving means can then by means of a Kalman filter and / or by means of static calculation of horizontal Inertialbe- acceleration and gravitational acceleration the desired deflection of the load hook relative to the trolley or against the suspension point of the hoisting rope and / or the deflection of the hoisting rope relative to the Vertical be determined.

In particular, the pendulum sensor system may comprise first determining means for determining and / or estimating a tilting of the load receiving means from the acceleration and rotation rate signals of the inertial measuring device and second determining means for determining the deflection of the hoisting rope and / or the load receiving means relative to the vertical from the determined tilting of the load receiving means and an inertial -Acceleration of the lifting device have.

The aforementioned first determination means may in particular comprise a complementary filter with a high-pass filter for the rotation rate signal of the inertial measuring device. and a low-pass filter for the acceleration signal of the inertial measuring device or a signal derived therefrom, said complementary filter may be configured, a rotational rate-based estimation of the tilt of the lifting device based on the high-pass filtered yaw rate signal, and an acceleration-based estimate of the tilt of the lifting device, which is based on the low-pass filtered acceleration signal to link together and to determine the desired tilting of the lifting device from the associated rate of rotation and acceleration-based estimates of the tilting of the lifting device.

In this case, the rotational rate-based estimation of the tilting of the load receiving means may include an integration of the high-pass-filtered yaw rate signal.

The acceleration-based estimation of the lifting of the lifting device can be based on the quotient of a measured horizontal acceleration component and a measured vertical acceleration component from which the acceleration-based estimation of the tilting is based on the relationship

is won.

The second determination means for determining the deflection of the load hook or the hoist rope relative to the vertical on the basis of the determined tilting of the load hook may comprise a filter and / or observer device which takes into account the determined tilting of the load receiving means as an input variable and the deflection of the load suspension means from an inertial acceleration on the load receiving means Hubseils and / or the lifting device relative to the vertical determined.

The named filter and / or observer device may in particular comprise a Kalman filter, in particular an extended Kalman filter.

As an alternative or in addition to such a Kalman filter, the second determination means may also comprise a calculation device for calculating the excursions. kung of the hoisting rope and / or the lifting device relative to the vertical from a static relationship of the accelerations, in particular from the quotient of a horizontal inertial acceleration and the gravitational acceleration have.

According to a further advantageous aspect of the invention, a two-degree-of-freedom control structure is used in the pendulum damping, by which the above-described state feedback (feedback) is supplemented by a feedforward control. In this case, the state feedback serves to ensure the stability and to quickly compensate for control errors, the pilot control, however, a good leadership behavior by ideally no rule errors occur.

The precontrol can advantageously be determined via the per se known method of differential flatness. Regarding the mentioned method of differential flatness, reference is made to the dissertation "Application of the flatness-based analysis and control of nonlinear multivariable systems" by Ralf Rothfuss, VDI-Verlag, 1997, which deals with the extent of this, ie with respect to the mentioned method of differential flatness of the present disclosure.

Since the deflections of the structural movements in contrast to the driven crane movements and the pendulum movements are small, the structural dynamics can be neglected to determine the feedforward control, whereby the crane, in particular tower crane can be represented as a flat system with the load coordinates as flat outputs.

Advantageously, therefore, the feedforward control and the calculation of the reference states of the two-degree structure is calculated in contrast to the feedback control of the closed loop neglecting the structural dynamics, ie the crane is for the purposes of feedforward as a rigid or sozu- say infinitely stiff structure adopted. Due to the small deflections of the elastic structure, which are very small in comparison to the crane movements to be carried out by the drives, this only leads to very small and therefore negligible deviations of the precontrol. For this, however, the description of - for the purposes of feedforward control as rigidly assumed tower crane, in particular tower crane as a flat system allows, which is easily invertible. The coordinates of the load position are flat outputs of the system. From the shallow outputs and their time derivatives, the required setpoint course of the manipulated variables as well as the system states can be calculated exactly algebraically (inverse system) - without simulation or optimization. This allows the load to be brought to a target position without overshooting.

The load position and its derivatives required for the flatness-based feedforward control can advantageously be calculated by a trajectory planning module and / or by a setpoint filtering. If a desired course for the load position and its first four time derivatives are determined via a trajectory planning or a setpoint filtering, the exact course of the necessary actuating signals for controlling the drives and the exact course of the corresponding system states can be calculated in the feedforward control via algebraic equations become.

In order to stimulate no structural movements by the feedforward control, it is advantageously possible to switch notch filters between trajectory planning and feedforward control in order to eliminate from the planned trajectory signal the excitable natural frequencies of the structural dynamics.

The model underlying the scheme can basically be designed differently. Advantageously, a compact representation of the entire system dynamics is used as a coupled pendulum, drive and structural dynamics, which is suitable as a basis for the observer and the control. In an advantageous embodiment of the invention, the crane control model is determined by a modeling method in which the entire Krandynamik in largely independent pending parts is split, advantageously for a tower crane in a part of all movements that are essentially excited by a slewing drive (pivoting dynamics), a part of all movements that are essentially stimulated by a Katzwerk drive (radial dynamics) and the dynamics in the direction of the hoist rope, which is excited by a winch drive.

The independent consideration of these parts neglecting the couplings allows a calculation of the system dynamics in real time and simplifies in particular the compact representation of the pivoting dynamics as a distributed parametric system (described by a linear partial differential equation), which describes the structural dynamics of the cantilever exactly Known methods can be easily reduced to the required number of eigenmodes.

The drive dynamics are advantageously modeled as a delay element 1st order or as a static amplification factor, the drives as a manipulated variable, a torque, a rotational speed, a force or a speed can be specified. Due to the subordinate control in the frequency converter of the respective drive this manipulated variable is adjusted.

The pendulum dynamics can be modeled as an idealized single / double filament pendulum with one / two point load masses and one / two simple ropes, which are either considered massless, or as bulked with modal order reduction on the most important eigenmodes of ropes.

The structural dynamics can be derived by approximating the steel structure in the form of continuous beams as a distributed parametric model, which can be discretized by known methods and reduced in system order, thereby taking a compact form, can be calculated quickly, and simplifies the observer and control design. Said pendulum damping device can monitor the input commands of the crane operator by manual operation of the crane by operating appropriate controls such as joysticks and override if necessary, especially in the sense that the crane operator, for example, too much predetermined accelerations are reduced or countermovements are automatically initiated when a crane movement predetermined by the crane operator has led or would lead to a swinging of the load hook. The controller module advantageously attempts to remain as close as possible to the movements and movement profiles desired by the crane operator in order to give the crane driver a sense of control, and only overrides the manually entered control signals as far as necessary in order to minimize the desired crane movement. and perform vibration-free.

Alternatively or additionally, the pendulum damping device can also be used in an automated operation of the crane, in which the control device of the crane in the sense of an autopilot, the load-carrying means of the crane automatically moves between at least two target points along a travel path. In such an automatic mode, in which a Verfahrweg- determination module of the control device determines a desired travel, for example in the sense of a web control and an automatic travel control module of the control device controls the drive controller or drive means so that the load hook is moved along the particular travel path, the pendulum damping device in engage the control of the drive controller by said Verfahrsteuermodul to move the crane hook pendulum-free or to dampen oscillations.

The invention will be explained in more detail below with reference to a preferred embodiment and associated drawings. In the drawings show:

1 is a schematic representation of a tower crane, in which the hook position and a cable angle relative to the vertical is detected by an imaging sensor, and in which a pendulum damping device affects the control of the drive means to prevent oscillations of the load hook and its hoisting rope,

2 is a schematic representation of a two-degree-of-freedom control structure of the pendulum damping device and the influencing of the manipulated variables of the drive controller by the latter,

Fig. 3: a schematic representation of deformations and vibration modes of a tower crane under load and their damping or avoidance by a Schägzugregelung, the partial view a.) Shows a pitch deformation of the Turmdehkrans under load and an associated diagonal pull of the hoisting rope, the partial views b. ) and c.) show a transverse deformation of the tower crane in a perspective view and in plan view from above, and the partial views d.) and e.) show an associated with such transverse deformations oblique pull of the hoisting rope,

4 shows a schematic representation of an elastic arm in a reference system rotating with the rotation rate,

5 is a schematic representation of a cantilever as a continuous beam with clamping in the tower, taking into account tower bending and tower torsion,

6 is a schematic representation of an elastic tower and a spring-mass replacement model of the tower bend transverse to the boom,

7 is a schematic representation of the pendulum dynamics in the pivoting direction of the crane with concentrated load mass and massless rope,

8 shows a schematic representation of the three most important eigenmodes of a

Tower crane, 9 is a schematic representation of the pendulum dynamics in the radial direction of the crane and its modeling by means of several coupled rigid bodies,

10 shows a schematic representation of a swinging hoist rope with load hook, to which an inertial measuring device is attached, which transmits its measuring signals wirelessly to a receiver on the trolley from which the hoist rope runs,

11 is a schematic representation of various load hooks to illustrate the possible tilting of the load hook relative to the hoisting rope,

FIG. 12: a schematic two-dimensional model of the pendeidynanamics of FIG

 Load hook suspension from the two preceding figures,

13 is an illustration of the tilt or the tilt angle of the load hook, which describes the rotation between inertial and load hook coordinates,

14 shows a block diagram of a complementary filter with high-pass and low-pass filters for determining the tilting of the load hook from the acceleration and rotation rate signals of the inertial measurement device,

FIG. 15 shows a comparative illustration of the pendulum angle profiles determined by means of an extended Kaman filter and by means of static estimation in comparison to the pendulum angle profile measured on a cardan joint, and FIG

Fig. 16: a schematic representation of a control or regulation structure with two degrees of freedom for automatically influencing the drives to avoid pendulum vibrations. As shown in Fig. 1, the crane may be formed as a tower crane. The tower crane shown in Fig. 1, for example, in a conventional manner have a tower 201 which carries a boom 202 which is balanced by a counter-jib 203, on which a counterweight 204 is provided. Said boom 202 can be rotated together with the counter-arm 203 about an upright pivot axis 205, which may be coaxial with the tower axis, by a slewing gear. On the boom 202, a trolley 206 can be moved by a cat drive, wherein from the trolley 206, a hoist rope 207 runs, to which a load hook 208 is attached.

As also shown in FIG. 1, the crane 2 can have an electronic control device 3 which, for example, can comprise a control computer arranged on the crane itself. Said control device 3 can in this case control various actuators, hydraulic circuits, electric motors, drive devices and other working units on the respective construction machine. This can, for example, in the crane shown its hoist, the slewing gear, the cat drive, whose -ggf. existing - boom rocker drive or the like.

Said electronic control device 3 can in this case communicate with a terminal 4, which can be arranged on the control station or in the driver's cab and, for example, in the form of a tablet with touch screen and / or joysticks, knobs, sliding switches and similar controls may have, so on the one hand different Information from the control computer 3 displayed on the terminal 4 and vice versa control commands via the terminal 4 in the control device 3 can be entered.

The said control device 3 of the crane 1 can in particular be designed to actuate the said drive devices of the hoisting gear, the trolley and the slewing gear even if a pendulum damping device 340 detects pendulum-relevant movement parameters. For this purpose, the crane 1 may comprise a pendulum sensor or detection device 60, which detects a diagonal pull of the hoist rope 207 and / or deflections of the load hook 208 relative to a vertical 61 passing through the suspension point of the load hook 208, ie the trolley 206. In particular, the cable angle φ against the gravity line, ie the vertical 62 can be detected, see. Fig. 1.

The intended determination means 62 of the pendulum sensor 60, for example, optically operate to determine said deflection. In particular, a camera 63 or another imaging sensor can be attached to the trolley 206, which looks downwards vertically from the trolley 206, so that when the load hook 208 is undeflected, its image reproduction lies in the center of the image provided by the camera 63. If, however, the load hook 208 is deflected relative to the vertical 61, for example due to jerky starting of the trolley 206 or abrupt braking of the slewing gear, the image reproduction of the load hook 208 moves out of the center of the camera image, which can be determined by an image evaluation device 64.

Alternatively or in addition to such an optical detection, the diagonal pull of the hoisting cable or the deflection of the load hook relative to the vertical can also take place by means of an inertial measuring device IMU, which is attached to the load hook 208 and can transmit its measuring signals preferably wirelessly to a receiver on the trolley 206, see. FIG. 10. The inertial measuring device IMU and the evaluation of its acceleration and yaw rate signals will be explained in more detail later.

Depending on the detected deflection relative to the vertical 61, in particular taking into account the direction and magnitude of the deflection, the control device 3 can control the slew drive and the trolley drive with the aid of the pendulum damping device 340 to bring the trolley 206 more or less precisely over the load hook 208 again and compensate for oscillations, or to reduce or not even let occur. For this purpose, the pendulum damping device 340 comprises a structural dynamics sensor 344 for determining dynamic deformations of structural components, wherein the controller module 341 of the pendulum damping device 340, which influences the driving of the drive means pendelock damping, is designed to influence the control of the drive means, the specific dynamic deformations of the structural components to consider the crane.

In this case, an estimation device 343 may also be provided, which determines the deformations and movements of the machine structure under dynamic loads, which depend on control commands entered in the control station and / or in dependence on specific drive actions of the drive devices and / or in dependence on certain speed and / or or acceleration profiles of the drive devices, estimated taking into account conditions characterizing the crane structure. In particular, a calculation unit 348 can calculate the structural deformations and resulting structural part movements on the basis of a stored calculation model as a function of the control commands entered at the control station.

Advantageously, the pendulum damping device 340 detects such elastic deformations and movements of structural components under dynamic loads by means of the structural dynamics sensor system 344. Such a sensor 344 may include, for example deformation sensors such as strain gauges on the steel structure of the crane, for example, the grid frameworks of the tower 201 or the boom 202. Alternatively or additionally, acceleration and / or velocity sensors and / or yaw rate sensors may be provided to detect certain movements of structural components, such as cantilever pitch pitch motions or rotational dynamics effects on the boom 202. Alternatively or additionally, such structural dynamics sensors can also be provided on the tower 201, in particular on its upper section on which the boom is mounted, in order to detect the dynamics of the tower 201. Alternatively or additionally, the drive trains may also be provided with motion and / or acceleration be assigned sensors to detect the dynamics of the drive trains can. For example, the pulleys of the trolley 206 for the hoist rope and / or pulleys for a guy rope of a luffing jib can be assigned rotary encoder to detect the actual rope speed at the relevant point can.

As illustrated in FIG. 2, the signals y (t) of the structural dynamics sensors 344 and the pendulum sensor 60 are fed back to the controller module 341, so that a closed control loop is realized. Said controller module 341 influences the control signals u (t) for controlling the crane drives, in particular the slewing gear, the hoist and the trolley drive, as a function of the returned structural dynamics and pendulum sensor signals.

As shown in FIG. 2, the controller structure further has a filter device or an observer 345, which observes the returned sensor signals or the crane reactions, which adjust at certain manipulated variables of the drive controller and, taking into account predetermined regularities of a dynamics model of the crane, the fundamentally different can be obtained by analysis and simulation of the steel structure, influenced by the observed crane reactions the manipulated variables of the controller.

Such a filter or observer device 345b can be designed in particular in the form of a so-called Kalman filter 346, to which the manipulated variables u (t) of the drive controller 347 of the crane and the returned sensor signals y (t), ie the detected crane movements, in particular the cable pull angle, are input variables φ relative to the vertical 62 and / or its temporal change or the angular velocity of the said skew, as well as the structural dynamic tangles of the cantilever 202 and the tower 201 are fed and from these inputs on the basis of Kalman equations, the dynamic system of the crane structure , in particular its steel components and drive trains, model, the manipulated variables of the drive controller 347 influenced accordingly to achieve the desired pendulum damping effect. With the aid of such a closed-loop control, in particular deformations and vibration modes of the tower crane under load can be damped or avoided from the beginning, as shown by way of example in FIG. 3, where the partial view a.) First schematically shows a pitch deformation of the tower arm under Load due to a bending of the tower 201 with the concomitant lowering of the boom 202 and an associated diagonal pull of the hoisting rope shows.

Furthermore, the partial views b.) And c.) Of FIG. 3 exemplarily show in a schematic manner a transverse deformation of the tower crane in a perspective view as well as in a plan view from above with the occurring deformations of the tower 201 and the boom 202.

Finally, FIG. 3 shows, in its partial views d.) And e.), An oblique pull of the hoist cable associated with such transverse deformations.

As FIG. 2 further shows, the controller structure is designed in the form of a two-degree of freedom control and, in addition to the closed-loop control with feedback of the pendulum sensor and structural-dynamics sensor signals, comprises a feed-forward control stage 350 , which tries by the best possible leadership behavior to let occur in the ideal case, no rule errors.

Said feedforward control 350 is advantageously formed flatness-based and determined by the so-called differential flatness method, as already mentioned.

Since the deflections of the structural movements and also of the pendulum movements are very small in comparison with the driven crane movements which constitute the nominal travel path, the structural dynamic signals and oscillation signals are neglected for the determination of the precontrol signals Ud (t) and Xd (t). that is, the signals y (t) of the pendulum and structural dynamics sensors 60 and 344 are not returned to the pilot module 350.

As shown in FIG. 2, setpoint values for the load receiving means 208 are fed to the pilot control module 350, wherein these setpoint values may be position indications and / or speed specifications and / or path parameters for the mentioned load receiving means 208 and define the desired movement.

In particular, the desired values for the desired load position and their time derivatives can advantageously be supplied to a trajectory planning module 351 and / or a setpoint filter 352, by means of which a desired course for the load position and its first four time derivatives can be determined, resulting in the Pre-control module 350 algebraic equations the exact course of the necessary control signals u _< j (t) for driving the drives and the exact course Ud (t) of the corresponding system states can be calculated.

In order to stimulate no structural movements by the feedforward control, a notch filter device 353 can advantageously be connected upstream of the pilot control module 350 in order to correspondingly filter the input variables supplied to the pilot control module 350, such a notch filter device 353 in particular between said trajectory planning module 351 and the setpoint filter module 352 on the one hand and On the other hand, the pilot module 350 may be provided. Said notching means 353 can be designed, in particular, to eliminate the excited natural frequencies of the structural dynamics from the desired value signals supplied to the precontrol.

In order to reduce or not even cause oscillation dynamics, the pendulum damping device 340 can be designed to correct the slewing gear and the trolley and possibly also the hoist such that the rope is always in the vertical perpendicular to the load, too when the crane tilts more and more forward due to the increasing load torque. For example, when lifting a load from the ground, the pitching motion of the crane due to its deformation under the load may be taken into account and the trolley can be tracked, taking into account the detected load position, or positioned under foresighted estimation of pitch deflection such that the hoist rope is subject to the resulting crane deformation in vertical perpendicular above the load. The largest static deformation occurs at the point where the load leaves the ground. In a corresponding manner, as an alternative or in addition, the slewing gear can also be traced under consideration of the detected load position and / or be positioned under forward-looking estimation of a transverse deformation so that the hoist rope is in vertical perpendicular above the load during the resulting crane deformation.

The model underlying the pendulum-damping control can basically be designed differently.

For the regulation-oriented mechanical modeling of elastic slewing cranes, the decoupled observation of the dynamics in the pivoting direction and within the tower-boom plane is useful. The slewing dynamics are stimulated and controlled by the slewing gear drive, while the dynamics in the tower-boom level are stimulated and regulated by the crab and hoist drive. The load oscillates in two directions - on the one hand transversely to the boom (pivoting direction), on the other hand in boom longitudinal direction (radial). The vertical load movement largely corresponds to the vertical boom movement due to the low hoist rope elasticity, which is small in tower cranes compared to the load deflections due to the pendulum motion.

In order to stabilize the load pendulum motion, it is necessary in particular to take into account the portions of the system dynamics that are excited by the slewing gear and by the creamer. These are called pan or radial dynamics. As long as the pendulum angles are not zero, both swivel and radial dynamics can be additionally influenced by the hoist. For one However, this regulatory design is negligible, especially for the pivoting dynamics.

The pivoting dynamics include in particular steel structure movements such as tower torsion, boom transverse deflection about the vertical axis and the tower bend transverse to the boom longitudinal direction, and the pendulum dynamics transverse to the boom and the slewing drive dynamics. The radial dynamics includes the tower bending in the boom direction, the pendulum dynamics in the boom direction and, depending on the perspective, the boom deflection in the vertical direction. In addition, the dynamic dynamics of the dynamics of the Katzwerk and possibly the hoist is attributed.

For the control advantageously a linear design method is sought, which is based on the linearization of the nonlinear mechanical model equations around a rest position. Such a linearization eliminates all couplings between pan and radial dynamics. This also means that no couplings are considered for the design of a linear control, even if the model was first derived coupled. Both directions from the beginning can be considered as decoupled, as this significantly simplifies the mechanical modeling. In addition, a clear model in a compact form is achieved for the pivoting dynamics, which can be evaluated quickly, which on the one hand saves computing power and on the other hand accelerates the development process of the control design.

In order to derive the swing dynamics as a compact, clear and accurate dynamic system model, the cantilever can be considered as an Euler-Bernoulli beam and thus initially as a distributed mass (distributed parametric) system. Furthermore, the retroactive effect of the stroke dynamics on the pivoting dynamics can also be neglected, which is a justified assumption for small pendulum angles due to the vanishing horizontal force component. When large pendulum angles occur, the effect of the winch on the swing dynamics can be taken into account as a disturbance variable.

The boom is modeled as a beam in a moving reference system which rotates through the slew drive at the yaw rate γ as shown in FIG.

Thus, three apparent accelerations within the reference system, known as Coriolis, centrifugal and Euler accelerations, act. Since the reference system rotates around a fixed point, this results for each point

within the reference system the apparent acceleration a 'too

d = 2 ω ^χ ν'- ώ ^χ r'-co x (<yxr '), (2)

Coriolis Euler centrifugal

where x represents the cross product,

 ω = [0 0 yj (3) the rotation vector and v 'the velocity vector of the point relative to the rotating reference system.

Of the three apparent accelerations, only the Coriolis acceleration represents a bidirectional coupling between pan and radial dynamics. This is proportional to the rotational speed of the reference system and to the relative speed. Typical maximum rotation rates of a tower crane are in the

_Range of about γ _ΜΑΧ «0.1- ^ ·, which is why the Coriolis acceleration typically

 s

takes small values compared to the driven accelerations of the tower crane. During the stabilization of the load pendulum movement at a fixed position, the rotation rate is very small, while during large guidance movements the Coriolis acceleration can be pre-planned and explicitly taken into account by a precontrol. In both cases, neglecting the Coriolis acceleration leads only to small approximation errors, which is why it is neglected below. The centrifugal acceleration acts as a function of the rotation rate only on the radial dynamics and can be considered as a disturbance for these. Due to the slow turning rates, it hardly affects the pivoting dynamics and can therefore be neglected. Important, however, is the linear Euler acceleration, which acts in the tangential direction and therefore plays a central role in the consideration of the pivoting dynamics.

Due to the small cross-sectional area of the boom and small shear deformations, the boom can be considered as an Euler-Bernoulli beam. Thus, the rotational kinetic energy of the beam rotation about the vertical axis is neglected. It is assumed that the mechanical parameters such as mass and moment of inertia of the Euler-Bernoulli approximation of the cantilever elements are known and can be used for the calculation.

Guys between the A-Bock and the boom have little effect on the pivoting dynamics and are therefore not modeled with. Deformations of the boom in the longitudinal direction are also so small that they can be neglected. This allows the undamped dynamics of the boom in the rotating reference system by the well-known partial differential equation

 μ (χ) w (x, t) + (EI (x) w "(x, t)) = q (x, t)

for the cantilever deflection w {x, t) at the point x at time t. Here, μ (χ) is the mass coating, I (x) is the area moment of inertia at location χ, E is the modulus of elasticity and q (x, t) is the applied distributed force on the cantilever. The zero point of the location coordinate x lies at the end of the derivation for this derivation

Counter-jib. The notation (·) '= - ^ describes the local

 dx

 Differentiation. Attenuation parameters will be introduced later.

In order to obtain a description of the boom dynamics in the inertial system, the elliptical force is separated from the distributed force, which is based on the partial differential equation "h _j )? + M (x * (x, t) + E (I (x) w" (x, t)) "= q (x, t) (5) where / cj is the length of the Counter jib and q {x, t) the actual distributed force on the boom without the Euler force Both beam ends are free and not clamped therefore the boundary conditions apply

 w "(0, /) = 0, w" (L, t) = 0 (6) w "'(0, /) = 0 w"' (L, t) = 0 (7) with the total length L of Jib and counter-jib.

A sketch of the cantilever is shown in FIG. The spring stiffnesses c _t and c _b represent the torsional stiffness or bending stiffness of the tower and are explained below.

For the modeling of the pivoting dynamics, the tower torsion and the tower bending transverse to the boom direction are advantageously taken into account. Due to its geometry, the tower can initially be assumed to be a homogeneous Euler-Bernoulli beam. For ease of modeling, the tower is represented at this point by a rigid body replacement model. Only one eigenmode for the tower bend and one for the tower torsion are considered. Since essentially only the movement at the tower tip is relevant for the pivoting dynamics, the tower dynamics can be used by a respective spring-mass system with matching natural frequency as a replacement system for bending or torsion. In the case of a higher elasticity of the tower, the spring-mass systems at this point can be easily supplemented by further eigenmodes by adding a corresponding number of masses and springs, cf.

Fig. 6.

The parameters spring stiffness c _h and mass m _T are chosen so that the

Deflection at the top and the natural frequency with that of the Euler Bernoulli beam match, representing the tower dynamics. Are for the tower, the constant area moment of inertia l _T , the tower height l _T and the Massebelag μ _τ known, so can the parameters of the static deflection at the end of the beam

 3

Fl _T

3EI _T

and the first Eigenfreque

of a homogeneous Euler-Bernoulli beam analytically too

 to calculate.

For the tower torsion can be analogous to a rigid body Ersatzmodeli with inertia

J _T and the torsional stiffness c, derive as shown in Fig. 5.

If the polar area moment of inertia I _p , the torsional moment of inertia J _T (which corresponds to the polar area moment of inertia for circular ring cross sections), the mass density p and the shear modulus G are known for the tower, the parameters of the replacement model can be used

GJ _T , T

J _T = 0A05pI _p l _T (11) to obtain a matching first natural frequency.

In order to consider both the substitute mass m _T and the spare inertia J _T in the form of an additive mass pad of the cantilever, the slender object approximation may be used, which implies that a slender bar segment of length

V m 'T, the mass m _T and with respect to its center of gravity has the inertia J _T. That is, the ground covering of the jib μ (χ) is at the point of Turmeinspannung over a

Length of b increased by the constant value - ^ -.

Since the dimensions and moments of inertia of the payloads of a tower crane are usually unknown, the payload can still be modeled as a concentrated mass point. The rope mass can be neglected. In contrast to the boom, the payload is slightly more influenced by Euler, Coriolis and centrifugal forces. The centrifugal acceleration acts only in cantilever direction, so it is not relevant at this point, the Coriollsbeschleunigung results with the distance x _{L of} the load to the tower

<* Coriolis, ν = ΪΫ * 1 · ( ³ )

Due to the low boom rotation rates, the core acceleration on the load can be neglected, especially when the load is to be positioned. However, in order to be able to implement a feedforward control if required, it is still carried along for a few steps.

For the derivation of the pendulum dynamics, this is projected onto a tangential plane, which is oriented orthogonal to the boom and cuts the position of the trolley.

The Eulerbeschleunigung results to

 Due to the usually small pendulum angle, the approximation applies

 x x "* l (15) from the approximation

A Euler, L = ^ü Euler ( ⁶ ) implies that the Euler acceleration acts on the load and the trolley in much the same way due to the rotation of the reference system. The acceleration on the load is shown in FIG.

It is

s (t) = x _lr r (t) + w (x _lr , t).

the y-position of the trolley in the tangential plane. The position of the trolley on the boom x _lr is approximated here as a constant parameter due to the decoupling of radial and pivoting dynamics.

The pendulum dynamics can be easily derived from the Lagrange formalism. This is first the potential energy

U = -m _L l (t) g cos (<fi (t))

with the load mass m,, the gravitational acceleration g and the rope length / (/) and the kinetic energy

in which

^~ s (+ / (sin (^ () ^~

 r (t) (20)

 - / (r) cos (fl) _

the y-position of the load in the tangential plane. With the Lagrange function

 L = T-U (21) and the Lagrange equations of the 2nd kind

 d_ dL_dL

 (22) dt δφ δφ

with the non-conservative n Coriolis force aCor, o "s, y ^S (<P (23)

follows the pendulum dynamics in the swing direction as

2φϊ + (s _{-a CorwUsy} ) _cosφ + g sin φ + φΐ = 0. (24) Linearized by φ = 0, φ = 0 the simplified pendulum dynamics follows, neglecting the change of the rope length / «0 and the Coriolis acceleration a _{Coriolis y} * 0

In order to describe the retroactivity of pendulum dynamics on the structural dynamics of boom and tower, the cable force F _R must be determined. The easiest way to do this is through their main share through the gravitational acceleration

^F R, h ^{= m} L ^ cos (^) sin (), (26) approximates. Their horizontal share in the y-direction thus arises

F _{R, h} = m _L gcosW) smW), (27) or linearized by ^ = 0

^F RM = ^m L ^ - ( ²⁸ )

The distributed parametric model (5) of cantilever dynamics describes infinitely many eigenmodes of the cantilever and is not yet suitable in form for a regulatory design. Since only a few of the lowest frequency eigenmodes are relevant for observer and closed-loop control, a modal transformation with subsequent modal order reduction can be applied to these few eigenmodes. However, an analytical modal transformation of equation (5) is rather difficult. Instead, it makes sense to locally discretize equation (5) using finite differences or the finite element method, thus obtaining an ordinary differential equation.

When discretized using the finite differences, the bar becomes N equidistantly distributed mass points at the cantilever positions

"E [l ... N] (29) split. The beam deflection at each of these positions is called w, = w (x "t) (30) noted. The local derivatives are given the central difference quotient

^, - ^ -, + ^ _{(31) W} W, _ _x -2M> _{I +} W _{M (32)} approximates, where A _x = x _M -x, the distance of the discrete mass points and w 'the local derivative w' (x ,, t) describe.

For the discretization of w "(x) the boundary conditions (6) - (7)

w _| ._, - 2w _i + w _| , ₊₁ = 0, e {1, N} (33) -w _I ._ ₂ + 2w _M -2w _{i + 1} + w _{i + 2} = 0, e {1, N} (34) after w_ w_ ₂ , w _{N + l} and w _{w + 2 are} resolved. The discretization of the term

 (I (x) w ")" in equation (5) is given by

(I (x) w ")" * ^ - ^{i ~ 2} ^ ⁺ ^ ⁱ (35) with

^, = (, K ^M. (36)

By choosing the central difference approximation, equation (35) at the edges depends on the values and I _{N +} , which in practice depends on the values

/ _] and I _N can be replaced.

For the further procedure, a vector notation (in bold) is recommended.

The vector of boom deflections is called

denotes, whereby the discretization of the term (I (x) w ")" in vector notation as

K ₀ w (38) with the stiffness matrix

I _x + I ₂ -2 /, - _2/2 I _{l +} I ₂ 0 0

-21 _{2 4/2} + / ₃ 2L-2L 0

I _{2 2} -2I -2I _3/2 + _4/3 + / ₄ ^• _2/3 -2 / ₄

 ^ 0 =

0 21 N-2 ^■ 21 Nl -2 + 4 / _N -l 21 Nl

 0 0

 can be expressed.

Likewise, the mass matrix of the mass coating (unit kgm) becomes a diagonal matrix

 defined with the vector

* r = [(* .- '') - - ^)] ⁷ (40) which describes the distance to the tower for each node.

For the distributed acting force becomes the vector

£ = fe. ··· 9 _N ] ( ⁴¹ ) with the entries q, = q (x,) defined, so that the discretization of the partial

Bar differential equation (5) in discretized form as

 e

 (42).

Now the dynamic interaction of steel structure movement and pendulum dynamics will be described.

For this purpose, first the additional point masses on the boom, namely the Gegenballastmasse m _CJ , the replacement mass for the tower m _T and the

Cat mass m, _{r of} the distributed mass matrix, = M ₀ + 0) (43) added.

In addition, the forces and moments can be described, with which tower and load act on the boom. The force due to the tower bend is due to the replacement model

q _T A _x = -c _b w (x _r ).

given by q _r = q (l _cj ). For the determination of the moment by the tower torsion is first the rotation of the boom beam at the clamping point,

needed, from which then the torsional moment

- w _T - 1 + w _T + 1

 T - c (46), which can be approximated by, for example, two equal forces acting equally far away from the tower (lever arm). The value of these two forces is

(47)

2Δx

when Ax is the lever arm. Thus, the moment can be described by the vector q of the forces on the boom. This only needs the two entries

? z - A = -> 4 ₊ A =. ( ⁴⁸ ).

By the horizontal cable force (28) results in the entry

 in q.

Since all forces depend on φ or w, the coupling of structural and pendulum dynamics can be written in matrix notation

 With

[0 (52) and

x _{; r} = [0 ... 1 ... O] ⁷ so that w (x _tr , t) = x w. (53)

At this point it should be noted that the three parameters position of the trolley on the boom x _lr , hoist rope length / and load mass m _L vary during operation. Therefore, (50) is a linear, parameter-variant differential equation whose specific expression can only be determined online at runtime. This must be taken into account in the future observer and control design.

The number of discretization points N should be chosen large enough to provide a precise description of the beam deformation and dynamics.

Thus, (50) becomes a large differential equation system. For the control, however, offers a modal order reduction in order to reduce the plurality of system states to a lower number.

The modal order reduction is one of the most commonly used reduction methods. The basic idea is to first perform a modal transformation, that is, to specify the dynamics of the system based on the eigenmodes (shapes) and the eigenfrequencies. Then be then only the relevant eigenmodes (usually the lowest frequency) are selected and all higher frequency modes neglected. The number of eigenmodes considered is referred to below as ξ.

First, the eigenvectors v, with e [l, N + l] must be calculated, which together with the corresponding natural frequencies ω _ι the eigenvalue problem

K v, = «, ² M v, (54). This calculation can be easily solved by known standard methods. The eigenvectors are then sorted with increasing natural frequency into the modal matrix

V = [v, v ₂ ...] (55) written. The modal transformation can then be carried out via the calculation

z + V ^{~ l} M ^'l KVz = ν ^~ Μ ^{' ι} Βγ (56) where the new state vector z (t) = V ^~] x (t) contains the amplitudes of the eigenmodes. Since the modally transformed stiffness matrix k has a diagonal shape, the modally reduced system can be easily implemented by limiting it to the first ξ columns and rows of this system

z _r + D _r z _r + K _r z _r = B _r r. (57), where the state vector z _r now only describes the few ξ modal amplitudes. In addition, the entries of the diagonal damping matrix D _r can be determined by experimental identification.

Three of the most important eigenmodes are shown in FIG. The uppermost describes the slowest eigenmode, which is dominated by the pendulum motion of the load.

The second eigenmode shown has a clear tower bend, while in the third of the boom bends significantly. All eigenmodes whose natural frequencies can be excited by the slewing drive should be taken into account. The dynamics of the slewing gear drive is advantageously approximated as a PT1 link that provides the dynamics

 uy

y = i_ (58) with the time constant T _y . In conjunction with equation (57) this is the case

with the new state vector x = [z _r z _r γ γ] ^τ and the control signal

Target speed of the slewing gear.

For the observer and the control of the pivoting dynamics, the system (59) can add an output vector y

 x = A x + B u (60) y = C x (61) so that the system is observable, i. that all states in the vector x can be reconstructed through the outputs y, as well as finitely many time derivations of the outputs, and thus can be estimated at runtime.

The output vector y describes exactly the rotation rates, expansions or accelerations, which are measured by the sensors on the crane.

On the basis of the model (61), for example, an observer 345, cf. FIG.

2, in the form of the (62), where the value P is derived from the algebraic Riccati equation 0 = PA + PA ^T + QP C ^T R ^'] can follow CP (63), which can be easily solved by standard methods. Q and R represent the

Covariance matrices of process and measurement noise and serve as design parameters of the Kalman filter.

Since equations (60) and (61) describe a parameter-variable system, the solution P of equation (63) is always valid only for the corresponding parameter set {x _tr , l, m _L }. The standard methods for solving algebraic problems

Riccati equations are, however, quite computationally intensive. In order not to have to evaluate equation (63) at runtime, the solution P for a finely resolved map in the parameters x _lr , l, m _{L can} be precalculated offline. At runtime (online), the value is then selected from the map whose parameter set {x _lr , l, m _L } is closest to the current parameters.

Since all system states x can be estimated by the observer 345, the control can be in the form of state feedback

realize. The vector x _{ie {contains} the desired states, which are typically all zero in the rest position (except for the rotation angle γ). While descending a trajectory, the values may be non-zero, but should not deviate too much from the rest position around which the model was linearized.

For this purpose, for example, a linear-quadratic approach is suitable, in which the feedback gain K is chosen such that the quality functional

is optimized. For the linear control design, the optimal feedback gain results

K = R ^~ B ^T P, (66) where P is analogous to the Kalman filter over the algebraic Riccati equation 0 = PA + A ^T P - PB C'B ^T P + Q (67).

Since also the gain K in equation (66) depends on the parameter set

{x _lr , l, m _L } is analogous to the procedure for the observer

Generated map. In the context of the regulation, this approach is known by the term "gain scheduling".

To use the control on a tower crane, the observer dynamics (62) can be simulated on a control unit at runtime. For this purpose, on the one hand, the control signals u of the drives, and on the other hand, the measurement signals y of the

Sensors are used. The control signals are in turn calculated from the feedback gain and the estimated state vector according to (62).

Since the radial dynamics can also be represented by a linear model of the form (60) - (61), the control of the radial dynamics analogous to the pivoting dynamics can be used. Both regulations then act independently of one another on the crane and stabilize the pendulum dynamics in the radial direction as well as transversely to the boom, in each case taking into account the drive and structural dynamics.

The following describes an approach to modeling radial dynamics.

This differs from the approach described above for modeling the pivoting dynamics in that the crane is now described by a replacement system of several coupled rigid bodies and not by continuous beams. In this case, the tower can be divided into two rigid bodies, wherein another rigid body can represent the boom, cf. Fig. 9.

In this case, a _y, and ß _y describe the angle between the rigid bodies and _φ ν the radial angle of the load pendulum. P describes the positions of the centroids, with the index _c , for the counterjib, _J for the boom, _TR for the trolley and _r for the tower (in this case the upper one) Rigid body of the tower) stands. The positions depend at least in part on the variables x _TR and / provided by the drives. At the joints between the rigid bodies there are springs with the spring stiffnesses c _a , c _g and dampers whose viscous friction is described by the parameters d and d _a .

The dynamics can be derived from the well-known Lagrange formalism. Here are the three degrees of freedom in the vector

q = (a _y, ß _y J _y)

summarized. These can be used to translate kinetic energies

as well as the potential energies due to gravity and spring stiffness

^ po "= 8 ^(m T ^P T ,: + ^m + JP + ^/ _Ίΐ: + '' ^Λ:)! + | _(α ⁺ ß ^

express. Since the rotatory energies are negligibly small compared to the translatonic ones, the Lagrangian function can be considered as

^ ¹ kin ¹ pot

be formulated. This results in the Euler-Lagrange equations

 d BL dL _.

 dt dq, dq,

with the generalized forces Q ', which influences the non-conservative

 Forces, such as the damping forces describe. Written out, the three equations result

 d dL dL

(68) dd dy _y da _y

dt dß _y dßy

 d dL dL

(70) dt dj> _y 9, By inserting L and calculating the corresponding derivatives, very large terms result in these equations, so that an explicit representation here does not make sense.

The dynamics of the drives of the creaser as well as the hoist can usually be well approximated by the PT1 dynamics of the first order

 1

 TR (71)

- TR

i ^' = - (u, -i). (72)

In it, r, the corresponding time constants and u _{t describe} the target speeds.

If you now keep all drive-related variables in the vector

 (73), the coupled radial dynamics of drive, pendulum and structural dynamics can be represented as

(74) or by switching to runtime as the nonlinear dynamics in the form q = f (q, q, x _a ) (75)

Since the radial dynamics is thus present in minimum coordinates, an order reduction is not required. However, due to the complexity of the equations described by (75), an analytic offline precomputation of the Jacobi is

 dt

 Matrix not possible. From (75) a linear model of the form (60) for the

 s [q>]

To obtain control, therefore, a numerical linearization can be performed at runtime. For this purpose, first the rest position (q ₀ , q ₀ ) can be determined, for which 0 = f (q ₀ , q ₀ , 0)

is satisfied. Then the model is beyond the equations

linearize and there is a linear system as in equation (60). By choosing a suitable sensor for structural and pendulum dynamics, for example with the aid of gyroscopes, there results a measuring output as in (61), through which the radial dynamics can be observed.

The further procedure of the observer and control design corresponds to that for the pivoting dynamics.

As already mentioned, the deflection of the hoist rope relative to the vertical 62 can not only be determined by an imaging sensor on the trolley, but also by an inertial measuring device on the load hook.

Such an inertial measuring device IMU can in particular comprise acceleration and rotation rate sensor means for providing acceleration and yaw rate signals, which on the one hand indicate translational accelerations along different spatial axes and, on the other hand, yaw rates or gyroscopic signals with respect to different spatial axes. Rotational speeds, but in principle also rotational accelerations or both, can be provided as rotation rates.

Advantageously, the inertial measuring device IMU can detect accelerations in three spatial axes and rotation rates about at least two spatial axes. The acceleration sensor means may be triaxial and the gyroscope sensor means may be biaxial.

The inertial measuring device IMU attached to the load hook can advantageously transmit its acceleration and rotation rate signals and / or signals derived therefrom wirelessly to the control and / or evaluation device 3 or its pendulum transmit damping device 340, which may be attached to a structural part of the crane or arranged separately in close proximity to the crane. In particular, the transmission may take place to a receiver REC, which may be attached to the trolley 206 and / or to the suspension from which the hoist cable runs. Advantageously, the transmission can be carried out, for example, via a WLAN connection, cf. Fig. 10.

As shown in FIG. 13, the load hook 208 can tilt with respect to the hoist rope 207 depending on the connection in different directions and in various ways. The diagonal pull angle β of the hoist rope 207 need not be identical to the orientation of the load hook. In this case, the tilt angle ε ß describes the tilting or rotation of the load hook 207 relative to the oblique tension β of the hoist rope 2017 or the rotation between inertial coordinates and load hook coordinates.

For the modeling of the pendulum behavior of a crane, the two pendulum directions in the direction of travel of the trolley, i. in the longitudinal direction of the boom on the one hand and in the direction of rotation or arc around the tower axis, i. in the direction transverse to the longitudinal direction of the boom, to be considered separately, since these two oscillations hardly influence each other. Each pendulum direction can therefore be modeled two-dimensionally.

Considering the model shown in Fig. 12, the pendulum dynamics can be described using the Lagrangian equations. The trolley position s _x (t), the rope length l {t) and the rope or pendulum angle ß (t) depending on

Time t is defined, whereby in the following, for the sake of simplicity and for better readability, the time dependence is no longer specified specifically by the term (t). First, the load hook position in inertial coordinates as

be defined, the time derivative

- i sin (ß) - lj3 cos (ß)

r = (102) /? sin (?) - cos (/?) describes the inertial velocity using - = β.

 dt

 hook acceleration

(si _x - 27 ßl / m coss ß - / ssiinn ß R + + l lssß ²² s siinn ß /? - l / ß / ^' ? mcossß R \

r ^:

21 ß sin ß - l ^' cosß + lß ² cos? + //? ^' sin ß is not needed for the derivation of the load dynamics, but used for the design of the filter, as explained.

The kinetic energy is determined by

T = -mr ^T r (104) 2

wherein the mass m of the load hook and the load is eliminated later. The potential energy due to gravity corresponds

F = -mr ^r g, g = (0 - gj, (105)

With the gravitational acceleration g.

Since V does not depend on r, the Euler-Lagrange equation is d dT BT dV _{n ΙΛ η} ^

 + = 0 (106) dt dq dq dq where the vector q = [ß ß describes the generalized coordinates. This gives the pendulum dynamics as a non-linear differential equation of the second order with respect to β,

ls + 2iss - s _x cos ß + g sin ß = 0. (107) The dynamics in the y - z plane can be expressed analogously.

In the following, the acceleration s _{x of} the trolley or of a gantry crane runner is considered as a known system input variable. This can sometimes be measured directly or estimated based on the measured trolley speed. Alternatively or additionally, the Katzbeschleunigung can be measured with a separate the trolley Accelerometer or estimated when the drive dynamics is known. The dynamic behavior of electric crane drives can be determined by the load behavior of the first order Estimated, wherein the input signal u _x corresponds to the desired speed and T _{x is} the time constant. With sufficient accuracy, no further measurement of the acceleration is needed.

The tilt direction of the load hook is described by the tilt angle ε _β , cf. Fig. 13.

Since the rate of rotation or rate of tilt is measured by gyroscopy, the model underlying the estimate of the tilt corresponds to the simple integrator

έ _β = ω _β (109) from the measured rate of rotation ω _ρ to the tilt angle.

The IMU measures all signals in the co-moving, co-rotating body-fixed coordinate system of the load hook, which is marked with the preceding index K, while vectors in inertial coordinates with / are marked or remain without any index. Once ε _{β is} estimated, the measured

Acceleration _K a ⁼ [ _K a _{x K} ^a _z J ⁱⁿ load hook coordinates to _K a in inertial coordinates are transformed, using cos ^) sin ^)

 (110) - sin ^) cos (£ ^)

 The inertial acceleration may then be based on estimating the pendulum angle

(107) and (103).

Assessing the rope angle β requires an accurate estimation of the tilting of the load hook ε _β . In order to estimate this angle on the basis of the simple model according to (109), an absolute reference value is needed because the gyroscope is limited in accuracy and an output value is unknown. In addition, the gyroscopic measurement is regularly superimposed by an approximately constant deviation, which is inherent to the measurement principle. Furthermore, it can not be assumed that ε _β generally oscillates around zero. Therefore, the acceleration sensor is used to to provide such reference value by the gravitational acceleration constant (which occurs in the low frequency signal)

Is known and in load hook coordinates j _f g = - «[- sin (^) cs (s _ß )]. (1 12) is transformable. The measured acceleration is the sum of (103) and (112)

_K a = _K r -K & ( ^{1 3} ) The negative sign of _K g results from the fact that the

Gravitational acceleration due to the sensor principle is measured as a fictitious upward acceleration.

Since all of the components are generally significantly smaller than g and oscillate around zero, the use of a low pass filter with sufficiently low blanking frequency allows the approximation

 ^ «- ^. (114)

Dividing the x component by the z component gives the reference tilt angle for low frequencies

The simple structure of the linear pendulum dynamics of (109) allows the use of various filters to estimate the orientation. An option is a so-called.

continuous-time Kalman Bucy filter which can be adjusted by varying the process parameters and noise measurement. In the following, however, a complementary filter as shown in Fig. 14 is used, which can be adjusted in terms of its frequency characteristic by selecting the high-pass and low-pass transfer functions.

As the block diagram of FIG. 14 shows, the complementary filter can be designed to estimate the direction of the load hook tilt ε _β . A high pass filtering of the

Gyroscope _signal co _ß with G _hpl (s) gives the offset-free yaw rate _β and after Integration of a first tilt angle estimation ε _{β ω} . The further estimate

 from the signal ^ a of the acceleration sensor.

In particular, first, a simple high-pass filter with the transfer function

G (116) s + a> ₀

and very low blanking frequency co ₀ can be applied to the gyroscope signal ω _β to eliminate the constant measurement offset. Integration yields the gyroscope-based tilt angle estimate ε _{β ω,} which is relatively accurate for high frequencies but is relatively inaccurate for low frequencies. The basic idea of the complementary filter is to sum up ε _{β ω} and ε _{β α} or to link them together

Frequencies of ε _{β ω} are weighted more heavily by using the high-pass filter and the lower frequencies of ε _{β α} are weighted more heavily by the use of the low-pass filter, since (1 15) is a good estimate for low frequencies. The transfer functions can be selected as simple filters of the first order, namely

 V fit

G _hp2 (s) =, G _lp (s) = (1 17)

 s + ω s + ω

wherein the Ausblendfrequenz ω is chosen lower than the oscillation frequency. There

G _hp2 (s) + G _lp (s) = l (118) holds for all frequencies, we do not scale the estimate of ε _β incorrectly.

Based on the estimated load hook orientation, the inertial acceleration, a, of the load hook can be determined from the measurement of _K S using (1 10), which allows for the design of an oscillator-based observer (107), and rotated acceleration measurement

 , a = r - g. (1 19)

Although both components of this equation can be used equally for the estimation of the pendulum angle, good results can also be obtained only using the x-component, which is independent of g. In the following it is assumed that the pendulum dynamics is superimposed by process-conditioned background noise w: N (0, 0 and measurement noise v. N (0, i)), so that it can be expressed as a nonlinear stochastic system, namely x = f (x, w) + w, x (0) = x ₀ (120) y- h (x, u) + v where the state vector x = [ß ßj For determination of the states, the continuous, extended Kaiman filter x = f ( x, u) + K (y -h (x, u)), x (0) = x ₀ ,

P = AP + PA ^T - PC ^T R ^× CP + Q, P (0) = ₀ ,

K = PC ^T R ^~ (121)

^ - Ix, «'

 OX OX

be used.

 The spatial state representation of the pendulum dynamics according to (107) is β

 (122)

(21 ß - s ^' _x cos + g sin ß) where the cat acceleration u = s _{x is} treated as the input of the system. In order to define a system output, the horizontal component of the load hook acceleration can be famulated from (1 9) as a function of the system states, with the result:

0

= s _x - 2 ßl cos ß - i ^' sm ß + lß ² sin ß - Iß cos ß

= (1-cs (β) ² ) s _x + sin β (-l + g cos β + Iβ ² ) The horizontal component _x g the acceleration of gravity is naturally zero. In this case, /, / can be reconstructed from the measurement of /, for example using the drive dynamics according to (108). When using (123) as a measuring function

Kx) =, a _x , (124) the linearization term is given as

 0 1

(- g cos β - s _x sin β) - 2 (125)

The covariance matrix estimates of the process noise Q = I _2x2 , the measurement noise R = 1000 and the initial error covariance matrix P = 0 _2x2 .

As FIG. 15 shows, the pendulum angle corresponds to that by means of an extended Kalman filter

(EKF) is estimated or even determined by a simple static approach, quite well a validation measurement of the pendulum angle at a gimbal joint by means of a rotary encoder on the trolley.

It is interesting that the calculation by means of a relatively simple static approach delivers comparably good results like the extended Kalman filter. Therefore, the pendulum dynamics according to (122) and the alignment equation according to (123) can be linearized around the stable state β = β = 0. Furthermore, if the rope length / is assumed to be constant such that = / = 0, the result is for the linearized system

x = (127)

g 0] x (128) and ₇ a serves as the reference value for the output. Neglecting the

Dynamic effects according to (127) and considering only the static output function (128), the pendulum angle from the simple static relationship ß = - ^ (129)

 G

which, interestingly, is independent of /. Fig. 15 shows that the results obtained are as accurate as those of the Kalman filter.

Thus, using β and Equation (101), an accurate estimation of the load position can be achieved.

When modeling the dynamics of the speed-based crane drives according to (108) along with a parameter determination, the resulting

Time constants according to T _t <very small. In this respect, dynamic effects of the drives can be neglected.

In order to specify the pendulum dynamics with the drive speed s _x instead of the drive acceleration s _x as the system input variable, the linearized dynamic system gigs (127) can be "increased" by integration, with the result that

The new status vector x = [Jff ß \. The dynamics obviously remain the same, whereas the physical meaning and the input change. As distinct from (127), β and β should be stabilized at zero, but not the time integral jβ. Since the controller should be able to maintain a desired speed s _xd , the desired stable state should be permanently x = 0 as

G be calculated. This can also be considered as a static prefilter F in the frequency domain, which ensures that \ vn _\ G _ux (s) = lF for the transfer function from

Speed input to the first state

<v *, ^{(J) =} -rr- ⁽¹³²⁾ . The first component of the new state vector x can be estimated using a Kalman-Bucy filter based on (130), with the system output y = [θ l] x.

The result is similar when designing a controller based on (127) and the

Motor controller is controlled by the integrated input signal «= ^ (r) dr.

The obtained feedback can be determined as a linear-quadratic (LQR) controller, which can represent a linear-quadratic Gaussian-type controller (LQG) along with the Kalman-Bucy filter. Both the feedback and the Kalman adjustment factor can be adapted to the rope length /, for example by using control factor diagrams.

In order to control the load hook closely along trajectories, a two-degree-of-freedom structure as shown in FIG. 6 may be used in conjunction with a trajectory planner providing a C ³ differentiable reference trajectory for the load hook position. The cat position can be added to the dynamics system according to (130), which gives the system

where u = s _x , so that the flat output

is what corresponds to the hook position of the linearized case constellation. State and input can be algebraically parametrized by the flat output and its derivatives, with z = [zz zj as

 w Iz

Μ = Ψ "(Ζ, Ζ) = Ζ + - (137) g which allows the algebraic calculation of the reference states and the nominal input position signal from the planned trajectory for z. A change of the setting point shows that the nominal error can be kept close to zero, so that the feedback signal u _{ß of} the controller K significantly smaller than the nominal

Input manipulated variable u _ff . In practice, the input manipulated variable may be set to _uβ = 0 when the signal of the intial wireless meter is lost.

As FIG. 16 shows, the regulator structure provided with two degrees of freedom can have a

Trajectory planner TP have a gentle trajectory ze C ³ for the flat

Output with limited derivations, the input quantity Ψ "and the parameterization of the state, as well as the controller K.

Claims

claims

A crane, in particular a tower crane, with a hoist rope (207) which runs from a crane jib (202) and carries a load receiving means (208), drive means for moving a plurality of crane elements and methods of the load receiving means (208), a control device (3) for controlling the drive means such that the load receiving center (208) moves along a travel path, as well as a pendulum damping device (340) for damping oscillations of the load receiving means (208) and / or the hoisting rope (207), wherein the pendulum damping device (340) comprises a pendulum sensor (60 ) for detecting oscillatory movements of the hoist rope (207) and / or the load receiving means (208) and a controller module (341) with a closed loop for influencing the control of the drive means in response to a feedback signal of the pendulum sensor (60) returned to the control loop characterized in that the pendulum damper (340) has a structure Dynamic sensor system (342) for detecting deformations and / or dynamic internal movements of structural components of the crane and the controller module (341) of the pendulum damping device

(340) is designed to take into account when influencing the control of the drive means, both the pendulum signal of the pendulum sensor (60) and the feedback control structure of the structural dynamics signals that indicate deformations and / or dynamic insignia movements of the structural components.

2. Crane according to one of the preceding claims, wherein the controller module

(341) has a two-degree-of-freedom control structure and / or has a pre-control module (350) for pre-controlling the actuating signals for the drive devices in addition to the closed loop.

3. Crane according to the preceding claim, wherein the pilot module (350) is designed as a differential flatness model.

4. Crane according to one of the two preceding claims, wherein the pilot module (350) is adapted to carry out the precontrol without consideration of the pendulum signals of the pendulum sensor (60) and the structural dynamics signals of the structural dynamics sensor (342).

5. A crane according to one of the preceding claims 2 to 4, wherein the precontrol module (350) is associated with a notch filter means (353) for filtering the input signals supplied to the precontrol, said notch filter means (353) being adapted to be excitable natural frequencies from said input signals to eliminate the structural dynamics.

6. Crane according to one of the preceding claims 2 to 5, wherein the pre-control module (350) a trajectory planning module (351) and / or a setpoint filter module (352) for determining a desired course for the load receiving means position and their temporal derivatives of predetermined setpoints for the load-receiving means are assigned. Crane according to the preceding two claims, wherein the notch filter means (353) is provided between the trajectory planning module (351) and the set point filter module (352) on the one hand and the pilot control module (350) on the other hand.

Crane according to one of the preceding claims, wherein the controller module (341) has a control model, which divides the structural dynamics of the crane into independent parts, the at least one pivoting dynamics part, which takes into account the structural dynamics with respect to pivoting of the boom (202) about the upright crane pivot axis, and a radial dynamic part that accounts for structural dynamics movements parallel to a vertical, boom-parallel plane.

Crane according to one of the preceding claims, wherein the structural dynamics sensor (342) at least

 a radial dynamic sensor for detecting dynamic

 Movements of the crane structure in an upright plane parallel to the crane boom (202), and

 a pivoting dynamic sensor for detecting dynamic

 Movements of the crane structure around an upright crane rotation axis, in particular tower axis (205)

and the controller module (341) of the pendulum damping device (340) is designed to control the drive devices, in particular a cat drive and slewing drive, depending on the detected dynamic movements of the crane structure in the upright, cantilever plane and the detected dynamic movements of the crane structure to the to influence upright crane rotation axis.

Crane according to one of the preceding claims, wherein the structural dynamics sensor (342) further

- Has a Hubdynamik sensor for detecting vertical dynamic deformations of the crane jib (202) and the controller block (341) of the pendulum damping device (340) is adapted to influence the control of the drive means, in particular a hoist drive, in dependence of the detected vertical dynamic deformations of the crane jib (202).

11. Crane according to one of the preceding claims, wherein the structural dynamics sensor (342) is adapted to determine dynamic torsions of a crane boom carrying crane tower (201) and / or the crane jib (202) and the controller module (341) of the pendulum damping device (341) ( 340) is designed to influence the activation of the drive devices as a function of the detected dynamic torsions of the crane jib (202) and / or of the crane tower (201).

12. Crane according to the preceding claim, wherein the structural dynamics sensor (342) is adapted to detect all eigenmodes of the dynamic torsions of the crane jib (202) and / or the crane tower (201) whose natural frequencies are within a predetermined frequency range.

13. Crane according to the preceding claim, wherein the structural dynamics sensor (342) at least one, preferably a plurality of tower sensor (s) which is spaced from a node of a tower oscillation, for detecting Turmverwindungen and at least one, preferably a plurality of cantilever sensor ( en) spaced from a node of a cantilever natural vibration for detecting cantilevers.

14. Crane according to one of the preceding claims, wherein the structural dynamics sensor (342) strain gauges and / or Beschleinigungssensoren and / or rotation rate sensors, in particular in the form of gyroscopes, for detecting the deformations and / or dynamic insich movements of structural components of the crane, wherein the acceleration sensors and / or yaw rate sensors are preferably designed to detect three axes.

15. Crane according to the preceding claim, wherein the structural dynamics sensor (344) at least one rotation rate and / or acceleration sensor and / or strain gauges for detecting dynamic Turmverformungen, at least one rotation rate and / or acceleration sensor and / or strain gauges for detecting dynamic Boom deformations has.

16. Crane according to one of the preceding claims, wherein the pendulum sensor (60) comprises a detection device for detecting and / or estimating a deflection (φ; ß) of the hoist rope (207) and / or the load receiving means (208) relative to a vertical (61) and the control module (341) of the pendulum damping device (340) is designed to control the drive devices in dependence on the determined deflection (<p; ß) of the hoist rope (207) and / or the load receiving means (208) relative to the vertical (61) influence.

17. Crane according to the preceding claim, wherein the detection device (60) has an image-giving sensors, in particular a camera (62), in the region of a suspension point of the hoist rope (207), in particular a trolley (206), substantially vertically downwards wherein an image evaluation device (64) for evaluating an image provided by the imaging sensor with respect to the position of the load receiving means (208) in the provided image and determining the deflection (φ) of the load receiving means (208) and / or the hoist rope (207) and / or the deflection speed relative to the vertical (61) is provided.

18. Crane according to one of the two preceding claims, wherein the detection device (60) mounted on the load receiving means (208) Inertialmeßeinrichtung (IMU) with acceleration and gyro sensor means for providing acceleration and yaw rate signals, first determining means (401) for determining and / or estimating a tilt (ερ) of the load receiving means (208) from the acceleration and yaw signals of the inertial measuring (IMU) and second determining means (410) for determining the deflection (ß) of the hoist rope (207) and / or the load receiving means (208) relative to the vertical (61) from the determined tilting (ε _β ) of the load receiving means (208) and an inertial acceleration there ) of the load receiving means (208).

19. A crane according to the preceding claim, wherein the first determining means (401) comprises a complementary filter (402) with a high pass filter (403) for the rotation rate signal of the inertial measuring device (IMU) and a low pass filter (404) for the acceleration signal of the inertial measuring device (404). IMU) or a signal derived therefrom, which complementary filter (402) is adapted to provide a rate-based estimate of the tilt (ε _β , _ω ) of the load handler (208) based on the high-pass-filtered yaw rate signal and an acceleration-based tilt estimate (ep , _a ) of the load receiving means (208), which is based on the low-pass filtered acceleration signal to link together and from the associated rate of rotation and acceleration-based estimates of the tilt (ερ, _ω ; ε _{β, 3} ) of the load receiving means (208) the desired tilt (ε _β ) of the load receiving means (208) to determine.

20. Crane according to the preceding claim, wherein the rotational rate-based estimate of the tilt (ε _{β, ω} ) of the load receiving means (208) comprises an integration of the high-pass-filtered yaw rate signal and / or the acceleration-based estimation of the tilt (ε _{β 3} ) of the load receiving means (208) the quotient of a measured horizontal acceleration ( _k a _x ) and a measured Vertical acceleration ( _k a _z ) is based, from which the acceleration-based

Estimation of the tilt (ε _{β, 3} ) on the basis of the relationship ε _{β α} =

is won.

21. Crane according to one of the preceding claims 18 to 20, wherein the second determining means (410) comprise a filter and / or Obereinereinrichung, which takes into account the determined tilt (ß ß) of the load receiving means (208) and an inertial acceleration (la ) determines the deflection (φ; ß) of the hoist rope (207) and / or the load receiving means (208) relative to the vertical (61) on the load receiving means (208).

22. Crane according to the preceding claim, wherein the filter and / or observer device comprises a Kalman filter (41 1), in particular an extended Kalman filter.

A crane according to any of the preceding claims 18 to 22, wherein said second determining means (410) includes calculation means for calculating the deflection (β) of the hoist rope (207) and / or the load handler (208) from the vertical (61) from the quotient a horizontal inertial acceleration Ga _x ) and the gravitational acceleration (g).

24. Crane according to one of the preceding claims 18 to 23, wherein the inertial measuring device (IMU) comprises a wireless communication module for wireless transmission of measurement signals and / or signals derived therefrom to a receiver, wherein the communication module and the receiver preferably via a WLAN connection are connected to each other and the receiver is arranged on the trolley, from which the hoist cable runs.

25. Crane according to one of the preceding claims, wherein the controller module (341) comprises a filter and / or observer device (345) for influencing the manipulated variables of drive controllers (347) for driving the drive means, said filter and / or observer device ( 345) is designed to receive as input variables on the one hand the manipulated variables of the drive controller (347) and on the other hand both the pendulum signal of the pendulum sensor (60) and the feedback control structure of the structural dynamics signals indicating deformations and / or dynamic insich movements of the structural components, and as a function of the dynamics-induced movements of crane elements and / or deformations of structural components obtained for certain controller manipulated variables, to influence the controller manipulated variables.

26. Crane according to the preceding claim, wherein the filter and / or observer device (345) as a Kalman filter (346) is formed.

27. Crane according to the preceding claim, wherein in the Kalman filter (346) detected and / or estimated and / or calculated and / or simulated functions that characterize the dynamics of the structural components of the crane are implemented.

28. Crane according to one of the preceding claims, wherein the controller module (341) is adapted to at least one control characteristic, in particular control gains, depending on changes in at least one parameter from the parameter group load mass (mi_), Hubseillänge (I), Katzposition (x _tr ) and discharge, to tighten and / or adapt.

29. A method for controlling a crane, in particular a tower crane, the hoisting rope (207) attached to the load receiving means (208) is moved by drive means, which drive means are controlled by a control device (3) of the crane, said Control of the drive devices of a

Pendulum damping device (340) comprising a controller module (341) is influenced by a closed loop in dependence of pendulum-relevant parameters, characterized in that the closed loop both pendulum signals of a pendulum sensor (60), by means of which oscillations of the hoisting rope and / or the load-receiving means are detected as well as structural dynamics signals of a structural dynamics sensor (342), by means of which deformations and / or dynamic insich movements of the structural components are detected, are returned and from the controller module (341) control signals (u (t)) for driving the drive means in dependence both recirculated pendulum signals of the pendulum sensor (60) and the returned structural dynamics signals of the structural dynamics sensor (342), be influenced.

30. Method according to the preceding claim, wherein the recirculated pendulum signals of the pendulum sensor system (60) as well as the returned structural dynamics signals of the structural dynamics sensor system (342) are fed to a Kalman filter (346), which also contains the manipulated variables of drive controllers (347) as input variables. be supplied to drive the drive means, wherein the Kalman filter (346) in response to said pendulum signals of the pendulum sensor (60), the structural dynamics signals of the structural dynamics sensor (342) and the feedback variables of the drive controller (347) influencing the control variables of the drive controller (347).

31. The method according to one of the two preceding claims, wherein the drive signals for driving the drive means of a control module (341) upstream pilot module (350) are precontrolled, said pilot module (350) is adapted to the pilot control without consideration of the pendulum signals pendulum sensor (60) and the structural dynamics signals of the structural dynamics sensor (342).