CN112255917B - Positioning driving control method, positioning driving control device, positioning driving control system, electronic equipment and storage medium - Google Patents
Positioning driving control method, positioning driving control device, positioning driving control system, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN112255917B CN112255917B CN202011115466.8A CN202011115466A CN112255917B CN 112255917 B CN112255917 B CN 112255917B CN 202011115466 A CN202011115466 A CN 202011115466A CN 112255917 B CN112255917 B CN 112255917B
- Authority
- CN
- China
- Prior art keywords
- vector
- determining
- decoding
- state
- mathematical model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 94
- 238000003860 storage Methods 0.000 title claims abstract description 25
- 239000013598 vector Substances 0.000 claims abstract description 289
- 238000005259 measurement Methods 0.000 claims abstract description 83
- 230000002159 abnormal effect Effects 0.000 claims abstract description 73
- 238000013178 mathematical model Methods 0.000 claims description 75
- 230000006870 function Effects 0.000 claims description 67
- 238000005553 drilling Methods 0.000 claims description 60
- 239000011159 matrix material Substances 0.000 claims description 27
- 238000004590 computer program Methods 0.000 claims description 11
- 238000012545 processing Methods 0.000 description 21
- 238000010586 diagram Methods 0.000 description 16
- 230000005540 biological transmission Effects 0.000 description 11
- 238000004891 communication Methods 0.000 description 11
- 230000007613 environmental effect Effects 0.000 description 9
- 230000007246 mechanism Effects 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 7
- 230000003287 optical effect Effects 0.000 description 5
- 238000013461 design Methods 0.000 description 4
- 230000005236 sound signal Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 230000001133 acceleration Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012417 linear regression Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000005192 partition Methods 0.000 description 2
- 230000001902 propagating effect Effects 0.000 description 2
- 238000013139 quantization Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 241001391944 Commicarpus scandens Species 0.000 description 1
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 239000010949 copper Substances 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 239000003208 petroleum Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Feedback Control In General (AREA)
Abstract
The disclosure relates to a positioning driving control method, a positioning driving control device, a positioning driving control system, electronic equipment and a storage medium, and relates to the field of control. The positioning driving control method comprises the following steps: determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal; obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment; and determining the running of the controlled object based on the decoding vector corresponding to the azimuth information at the second moment. The embodiment of the disclosure can realize the running of the controlled object when the measurement output of the sensor is abnormal.
Description
Technical Field
The present disclosure relates to the field of control technologies, and in particular, to a positioning driving control method, an apparatus, a system, an electronic device, and a storage medium.
Background
In recent years, as a supporting industry of national production, the petroleum industry has been receiving wide attention from all social circles. Exploration and development of marine oil has been known for over 100 years. The offshore drilling platform is used as an essential device for offshore oil exploitation, and is developed synchronously with offshore oil exploration and development from the beginning. The movable drilling platform (ship) is not operated in a fixed sea area, and is suitable for operation in displacement, different sea areas, different water depths and different directions. Therefore, the design of the dynamic positioning system is always a key technical problem.
However, the existing control method for the power system of the drilling platform cannot solve the problem when the sensor has an abnormal value, and because the sensor works in a severe environment for a long time and is easy to break down, age and the like, the obtained output value is likely to be the abnormal value and deviates from the normal value to a great extent, so that the remote judgment is influenced, an error control signal is given, and the effective control of the position of the drilling platform cannot be completed. In addition, since the data of the offshore drilling platform is usually transmitted to a remote location through a network, the data transmission safety problem becomes a focus of attention of system safety personnel.
Disclosure of Invention
The present disclosure provides a positioning driving control method, device, system, electronic device and storage medium technical solution to realize driving of a controlled object when a measurement output of a sensor is abnormal.
According to an aspect of the present disclosure, there is provided a positioning travel control method including:
determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal;
obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment;
and determining the running of the controlled object based on the decoding vector corresponding to the azimuth information at the second moment.
Preferably, the method for determining the gain corresponding to the controller according to the decoding vector corresponding to the orientation information of the controlled object when the measurement output of the sensor is abnormal includes:
acquiring a mathematical model corresponding to the angle and the position of a controlled object and a measurement output abnormal vector of a sensor in the mathematical model;
determining a state observer according to the mathematical model and the measurement output abnormal vector, and determining an intermediate state vector according to a decoder;
determining a coding vector according to the estimation vector of the state observer and the intermediate state vector; decoding the coding vector to obtain a decoding vector;
determining a controller of the controlled object according to the decoding vector and a state observation model of the mathematical model, and solving the gain of the controller;
and/or, the orientation information comprises at least a position and/or a velocity;
and/or the controlled object is an ocean drilling platform.
Preferably, the method of determining a state observer from the mathematical model and the measurement output anomaly vector comprises:
obtaining the measurement output abnormal vector, and determining a saturation function according to the measurement output abnormal vector;
determining the state observer according to the saturation function and a state observation model of the mathematical model;
and/or the presence of a gas in the interior of the container,
the method of determining an intermediate state vector from a decoder, comprising: obtaining an intermediate state vector at the moment according to the state observation model of the mathematical model and a decoding vector at the last decoding moment of the decoder;
and/or, the method of determining a code vector from an estimated vector of the state observer and the intermediate state vector, comprising:
and determining a coding vector according to the difference value of the estimation vector and the intermediate state vector at the same coding moment.
Preferably, the method of determining a saturation function from the measurement output anomaly vector comprises:
acquiring a set maximum value vector corresponding to the measurement output abnormal vector;
determining an absolute value of the measurement output anomaly vector;
and determining the size of a saturation function according to the absolute value and the corresponding set maximum value vector thereof, and determining the sign of the saturation function according to the measurement output abnormal vector.
Preferably, the method for decoding the encoded vector to obtain a decoded vector includes:
obtaining a plurality of code words according to the coding vector, and determining a plurality of central points of corresponding hyper-rectangles of the code words;
and respectively decoding the corresponding code words according to the plurality of central points to obtain the decoding vectors.
Preferably, the method for determining a controller of the controlled object according to the decoded vector and the state observation model of the mathematical model and obtaining the gain of the controller includes:
determining a controller of which the power equipment in the controlled object has gain to be determined according to the decoding vector;
determining a mathematical model corresponding to the controlled object in a closed-loop form based on a state observation model controller of the mathematical model;
and determining a gain matrix according to the mathematical model corresponding to the closed-loop form and the input-state stability index, and solving the gain to be determined according to the gain matrix to obtain the gain of the controller.
According to an aspect of the present disclosure, there is provided a positioning travel control apparatus including:
the gain determining unit is used for determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal;
the direction determining unit is used for obtaining a decoding vector corresponding to the direction information of the second moment according to the controller and the decoding vector corresponding to the direction information of the first moment;
and the positioning running unit is used for determining the running of the controlled object based on the decoding vector corresponding to the azimuth information at the second moment.
According to an aspect of the present disclosure, there is provided a positioning driving control system for an offshore drilling platform, comprising:
a drilling platform power system;
the drilling platform power system is used for determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the marine drilling platform when the measurement output of the sensor is abnormal; obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment;
and the power system of the drilling platform determines the running of the marine drilling platform based on the decoding vector corresponding to the azimuth information at the second moment.
According to an aspect of the present disclosure, there is provided an electronic device including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to: the positioning travel control method is executed.
According to an aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described positioning travel control method.
In the embodiment of the disclosure, a positioning driving control method, a positioning driving control device, a positioning driving control system, an electronic device, and a storage medium are provided to realize driving of a controlled object when a measurement output of a sensor is abnormal. The problem of when the sensor produces the abnormal value, bring the influence for going is solved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.
Fig. 1 shows a flowchart of a positioning travel control method according to an embodiment of the present disclosure;
FIG. 2 illustrates a block diagram of a positioning travel control system according to an embodiment of the present disclosure;
FIG. 3 illustrates a graph of disturbance components (ambient interference vectors) according to an embodiment of the present disclosure;
FIG. 4 shows an actual state vector x of a marine drilling platform dynamic positioning closed loop system according to an embodiment of the present disclosure1,kState estimation vector trajectoryAnd decoding the vectorA trajectory;
FIG. 5 shows an actual state vector x of the dynamic positioning closed-loop system of the offshore drilling platform according to the embodiment of the present invention2,kState estimation trajectoryAnd decoding the vectorA trajectory;
FIG. 6 shows a decoding error w of the marine drilling platform dynamic positioning closed-loop system according to an embodiment of the present invention1,kAnd w2,kA trajectory;
FIG. 7 is a block diagram illustrating an electronic device 800 in accordance with an exemplary embodiment;
fig. 8 is a block diagram illustrating an electronic device 1900 in accordance with an example embodiment.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
It is understood that the above-mentioned method embodiments of the present disclosure can be combined with each other to form a combined embodiment without departing from the logic of the principle, which is limited by the space, and the detailed description of the present disclosure is omitted.
In addition, the present disclosure also provides a positioning driving control device, a control system, an electronic device, a computer-readable storage medium, and a program, which can be used to implement any positioning driving control method provided by the present disclosure, and the corresponding technical solutions and descriptions and corresponding descriptions in the method section are omitted for brevity.
In an embodiment of the present disclosure, MTRepresenting the transpose of the matrix M, M-1Representing the inverse of matrix M.Representing an n-dimensional euclidean space,representing the set of all real matrices of order n x m.Representing a set of integers. I and 0 denote an identity matrix and a zero matrix, respectively. A matrix P > 0 means that P is a true symmetric positive definite matrix,andrespectively representing the mathematical expectation of the random variable x and the mathematical expectation of the random variable x under the condition of y. | x | | represents the euclidean norm of the vector x. diag { A1,A2,…,AnDenotes that the diagonal block is the matrix A1,A2,...,AnThe symbol indicates the omission of the symmetric term in the symmetric block matrix. If M represents a symmetric matrix, then λmax(M),λmin(M) represents the maximum and minimum eigenvalues of M, respectively. SymbolRepresenting a kronecker multiplication operation.If functionIs strictly increasing, then γ (-) is said to beA class function. If it is notAnd when s → ∞, γ(s) → ∞, then we call the function γ (·) asA class function. For mappingIf k is determined to beClass function, and for a certain s, when k → ∞, the value is 0, then call itIs composed ofA class function. If the matrix dimension is not specified explicitly in the specification, it is assumed that the dimension is suitable for algebraic operation of the matrix.
Fig. 1 illustrates a flowchart of a positioning travel control method according to an embodiment of the present disclosure, which, as illustrated in fig. 1, includes: step S101: determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal; step S102: obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment; step S103: and determining (controlling) the traveling of the controlled object based on the decoded vector corresponding to the azimuth information at the second time. So as to realize the running of the controlled object when the measurement output of the sensor is abnormal. The problem of when the sensor produces the abnormal value, bring the influence for going is solved. The first time is a time before the second time, for example: the first moment was 9 a.m.: 00, second time 9 am: 05.
after determining the gain corresponding to the controller, the controller may obtain a decoding vector corresponding to the azimuth information at the second time from a decoding vector corresponding to the azimuth information at the first time, and the controlled object travels based on the decoding vector corresponding to the azimuth information at the second time. The method introduces the encoding and decoding communication protocol, so that no real data can be obtained even if the data is stolen in the transmission process, and the phenomenon of unsafe data is effectively avoided. Therefore, the method not only has innovativeness in theory, but also can meet the engineering application requirements.
Step S101: and determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal.
In the present disclosure, the method for determining a gain corresponding to a controller based on a decoded vector corresponding to orientation information of a controlled object when a measurement output of a sensor is abnormal includes: acquiring a mathematical model corresponding to the angle and position measurement of a controlled object and a measurement output abnormal vector of a sensor in the mathematical model; determining a state observer according to the mathematical model and the measurement output abnormal vector, and determining an intermediate state vector according to a decoder; determining a coding vector according to the estimation vector of the state observer and the intermediate state vector; decoding the coding vector to obtain a decoding vector; and determining a controller of the controlled object according to the decoding vector and the state observation model of the mathematical model, and solving the gain of the controller. Wherein the orientation information comprises at least a position and/or a velocity; the controlled object may be an offshore drilling platform.
In an embodiment of the present disclosure, before the obtaining of the mathematical model corresponding to the angle and the position of the controlled object, the determining of the mathematical model includes: acquiring an environmental interference vector of the controlled object, a control input vector of power equipment and a vector corresponding to azimuth information; and determining the mathematical model based on the environmental interference vector, the control input vector of the power equipment and the vector corresponding to the orientation information.
For example, the position and speed measurement information of the drilling platform in three different degrees of freedom can be measured in real time through a position sensor and a speed sensor, the position and speed measurement information in three different degrees of freedom is a vector corresponding to the azimuth information, the environmental disturbance vector of the controlled object is an environmental disturbance force (a nonlinear external disturbance signal) such as wind, wave, flow and the like, the control input vector of the power equipment is a control input signal (vector), and the mathematical model is determined based on the environmental disturbance vector, the control input vector of the power equipment and the vector corresponding to the azimuth information.
In an embodiment of the present disclosure, the mathematical model includes: a state observation model and a sensor measurement output model; the state observation model is used for determining the azimuth information at the K +1 moment according to the disturbance component at the K moment, the control input vector of the power equipment and the azimuth information; and the sensor measurement output model is used for measuring the measurement output corresponding to the orientation information at the moment K.
In an embodiment of the present disclosure, the method for determining the state observation model includes: determining a nonlinear external disturbance function corresponding to the environmental interference vector, and determining a disturbance component at the K moment according to a vector corresponding to the azimuth information at the K moment and the nonlinear external disturbance function; determining a coefficient matrix of the state observation model according to the disturbance component at the moment K, the control input vector and the azimuth information of the power equipment and the azimuth information at the moment K + 1; and determining the state observation model based on the coefficient matrix, the disturbance component at the corresponding K moment, the control input vector of the power equipment and the orientation information. Specifically, a linear regression may be performed on the environmental interference vector to obtain a non-linear external disturbance function corresponding to the environmental interference vector. Similarly, linear regression can be performed on the disturbance component at the time K, the control input vector and the azimuth information of the power equipment and the azimuth information at the time K + 1, and the coefficient matrix of the state observation model is determined.
In an embodiment of the disclosure, a mathematical model of a dynamic positioning system of an offshore drilling platform is provided, the mathematical model comprising a high frequency motion model and a low frequency motion model; a mathematical model of environmental disturbance forces (non-linear external disturbance signals) such as wind, waves, flow and the like, and a dynamic mathematical model of the thruster. A mathematical model of an offshore drilling platform, as follows:
in the formula (1), the first and second groups,a state vector consisting of the position and speed information of the drilling platform at the K moment, and the initial state is s0Satisfies | s0‖2≤0Wherein |2Is a norm of 2, and is,0to set a known constant;the measurement output of the sensor at the moment K;a control input signal (vector) for a thruster (power plant);is a non-linear external perturbation function. The coefficient matrices E, D, B, N are real valued matrices of appropriate dimensions.
In this disclosure, the method of determining a state observer from the mathematical model and the measurement output anomaly vector includes: obtaining the measurement output abnormal vector, and determining a saturation function according to the measurement output abnormal vector; and determining the state observer according to the saturation function and a state observation model of the mathematical model. The present disclosure introduces a saturation function to mitigate the impact of sensor outliers on system performance.
In the embodiment of the present disclosure, the measurement output of the mathematical model and the sensor that may occur is greater than or equal to the set value (vector), and is considered to be a measurement output abnormal value (vector). For example,if the value is greater than or equal to the set value (vector), the measurement output abnormal value (vector) is considered.
In this disclosure, the method of determining a saturation function from the measurement output anomaly vector includes: acquiring a set maximum value vector corresponding to the measurement output abnormal vector; determining an absolute value of the measurement output anomaly vector; and determining the size of a saturation function according to the absolute value and the corresponding set maximum value vector thereof, and determining the sign of the saturation function according to the measurement output abnormal vector.
The method for determining the size of the saturation function according to the absolute value and the set maximum value vector corresponding to the absolute value is that the minimum value of the absolute value and the set maximum value vector corresponding to the absolute value is taken to determine the size of the saturation function.
In an embodiment of the disclosure, the state observer is determined from the state observation model of the mathematical model and the saturation function in the form of:
in the formula (2)Is in a stateAn estimated vector at time k;is in a stateAn estimated vector at time k + 1;an initial vector which is an estimated vector; keFor the observer gain to be designed;for the saturation function, to combat sensor outliers, defined as follows:
wherein,in setting a maximum value vectorIs determined, wherein sign is a sign function. y isnIs the measurement output of the sensor at time k (time n);at k timeThe estimated vector at time (n time).
In order to ensure the rationality of the selection of the upper and lower saturation limits in the second step, a computer is used for carrying out statistics and analysis on a large amount of existing data of the existing drilling platform, and then the set maximum value of the saturation function is selected to be
In the disclosure, a coding and decoding mechanism is introduced to ensure the security of data in the transmission process. The method for determining an intermediate state vector according to a decoder comprises the following steps: and obtaining an intermediate state vector at the moment according to the state observation model of the mathematical model and the decoding vector at the last decoding moment of the decoder.
In an embodiment of the present disclosure, the vector is decoded at the last decoding instantThe state observation model brought into the mathematical model obtains the intermediate state vector at the momentNamely:
In this disclosure, the method of determining a code vector from an estimated vector of the state observer and the intermediate state vector includes: and determining a coding vector according to the difference value of the estimation vector and the intermediate state vector at the same coding moment.
In an embodiment of the present disclosure, an encoding vector ζ (ld) is determined from a difference of the estimated vector and the intermediate state vector at the same encoding time.
In an embodiment of the present disclosure, the method for decoding the encoded vector to obtain a decoded vector includes: obtaining a plurality of code words according to the coding vector, and determining a plurality of central points of corresponding hyper-rectangles of the code words; and respectively decoding the corresponding code words according to the plurality of central points to obtain the decoding vectors.
For theCoding the coded vector zeta (ld) to obtain a series of multi-code wordsCalculating the center point of a hyper-rectangle corresponding to a series of multi-code words, wherein the hyper-rectangle has a plurality of sub-hyper-rectanglesFor example, each sub-hyper-rectangle has a center point within it; and decoding the corresponding code word by using the central point in the sub-hyper-rectangle. Wherein,nxfor coding the dimensions of the vector, hyper-rectanglesc is a coding interval, q is the number of the coding interval partitions, d is a coding step length, l is 1,2,3, wherein ld is a coding moment, wherein | |2Is a 2 norm.
Wherein, the estimated vector at the k time is obtained according to the state observerIf the time K corresponds to the encoding time ld (time K equals time ld), the encoding will be performed at the time KIs converted intoWhere the encoding instant ld belongs to the period of the state observer output. For example: and the encoding time ld is 3, 6 and 9, and the time period K output by the state observer is any integer value from 1 to 10. Decoding the vector according to the dynamic mathematical model and the last decoding time ld-1Obtain the intermediate state vector of the time ld
During the encoding process, the encoder encodes according to the following formula:
when the decoding vector is not at the encoding moment, namely the moment K is not equal to the encoding moment ld, assigning the decoding vector at the moment K to the intermediate state vector at the moment K; decoding the vector according to the dynamic mathematical model and the last decoding time ld-1Obtain the intermediate state vector of the time ld
The decoder decodes the data in the form of the following equation:
Calculating the central point of a series of code words corresponding to a hyper-rectangle, wherein the hyper-rectangle is provided with a plurality of sub hyper-rectangles, and each sub hyper-rectangle is internally provided with the central point; decoding the corresponding codeword using a center point within each sub-hyper-rectangle.
Wherein c is the coding interval of the coding vector, and q is the number of the coding interval partitions.
In the embodiment of the disclosure, in the process of setting the encoding and decoding mechanism, the encoding period d and the number q of quantization intervals may greatly affect the decoding error and thus the performance of the controller. Therefore, the size of the coding period and the number of the quantization intervals can be adjusted in real time according to the actual operation condition of the drilling platform, and d is 3 and q is 10.
In the disclosure, the method for determining a controller of the controlled object according to the decoded vector and the state observation model of the mathematical model and obtaining a gain of the controller includes: determining that the power equipment in the controlled object has the controller with gain to be determined according to the decoding vectorDetermining a mathematical model corresponding to the controlled object in a closed-loop form by a state observation model controller based on the mathematical model; and determining a gain matrix according to the mathematical model corresponding to the closed-loop form and the input-state stability index, and solving the gain to be determined according to the gain matrix to obtain the gain of the controller.
In the embodiment of the disclosure, the decoding vector corresponding to the position and the speed of the marine drilling platform is obtained based on decodingPower equipmentDesigning a controller to further obtain a mathematical model corresponding to the closed-loop form of the controlled object, namely an ocean drilling platform dynamic positioning closed-loop system, wherein the form is as follows:
xk+1=(E+BKc)xk+Df(xk)+BKcwk (4);
The controller gain matrix can be obtained by applying the input-state stability theorem and solving the following convex optimization problem:
wherein Q, Z is positive definite matrix to be solved, matrix G11,G12,G22,And a positive scalar μ3And (5) waiting for solving. In addition, theΓ=[B(BTB)-1(BT)⊥]T,B⊥Is BTZero space orthogonal basis of (i.e. B)T B ⊥0. The gain to be determined of the controller is
Based on the above step S101, the present disclosure substantially provides a method and an apparatus for determining a controller when a measurement output is abnormal, a control system, an electronic device, and a storage medium, including: and determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal. So as to realize the running of the controlled object when the measurement output of the sensor is abnormal. The problem of when the sensor produces the abnormal value, bring the influence for going is solved.
In an embodiment of the disclosure, the method for determining a gain corresponding to a controller according to a decoding vector corresponding to orientation information of a controlled object when a measurement output of a sensor is abnormal includes: acquiring a mathematical model corresponding to the angle and the position of a controlled object and a measurement output abnormal vector of a sensor in the mathematical model; determining a state observer according to the mathematical model and the measurement output abnormal vector, and determining an intermediate state vector according to a decoder; determining a coding vector according to the estimation vector of the state observer and the intermediate state vector; decoding the coding vector to obtain a decoding vector; and determining a controller of the controlled object according to the decoding vector and the state observation model of the mathematical model, and solving the gain of the controller. Wherein the orientation information comprises at least a position and/or a velocity; the controlled object is a power device of the marine drilling platform. The detailed description of the positioning control method can be seen in detail.
Step S102: and obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment.
After determining the gain corresponding to the controller, the controller may obtain a decoding vector corresponding to the azimuth information at the second time from a decoding vector corresponding to the azimuth information at the first time, and the controlled object travels based on the decoding vector corresponding to the azimuth information at the second time. Wherein the orientation information at least comprises a position and/or a velocity, the first time being a time before the second time, for example: the first moment was 9 a.m.: 00, the second moment is 9 a.m.: 05. meanwhile, the present disclosure utilizes a coding and decoding mechanism to ensure the security of data in the network transmission process.
In the embodiment of the disclosure, the mathematical model corresponding to the closed-loop form of the controlled object is xk+1=(E+BKc)xk+Df(xk)+BKcwkWherein the gain K is to be determinedcHas been determined in the above method as a known quantity. Orientation information x based on first time KkCorrespond toDecoded vector (decoded vector corresponding to position and velocity at first time)Through a mathematical model (controller) corresponding to the closed-loop form of the controlled object, a decoding vector (a decoding vector corresponding to the position and the speed of the second moment) corresponding to the azimuth information of the second moment K +1 at the next moment of the first moment K can be obtainedWherein the decoding errorI.e. the orientation information x at the first moment KkCorresponding decoded vectorOrientation information x from the first time KkThe difference of (a).
In the disclosure or the embodiment of the disclosure, the controller determines according to a decoding vector corresponding to the orientation information of the controlled object when the measurement output of the sensor is abnormal, obtains observed information by using an observer capable of resisting the sensor to measure the abnormal value, and ensures the safety of data in the network transmission process by using a coding and decoding mechanism.
Step S103: and determining (controlling) the traveling of the controlled object based on the decoded vector corresponding to the azimuth information at the second time. And the controlled object runs based on the decoding vector corresponding to the azimuth information at the second moment. That is, after the controller outputs the decoded vector corresponding to the azimuth information at the second time, the controlled object (the offshore drilling platform) travels based on the decoded vector corresponding to the azimuth information at the second time as a control signal of the controlled object (the offshore drilling platform). So as to realize the running of the controlled object when the measurement output of the sensor is abnormal. The problem of when the sensor produces the abnormal value, bring the influence for going is solved.
The present disclosure measures drilling platform position and velocity measurement information in three different degrees of freedom in real time via position and velocity sensors. An observer which can resist the sensor to measure the abnormal value is used for obtaining the observed information, and a coding and decoding mechanism is used for ensuring the safety of the data in the network transmission process. And obtaining a decoding error by using the decoding information, and obtaining a controller design method for driving the marine drilling platform according to the specified position by using an input-state stability theorem. Compared with the existing controller design method based on the observer, the control method provided by the invention can resist the abnormal value of the sensor under a coding and decoding mechanism, obtains the control method depending on the linear matrix inequality solution, achieves the purposes of resisting the abnormal value and guaranteeing the data transmission safety, has more practical significance, and is easy to solve and realize.
To obtain the sufficient condition (5) for the controller to exist, the following definition 1 and lemma 1 are applied.
Definition 1: consider a nonlinear system:
ρk+1=g(ρk,νk) (6);
whereinAndrespectively representing the system state, the external input and the continuous nonlinear function satisfy that g (0,0) is 0. For the system (6), it is assumed that there is oneClass function α (·,. cndot.) and oneClass function β (-) is toAndthe following conditions hold:
‖ρk‖2≤α(‖ρ0‖2,k)+β(‖νk‖∞);
Introduction 1: assuming the presence of the Lyapunov function V (k, ρ)k):One isClass functionThree forClass function σ1(·),σ2(. and σ)3(. to) makeAndthe following two inequalities hold:
σ1(‖ρk‖2)≤V(k,‖ρk‖2)≤σ2(‖ρk‖2);
V(k+1,ρk+1)-V(k,ρk)≤-σ3(‖ρk‖2)+θ(‖νk‖2);
the nonlinear system (6) is input-output stable. α (,) and β (·) in definition 2 can be chosen as:
The execution subject of the positioning driving control method provided by the present disclosure may be a positioning driving control apparatus, for example, the positioning driving control method may be executed by a terminal device or a server or other processing device, wherein the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like. In some possible implementations, the positioning travel control method may be implemented by a processor calling computer readable instructions stored in a memory.
It will be understood by those of skill in the art that in the above method of the present embodiment, the order of writing the steps does not imply a strict order of execution and does not impose any limitations on the implementation, as the order of execution of the steps should be determined by their function and possibly inherent logic.
The positioning travel control device provided by the present disclosure includes: the gain determining unit is used for determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal; the azimuth determining unit is used for obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment; and the positioning running unit is used for determining the running of the controlled object based on the decoding vector corresponding to the azimuth information at the second moment. So as to realize the running of the controlled object when the measurement output of the sensor is abnormal. The problem of when the sensor produces the abnormal value, bring the influence for going is solved.
Fig. 2 is a block diagram of a positioning travel control system according to an embodiment of the present disclosure, as shown in fig. 2, which is applied to an offshore drilling platform, and includes: a drilling platform power system; the drilling platform power system is used for determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the marine drilling platform when the measurement output of the sensor is abnormal; obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment; and the power system of the drilling platform determines the running of the marine drilling platform based on the decoding vector corresponding to the azimuth information at the second moment. So as to realize the running of the controlled object when the measurement output of the sensor is abnormal. The problem of when the sensor produces the abnormal value, bring the influence for going is solved.
In fig. 2, the drilling platform power system comprises: the system comprises an offshore drilling platform 1 as a controlled object, a sensor 2, a state observer 3, an encoder 4, a decoder 5 and a controller 6. The mathematical model corresponding to the closed loop form of the controlled object is xk+1=(E+BKc)xk+Df(xk)+BKcwkWherein the gain K is to be determinedcHas been determined in the above method as a known quantity. The sensor 2 measures azimuth information of each moment in real time, if the measurement output of the sensor is abnormal, the state observer 3 outputs an estimation vector corresponding to the azimuth information, the estimation vector is encoded through the encoder 4 and decoded through the decoder 5 to obtain a decoding vector, the controller 6 obtains a decoding vector corresponding to the azimuth information of the next moment according to the decoding vector corresponding to the azimuth information of the previous moment, and the marine drilling platform 1 determines (controls) the running of the marine drilling platform according to the decoding vector corresponding to the azimuth information of the next moment.
Orientation information x based on first time KkCorresponding decoded vector (decoded vector corresponding to position and velocity at first time)Through the mathematical model corresponding to the closed-loop form of the controlled object, the decoding vector (the decoding vector corresponding to the position and the speed of the second moment) corresponding to the azimuth information of the second moment K +1 at the next moment of the first moment K can be obtainedWherein the decoding errorI.e. the orientation information x at the first moment KkCorresponding decoded vectorOrientation information x from the first time KkThe difference of (a).
In some embodiments, functions or modules included in the apparatus or system provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.
According to the algorithm, a certain offshore drilling platform is taken as a research object, the main parameters are the total length of the platform 74.2m, the width of the platform 18.6m, the width of a vertical line 84.6m, the design draft of 6.35m, the net weight of the platform 4205t, and the power of a main engine is 3530 kW. The platform model parameters are identified by a plurality of sea trials to obtain the following parameters:
the external disturbances are as follows:
saturation function σ (Ne)k) The following conditions are satisfied:
the formula (5) is solved to obtain the gain K of the controllercThe method comprises the following steps:
the controller substituting the gain of the controller when the measurement output of the sensor is abnormal of the marine drilling platform dynamic positioning system realizes the control of the marine drilling platform with the abnormal value of the sensor under the coding and decoding mechanism, and simulation results are obtained in the graphs of fig. 3 to fig. 6.
FIG. 3 illustrates a graph of disturbance components (ambient interference vectors) according to an embodiment of the present disclosure; FIG. 4 shows an actual state vector x of a marine drilling platform dynamic positioning closed loop system according to an embodiment of the present disclosure1,kState estimation vector trajectoryAnd decoding the vectorA trajectory; FIG. 5 shows an actual state vector x of a dynamic positioning closed-loop system of an offshore drilling platform according to an embodiment of the present invention2,kState estimation trajectoryAnd decoding the vectorA trajectory; FIG. 6 shows a decoding error w of the dynamic positioning closed-loop system of the offshore drilling platform according to the embodiment of the invention1,kAnd w2,kA trajectory. As can be seen from fig. 3 to 6, under the encoding and decoding mechanism, for the marine drilling platform having the sensor abnormal value, the controller resisting the sensor abnormal value provided by the present disclosure can effectively control the marine drilling platform.
Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the above-mentioned method. The computer readable storage medium may be a non-volatile computer readable storage medium.
An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to the above-described positioning travel control method. The electronic device may be provided as a terminal, server, or other form of device.
Fig. 7 is a block diagram illustrating an electronic device 800 in accordance with an example embodiment. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like terminal.
Referring to fig. 7, electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 800 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the electronic device 800, relative positioning of components such as a display and keypad of the electronic device 800, a change in position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium, such as the memory 804, is also provided that includes computer program instructions executable by the processor 820 of the electronic device 800 to perform the above-described methods.
Fig. 8 is a block diagram illustrating an electronic device 1900 in accordance with an example embodiment. For example, the electronic device 1900 may be provided as a server. Referring to fig. 8, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the positioning travel control method described above.
The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output (I/O) interface 1958. The electronic device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the electronic device 1900 to perform the above-described methods.
The present disclosure may be a positioning travel control system, a positioning travel control method, and/or a computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (8)
1. A positioning travel control method characterized by comprising:
determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal;
obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment;
determining the running of the controlled object based on the decoding vector corresponding to the azimuth information at the second moment; wherein the orientation information comprises at least a position and/or a velocity;
the method for determining the gain corresponding to the controller according to the decoding vector corresponding to the orientation information of the controlled object when the measurement output of the sensor is abnormal comprises the following steps:
acquiring a mathematical model corresponding to the angle and the position of a controlled object and a measurement output abnormal vector of a sensor in the mathematical model;
determining a state observer according to the mathematical model and the measurement output abnormal vector, and determining an intermediate state vector according to a decoder;
determining a coding vector according to the estimation vector of the state observer and the intermediate state vector; decoding the coding vector to obtain a decoding vector;
determining a controller of the controlled object according to the decoding vector and a state observation model of the mathematical model, and solving the gain of the controller;
wherein, the controlled object is an ocean drilling platform, and the mathematical model corresponding to the controlled object is as follows:
wherein,a state vector consisting of the position and speed information of the offshore drilling platform at the moment K, an initial state x0=s0S of0Satisfies | s0‖2≤∈0Wherein |2Is 2 norm, e0To set a known constant;the measurement output of the sensor at the moment K;a control input signal for the power plant; f (·):the method is characterized in that the method is a nonlinear external disturbance function, and E, D, B and N are real-valued matrixes with proper dimensions;
wherein the method of determining a state observer from the mathematical model and the measurement output anomaly vector comprises:
obtaining the measurement output abnormal vector, and determining a saturation function according to the measurement output abnormal vector;
determining the state observer according to the saturation function and a state observation model of the mathematical model;
wherein the state observer is determined from the saturation function and a state observation model of the mathematical model in the form:
wherein,is in a stateAn estimated vector at time k;is a stateAn estimated vector at time k + 1;an initial vector which is an estimated vector; keFor the observer gain to be designed; σ (·):is a saturation function; f (·):the method is characterized in that the method is a nonlinear external disturbance function, and E, D, B and N are real-valued matrixes with proper dimensions;
wherein the saturation function is defined as:
2. The positioning travel control method according to claim 1,
the method of determining an intermediate state vector from a decoder, comprising: obtaining an intermediate state vector at the moment according to the state observation model of the mathematical model and a decoding vector at the last decoding moment of the decoder;
and/or, the method of determining a coding vector from the estimated vector of the state observer and the intermediate state vector, comprising:
and determining a coding vector according to the difference value of the estimation vector and the intermediate state vector at the same coding moment.
3. The method for controlling positioning driving according to any one of claims 1-2, wherein the method for decoding the encoded vector to obtain a decoded vector comprises:
obtaining a plurality of code words according to the coding vector, and determining a plurality of central points of corresponding hyper-rectangles of the code words;
and respectively decoding the corresponding code words according to the plurality of central points to obtain the decoding vectors.
4. The method according to any one of claims 1 to 2, wherein the method for determining the controller of the controlled object based on the decoded vector and the state observation model of the mathematical model and obtaining the gain of the controller includes:
determining a controller of which the power equipment in the controlled object has gain to be determined according to the decoding vector;
determining a mathematical model corresponding to the controlled object in a closed-loop form by a state observation model controller based on the mathematical model;
and determining a gain matrix according to the mathematical model corresponding to the closed-loop form and the input-state stability index, and solving the gain to be determined according to the gain matrix to obtain the gain of the controller.
5. A positioning travel control apparatus, characterized by comprising:
the gain determining unit is used for determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the controlled object when the measurement output of the sensor is abnormal; the method for determining the gain corresponding to the controller according to the decoding vector corresponding to the orientation information of the controlled object when the measurement output of the sensor is abnormal comprises the following steps:
acquiring a mathematical model corresponding to the angle and the position of a controlled object and a measurement output abnormal vector of a sensor in the mathematical model;
determining a state observer according to the mathematical model and the measurement output abnormal vector, and determining an intermediate state vector according to a decoder;
determining a coding vector according to the estimation vector of the state observer and the intermediate state vector; decoding the coding vector to obtain a decoding vector;
determining a controller of the controlled object according to the decoding vector and a state observation model of the mathematical model, and solving the gain of the controller;
wherein, the controlled object is an ocean drilling platform, and the mathematical model corresponding to the controlled object is as follows:
wherein,a state vector consisting of the position and speed information of the offshore drilling platform at the moment K, an initial state x0=s0S of0Satisfies | s0‖2≤∈0Wherein |2Is 2 norm, e0To set a known constant;the measurement output of the sensor at the moment K;
a control input signal for the power plant; f (·):the method is characterized in that the method is a nonlinear external disturbance function, and E, D, B and N are real-valued matrixes with proper dimensions; wherein the method of determining a state observer from the mathematical model and the measurement output anomaly vector comprises:
obtaining the measurement output abnormal vector, and determining a saturation function according to the measurement output abnormal vector;
determining the state observer according to the saturation function and a state observation model of the mathematical model;
wherein the state observer is determined from the saturation function and a state observation model of the mathematical model in the form:
wherein,is in a stateAn estimated vector at time k;is in a stateAn estimated vector at time k + 1;an initial vector which is an estimated vector; keFor the observer gain to be designed; σ (·):is a saturation function; f (·):the method is characterized in that the method is a nonlinear external disturbance function, and E, D, B and N are real-valued matrixes with proper dimensions;
wherein the saturation function is defined as:
wherein, in setting a maximum value vectorThe iota element of (1) is a sign function; y isnIs the measurement output of the sensor at time n;an estimated vector at time n; n is a real-valued matrix of appropriate dimensions;
the direction determining unit is used for obtaining a decoding vector corresponding to the direction information of the second moment according to the controller and the decoding vector corresponding to the direction information of the first moment;
a positioning driving unit which determines the driving of the controlled object based on the decoding vector corresponding to the azimuth information at the second moment; wherein the orientation information comprises at least a position and/or a velocity.
6. A positioning driving control system is applied to an ocean drilling platform and is characterized by comprising: a drilling platform power system;
the drilling platform power system is used for determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the marine drilling platform when the measurement output of the sensor is abnormal; obtaining a decoding vector corresponding to the azimuth information at the second moment according to the controller and the decoding vector corresponding to the azimuth information at the first moment; the method for determining the gain corresponding to the controller according to the decoding vector corresponding to the azimuth information of the offshore drilling platform when the measurement output of the sensor is abnormal comprises the following steps:
acquiring a mathematical model corresponding to the angle and the position of a controlled object and a measurement output abnormal vector of a sensor in the mathematical model;
determining a state observer according to the mathematical model and the measurement output abnormal vector, and determining an intermediate state vector according to a decoder;
determining a coding vector according to the estimation vector of the state observer and the intermediate state vector; decoding the coding vector to obtain a decoding vector;
determining a controller of the controlled object according to the decoding vector and a state observation model of the mathematical model, and solving the gain of the controller;
wherein, the controlled object is an ocean drilling platform, and the mathematical model corresponding to the controlled object is as follows:
wherein,a state vector consisting of the position and speed information of the offshore drilling platform at the moment K, an initial state x0=s0S of0Satisfies | s0‖2≤∈0Wherein |2Is 2 norm, e0To set a known constant;the measurement output of the sensor at the moment K;a control input signal for the power plant; f (·):the method is characterized in that the method is a nonlinear external disturbance function, and E, D, B and N are real-valued matrixes with proper dimensions;
wherein the method of determining a state observer from the mathematical model and the measurement output anomaly vector comprises:
obtaining the measurement output abnormal vector, and determining a saturation function according to the measurement output abnormal vector;
determining the state observer according to the saturation function and a state observation model of the mathematical model;
wherein the state observer is determined from the saturation function and a state observation model of the mathematical model in the form:
wherein,is in a stateAn estimated vector at time k;is in a stateEstimation direction at time k +1An amount;an initial vector which is an estimated vector; keFor the observer gain to be designed; σ (·):is a saturation function; f (·):the method is characterized in that the method is a nonlinear external disturbance function, and E, D, B and N are real-valued matrixes with proper dimensions;
wherein the saturation function is defined as:
wherein, in setting a maximum value vectorThe iota element of (1) is a sign function; y isnIs the measurement output of the sensor at time n;an estimated vector at time n; n is a real-valued matrix of appropriate dimensions; and the power system of the drilling platform determines the running of the marine drilling platform based on the decoding vector corresponding to the azimuth information at the second moment.
7. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to invoke the memory-stored instructions to perform the positioning travel control method of any of claims 1 to 4.
8. A computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the positioning travel control method of any one of claims 1 to 4.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202011115466.8A CN112255917B (en) | 2020-10-19 | 2020-10-19 | Positioning driving control method, positioning driving control device, positioning driving control system, electronic equipment and storage medium |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202011115466.8A CN112255917B (en) | 2020-10-19 | 2020-10-19 | Positioning driving control method, positioning driving control device, positioning driving control system, electronic equipment and storage medium |
Publications (2)
Publication Number | Publication Date |
---|---|
CN112255917A CN112255917A (en) | 2021-01-22 |
CN112255917B true CN112255917B (en) | 2022-06-07 |
Family
ID=74244042
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202011115466.8A Active CN112255917B (en) | 2020-10-19 | 2020-10-19 | Positioning driving control method, positioning driving control device, positioning driving control system, electronic equipment and storage medium |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN112255917B (en) |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102508431A (en) * | 2011-11-04 | 2012-06-20 | 江苏科技大学 | Thrust distribution method for power positioning system of offshore drilling platform |
US8210283B1 (en) * | 2011-12-22 | 2012-07-03 | Hunt Energy Enterprises, L.L.C. | System and method for surface steerable drilling |
CN103499921A (en) * | 2013-09-11 | 2014-01-08 | 西安交通大学 | Fault diagnosis method for variable structure fuzzy system sensor and application thereof in flight control system |
CN104675380A (en) * | 2015-01-28 | 2015-06-03 | 扬州大学 | Online oil-drilling drill string monitoring system and fault diagnosis method |
CN104714520A (en) * | 2014-12-29 | 2015-06-17 | 东华大学 | Fault estimation method under sensor network environment and based on Green space theory |
CL2015000009A1 (en) * | 2012-07-06 | 2015-08-21 | Tech Resources Pty Ltd | Method to drill to a position relative to a geological limit in a geological formation, where the method includes detecting drilling parameters while a drilling is being drilled in the geological formation, using said parameters to locate the position of a drill, generating a map of geological model, use the detected parameters and use a auger controller; system; auger. |
CN105978725A (en) * | 2016-05-13 | 2016-09-28 | 芦慧 | Non-fragile distributed fault estimation method based on sensor network |
CN106005264A (en) * | 2016-05-12 | 2016-10-12 | 哈尔滨工程大学 | Automatic monitoring and control technology-based drilling platform propeller auxiliary anchoring positioning system |
CN111323007A (en) * | 2020-02-12 | 2020-06-23 | 北京市商汤科技开发有限公司 | Positioning method and device, electronic equipment and storage medium |
-
2020
- 2020-10-19 CN CN202011115466.8A patent/CN112255917B/en active Active
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102508431A (en) * | 2011-11-04 | 2012-06-20 | 江苏科技大学 | Thrust distribution method for power positioning system of offshore drilling platform |
US8210283B1 (en) * | 2011-12-22 | 2012-07-03 | Hunt Energy Enterprises, L.L.C. | System and method for surface steerable drilling |
CL2015000009A1 (en) * | 2012-07-06 | 2015-08-21 | Tech Resources Pty Ltd | Method to drill to a position relative to a geological limit in a geological formation, where the method includes detecting drilling parameters while a drilling is being drilled in the geological formation, using said parameters to locate the position of a drill, generating a map of geological model, use the detected parameters and use a auger controller; system; auger. |
CN103499921A (en) * | 2013-09-11 | 2014-01-08 | 西安交通大学 | Fault diagnosis method for variable structure fuzzy system sensor and application thereof in flight control system |
CN104714520A (en) * | 2014-12-29 | 2015-06-17 | 东华大学 | Fault estimation method under sensor network environment and based on Green space theory |
CN104675380A (en) * | 2015-01-28 | 2015-06-03 | 扬州大学 | Online oil-drilling drill string monitoring system and fault diagnosis method |
CN106005264A (en) * | 2016-05-12 | 2016-10-12 | 哈尔滨工程大学 | Automatic monitoring and control technology-based drilling platform propeller auxiliary anchoring positioning system |
CN105978725A (en) * | 2016-05-13 | 2016-09-28 | 芦慧 | Non-fragile distributed fault estimation method based on sensor network |
CN111323007A (en) * | 2020-02-12 | 2020-06-23 | 北京市商汤科技开发有限公司 | Positioning method and device, electronic equipment and storage medium |
Non-Patent Citations (1)
Title |
---|
彭勇胜.面向轨迹数据的行为挖掘关键技术研究.《万方学位论文》.2020,第1-81页. * |
Also Published As
Publication number | Publication date |
---|---|
CN112255917A (en) | 2021-01-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110210535B (en) | Neural network training method and device and image processing method and device | |
CN110909815B (en) | Neural network training method, neural network training device, neural network processing device, neural network training device, image processing device and electronic equipment | |
CN110633755A (en) | Network training method, image processing method and device and electronic equipment | |
US12045578B2 (en) | Method for determining text similarity, storage medium and electronic device | |
CN109919300B (en) | Neural network training method and device and image processing method and device | |
US20210312289A1 (en) | Data processing method and apparatus, and storage medium | |
CN111462238B (en) | Attitude estimation optimization method and device and storage medium | |
US11314965B2 (en) | Method and apparatus for positioning face feature points | |
CN111242303B (en) | Network training method and device, and image processing method and device | |
CN110706339B (en) | Three-dimensional face reconstruction method and device, electronic equipment and storage medium | |
WO2022247103A1 (en) | Image processing method and apparatus, electronic device, and computer-readable storage medium | |
CN111223040A (en) | Network training method and device and image generation method and device | |
CN113762623B (en) | Landslide direction and trend identification and prediction method and device and electronic equipment | |
CN112668707B (en) | Operation method, device and related product | |
CN115908640A (en) | Method and device for generating image, readable medium and electronic equipment | |
CN113139484A (en) | Crowd positioning method and device, electronic equipment and storage medium | |
CN110188865A (en) | Information processing method and device, electronic equipment and storage medium | |
EP4287181A1 (en) | Method and apparatus for training neural network, and method and apparatus for audio processing | |
CN111985635A (en) | Method, device and medium for accelerating neural network inference processing | |
CN112269904A (en) | Data processing method and device | |
CN112255917B (en) | Positioning driving control method, positioning driving control device, positioning driving control system, electronic equipment and storage medium | |
CN113065361B (en) | Method and device for determining user intimacy, electronic equipment and storage medium | |
CN108024005B (en) | Information processing method and device, intelligent terminal, server and system | |
CN113239389B (en) | Data processing method and device and data processing device | |
CN111860552A (en) | Model training method and device based on nuclear self-encoder and storage medium |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |