Cheong et al., 2013 - Google Patents
Adaptive fuzzy dynamic surface sliding mode position control for a robot manipulator with friction and deadzoneCheong et al., 2013
View PDF- Document ID
- 3460857916926669351
- Author
- Cheong J
- Han S
- Lee J
- Publication year
- Publication venue
- Mathematical Problems in Engineering
External Links
Snippet
Precise tracking positioning performance in the presence of both the deadzone and friction of a robot manipulator actuator is difficult to achieve by traditional control methodology without proper nonlinear compensation schemes. In this paper, we present a dynamic …
- 230000003044 adaptive 0 title abstract description 23
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
-
- 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
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
-
- 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
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
-
- 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
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
-
- 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
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Yen et al. | Recurrent fuzzy wavelet neural networks based on robust adaptive sliding mode control for industrial robot manipulators | |
Ahmed et al. | Robust adaptive fractional‐order terminal sliding mode control for lower‐limb exoskeleton | |
Han et al. | Improved prescribed performance constraint control for a strict feedback non‐linear dynamic system | |
He et al. | Adaptive neural network control of a robotic manipulator with unknown backlash‐like hysteresis | |
Nguyen et al. | Adaptive chattering free neural network based sliding mode control for trajectory tracking of redundant parallel manipulators | |
Sheikholeslam et al. | Design of adaptive fuzzy wavelet neural sliding mode controller for uncertain nonlinear systems | |
Qi et al. | Stable indirect adaptive control based on discrete-time T–S fuzzy model | |
Xiong et al. | Adaptive gains to super‐twisting technique for sliding mode design | |
Razmjooei et al. | Non-linear finite-time tracking control of uncertain robotic manipulators using time-varying disturbance observer-based sliding mode method | |
Wu et al. | Adaptive tracking control of robot manipulators with input saturation and time‐varying output constraints | |
Hsu | Adaptive neural complementary sliding-mode control via functional-linked wavelet neural network | |
Dachang et al. | Adaptive backstepping sliding mode control of trajectory tracking for robotic manipulators | |
Chu et al. | Backstepping control for flexible joint with friction using wavelet neural networks and L2‐gain approach | |
Cheong et al. | Adaptive fuzzy dynamic surface sliding mode position control for a robot manipulator with friction and deadzone | |
Mendoza et al. | Output‐feedback proportional–integral–derivative‐type control with simple tuning for the global regulation of robot manipulators with input constraints | |
Nguyen | Non-Negative Adaptive Mechanism-Based Sliding Mode Control for Parallel Manipulators with Uncertainties. | |
Yang et al. | Synchronization analysis for nonlinear bilateral teleoperator with interval time‐varying delay | |
Amer et al. | Quasi sliding mode‐based single input fuzzy self‐tuning decoupled fuzzy PI control for robot manipulators with uncertainty | |
Ulrich et al. | On the simple adaptive control of flexible-joint space manipulators with uncertainties | |
Han et al. | Barrier Lyapunov Function‐Based Sliding Mode Control for Guaranteed Tracking Performance of Robot Manipulator | |
Fateh et al. | Discrete adaptive fuzzy control for asymptotic tracking of robotic manipulators | |
Liang et al. | Task space trajectory tracking control of robot manipulators with uncertain kinematics and dynamics | |
Zhang et al. | Adaptive Safety-Critical Control With Uncertainty Estimation for Human–Robot Collaboration | |
Munoz Vazquez et al. | Discrete‐time fractional fuzzy control of electrically driven mechanical systems | |
Maldonado‐Fregoso et al. | A generalized adaptive stiffness control scheme for robot manipulators with bounded inputs |