Fuzzy Logic Control of an Uncertain Manipulator With Full-State Constraints and Disturbance Observer

In this paper, a fuzzy logic control strategy is proposed for solving trajectory tracking control issues of an uncertain manipulator. Fuzzy logic is utilized to compensate for nonlinear uncertainties in manipulator dynamics and full-state constraints are involved in full-state feedback controller design for ensuring motion constraints during movement processes. Disturbance observer (DO) is designed to counteract the effects of unknown nonlinear disturbances caused by friction force or other various forms of disturbance. Combining with Lyapunov theory and back-stepping method, the proposed method can guarantee error signals in closed-loop system semi-globally uniformly bounded (SGUB). In view of safe operation, tangent barrier Lyapunov functions (tBLFs) are chosen to maintain joint angle and velocity in a predefined constrained region in tracking processes. Finally, simulation results are carried out to show the effectiveness of our proposed control strategy.

[1]  Wei He,et al.  Vibration Control of a Flexible Robotic Manipulator in the Presence of Input Deadzone , 2017, IEEE Transactions on Industrial Informatics.

[2]  Changyin Sun,et al.  Iterative Learning Control for a Flapping Wing Micro Aerial Vehicle Under Distributed Disturbances , 2019, IEEE Transactions on Cybernetics.

[3]  Xin Chen,et al.  Adaptive Fuzzy Output-Feedback Controller Design for Nonlinear Systems via Backstepping and Small-Gain Approach , 2014, IEEE Transactions on Cybernetics.

[4]  Shuzhi Sam Ge,et al.  Adaptive neural control of uncertain MIMO nonlinear systems , 2004, IEEE Transactions on Neural Networks.

[5]  Shaocheng Tong,et al.  Adaptive NN Tracking Control of Uncertain Nonlinear Discrete-Time Systems With Nonaffine Dead-Zone Input , 2015, IEEE Transactions on Cybernetics.

[6]  Tianyou Chai,et al.  Nonlinear Disturbance Observer-Based Control Design for a Robotic Exoskeleton Incorporating Fuzzy Approximation , 2015, IEEE Transactions on Industrial Electronics.

[7]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[8]  Shuzhi Sam Ge,et al.  Adaptive neural network control of robot manipulators in task space , 1997, IEEE Trans. Ind. Electron..

[9]  Shaocheng Tong,et al.  Fuzzy Adaptive Control With State Observer for a Class of Nonlinear Discrete-Time Systems With Input Constraint , 2016, IEEE Transactions on Fuzzy Systems.

[10]  Shuzhi Sam Ge,et al.  Neural Network Control of a Rehabilitation Robot by State and Output Feedback , 2015, J. Intell. Robotic Syst..

[11]  Shaocheng Tong,et al.  Neural Network Controller Design for an Uncertain Robot With Time-Varying Output Constraint , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[12]  Alin Albu-Schäffer,et al.  Human-Like Adaptation of Force and Impedance in Stable and Unstable Interactions , 2011, IEEE Transactions on Robotics.

[13]  Changyin Sun,et al.  Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[14]  Guo-Xing Wen,et al.  Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[15]  Shaocheng Tong,et al.  Adaptive Controller Design-Based ABLF for a Class of Nonlinear Time-Varying State Constraint Systems , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[16]  Kaixiang Peng,et al.  Adaptive Neural Control for Robotic Manipulators With Output Constraints and Uncertainties , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[17]  Francis Eng Hock Tay,et al.  Barrier Lyapunov Functions for the control of output-constrained nonlinear systems , 2009, Autom..

[18]  Shaocheng Tong,et al.  A Combined Backstepping and Stochastic Small-Gain Approach to Robust Adaptive Fuzzy Output Feedback Control , 2013, IEEE Transactions on Fuzzy Systems.

[19]  C. L. Philip Chen,et al.  Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[20]  Zongquan Deng,et al.  Adaptive Neural Network-Based Finite-Time Online Optimal Tracking Control of the Nonlinear System With Dead Zone , 2019, IEEE Transactions on Cybernetics.

[21]  Wei He,et al.  PDE Model-Based Boundary Control Design for a Flexible Robotic Manipulator With Input Backlash , 2019, IEEE Transactions on Control Systems Technology.

[22]  Shuzhi Sam Ge,et al.  Cooperative control of a nonuniform gantry crane with constrained tension , 2016, Autom..

[23]  Changyin Sun,et al.  Neural Network Control of a Flexible Robotic Manipulator Using the Lumped Spring-Mass Model , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[24]  Xuefang Li,et al.  Adaptive Boundary Iterative Learning Control for an Euler–Bernoulli Beam System With Input Constraint , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[25]  Shuzhi Sam Ge,et al.  Adaptive output feedback NN control of a class of discrete-time MIMO nonlinear systems with unknown control directions , 2009, 2009 7th Asian Control Conference.

[26]  Chun-Yi Su,et al.  Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision , 2017, IEEE Transactions on Industrial Informatics.

[27]  Hongyi Li,et al.  Adaptive finite-time tracking control of full state constrained nonlinear systems with dead-zone , 2019, Autom..

[28]  Shuzhi Sam Ge,et al.  Adaptive Control of Robotic Manipulators With Unified Motion Constraints , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[29]  Jie Chen,et al.  Optimal Linear Quadratic Regulator of Switched Systems , 2019, IEEE Transactions on Automatic Control.

[30]  Wei He,et al.  Cooperative Adaptive Event-Triggered Control for Multiagent Systems With Actuator Failures , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[31]  Lu Bai,et al.  Adaptive Neural Control of Uncertain Nonstrict-Feedback Stochastic Nonlinear Systems with Output Constraint and Unknown Dead Zone , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[32]  Shuzhi Sam Ge,et al.  Unified iterative learning control for flexible structures with input constraints , 2018, Autom..

[33]  Keng Peng Tee,et al.  Control of nonlinear systems with time-varying output constraints , 2009, 2009 IEEE International Conference on Control and Automation.

[34]  Wei He,et al.  Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[35]  Shaocheng Tong,et al.  Adaptive Fuzzy Control via Observer Design for Uncertain Nonlinear Systems With Unmodeled Dynamics , 2013, IEEE Transactions on Fuzzy Systems.

[36]  Jun Fu,et al.  Direct adaptive controller for uncertain MIMO dynamic systems with time-varying delay and dead-zone inputs , 2015, Autom..

[37]  Seul Jung,et al.  Neural network impedance force control of robot manipulator , 1998, IEEE Trans. Ind. Electron..

[38]  Shuzhi Sam Ge,et al.  Adaptive Robust Motion/Force Control of Holonomic-Constrained Nonholonomic Mobile Manipulators , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[39]  Peter J. Gawthrop,et al.  A nonlinear disturbance observer for robotic manipulators , 2000, IEEE Trans. Ind. Electron..

[40]  Shuzhi Sam Ge,et al.  Impedance Learning for Robots Interacting With Unknown Environments , 2014, IEEE Transactions on Control Systems Technology.

[41]  Changyin Sun,et al.  Adaptive Neural Network Control of a Flapping Wing Micro Aerial Vehicle With Disturbance Observer , 2017, IEEE Transactions on Cybernetics.

[42]  Changyin Sun,et al.  An Analysis of a Neural Dynamical Approach to Solving Optimization Problems , 2009, IEEE Transactions on Automatic Control.

[43]  Darren M. Dawson,et al.  Contril of rigid-link, flexible-joint robots: a survey of backstepping approaches , 1995, J. Field Robotics.

[44]  Shuzhi Sam Ge,et al.  Adaptive Neural Output Feedback Control of Uncertain Nonlinear Systems With Unknown Hysteresis Using Disturbance Observer , 2015, IEEE Transactions on Industrial Electronics.

[45]  Guanglin Li,et al.  Fuzzy Approximation-Based Adaptive Backstepping Control of an Exoskeleton for Human Upper Limbs , 2015, IEEE Transactions on Fuzzy Systems.

[46]  Bin Xu,et al.  Disturbance Observer-Based Dynamic Surface Control of Transport Aircraft With Continuous Heavy Cargo Airdrop , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[47]  Shaohua Luo,et al.  Chaos RBF dynamics surface control of brushless DC motor with time delay based on tangent barrier Lyapunov function , 2014 .

[48]  Ian Howard,et al.  Neural network adaptive control design for robot manipulators under velocity constraints , 2017, J. Frankl. Inst..

[49]  Shuzhi Sam Ge,et al.  Human–Robot Collaboration Based on Motion Intention Estimation , 2014, IEEE/ASME Transactions on Mechatronics.