Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation

In this paper, adaptive impedance control is developed for an n-link robotic manipulator with input saturation by employing neural networks. Both uncertainties and input saturation are considered in the tracking control design. In order to approximate the system uncertainties, we introduce a radial basis function neural network controller, and the input saturation is handled by designing an auxiliary system. By using Lyapunov's method, we design adaptive neural impedance controllers. Both state and output feedbacks are constructed. To verify the proposed control, extensive simulations are conducted.

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

[2]  Shuzhi Sam Ge,et al.  Robust attitude control of helicopters with actuator dynamics using neural networks , 2010 .

[3]  Rieko Osu,et al.  The central nervous system stabilizes unstable dynamics by learning optimal impedance , 2001, Nature.

[4]  Tong Heng Lee,et al.  Iterative learning control design based on composite energy function with input saturation , 2004, Autom..

[5]  Shuzhi Sam Ge,et al.  Vibration Control of a Flexible Beam With Output Constraint , 2015, IEEE Transactions on Industrial Electronics.

[6]  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.

[7]  L. Fu,et al.  Robust output tracking for nonlinear systems with weakly non-minimum phase , 1993 .

[8]  Shuzhi Sam Ge,et al.  Vibration Control of a Flexible String With Both Boundary Input and Output Constraints , 2015, IEEE Transactions on Control Systems Technology.

[9]  Shaocheng Tong,et al.  Adaptive Fuzzy Output Feedback Tracking Backstepping Control of Strict-Feedback Nonlinear Systems With Unknown Dead Zones , 2012, IEEE Transactions on Fuzzy Systems.

[10]  Zhong-Ping Jiang,et al.  Adaptive stabilization and tracking control of a nonholonomic mobile robot with input saturation and disturbance , 2013, Syst. Control. Lett..

[11]  Xin Chen,et al.  Adaptive Neural Control for a Class of Nonlinear Time-Varying Delay Systems With Unknown Hysteresis , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[12]  Shuzhi Sam Ge,et al.  Learning impedance control for physical robot–environment interaction , 2012, Int. J. Control.

[13]  Shaocheng Tong,et al.  Adaptive Neural Output Feedback Controller Design With Reduced-Order Observer for a Class of Uncertain Nonlinear SISO Systems , 2011, IEEE Transactions on Neural Networks.

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

[15]  V. Santibáñez,et al.  A practical PID regulator with bounded torques for robot manipulators , 2010 .

[16]  Cong Wang,et al.  Dynamic Learning From Adaptive Neural Network Control of a Class of Nonaffine Nonlinear Systems , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[17]  Shuzhi Sam Ge,et al.  Robust adaptive control of a thruster assisted position mooring system , 2014, Autom..

[18]  Rongxin Cui,et al.  Adaptive backstepping control of wheeled inverted pendulums models , 2015 .

[19]  Sukhan Lee,et al.  Energy-Efficient SVM Learning Control System for Biped Walking Robots , 2013, IEEE Transactions on Neural Networks and Learning Systems.

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

[21]  Shuzhi Sam Ge,et al.  Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints , 2011, Autom..

[22]  Zhongke Shi,et al.  Composite Neural Dynamic Surface Control of a Class of Uncertain Nonlinear Systems in Strict-Feedback Form , 2014, IEEE Transactions on Cybernetics.

[23]  Shuzhi Sam Ge,et al.  Adaptive Control of a Flexible Crane System With the Boundary Output Constraint , 2014, IEEE Transactions on Industrial Electronics.

[24]  Pierluigi Ritrovato,et al.  S-WOLF: Semantic Workplace Learning Framework , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[25]  Guo-Xing Wen,et al.  Fuzzy Neural Network-Based Adaptive Control for a Class of Uncertain Nonlinear Stochastic Systems , 2014, IEEE Transactions on Cybernetics.

[26]  Shuzhi Sam Ge,et al.  Top Tension Control of a Flexible Marine Riser by Using Integral-Barrier Lyapunov Function , 2015, IEEE/ASME Transactions on Mechatronics.

[27]  Danwei Wang,et al.  Learning impedance control for robotic manipulators , 1998, IEEE Trans. Robotics Autom..

[28]  Bin Jiang,et al.  Robust Adaptive Tracking Control of the Underwater Robot with Input Nonlinearity Using Neural Networks , 2010 .

[29]  Carlos Canudas de Wit,et al.  Theory of Robot Control , 1996 .

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

[31]  Yongduan Song,et al.  Cooperative Tracking Control of Nonlinear Multiagent Systems Using Self-Structuring Neural Networks , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[32]  Shaocheng Tong,et al.  Adaptive Neural Output Feedback Tracking Control for a Class of Uncertain Discrete-Time Nonlinear Systems , 2011, IEEE Transactions on Neural Networks.

[33]  S. S. Ge,et al.  Synchronised tracking control of multi-agent system with high order dynamics , 2012 .

[34]  Jun Wang,et al.  Global Exponential Synchronization of Two Memristor-Based Recurrent Neural Networks With Time Delays via Static or Dynamic Coupling , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[35]  Jing Zhou,et al.  Robust Adaptive Control of Uncertain Nonlinear Systems in the Presence of Input Saturation and External Disturbance , 2011, IEEE Transactions on Automatic Control.

[36]  Wei He,et al.  Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints , 2016, IEEE Transactions on Cybernetics.

[37]  Shaocheng Tong,et al.  Adaptive NN Controller Design for a Class of Nonlinear MIMO Discrete-Time Systems , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[38]  Neville Hogan,et al.  On the stability of manipulators performing contact tasks , 1988, IEEE J. Robotics Autom..

[39]  Bin Xu,et al.  Robust adaptive neural control of flexible hypersonic flight vehicle with dead-zone input nonlinearity , 2015 .

[40]  Deliang Liang,et al.  Nonlinear state-observer control for projective synchronization of a fractional-order hyperchaotic system , 2012 .

[41]  Shuzhi Sam Ge,et al.  Boundary control of a flexible marine riser with vessel dynamics , 2010, Proceedings of the 2010 American Control Conference.

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

[43]  Rastko R. Selmic,et al.  Neural network control of a class of nonlinear systems with actuator saturation , 2004 .

[44]  Shuzhi Sam Ge,et al.  Contact-Force Distribution Optimization and Control for Quadruped Robots Using Both Gradient and Adaptive Neural Networks , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[45]  Thomas B. Sheridan,et al.  Robust compliant motion for manipulators, part I: The fundamental concepts of compliant motion , 1986, IEEE J. Robotics Autom..

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

[47]  S. C. Tong,et al.  Adaptive Neural Network Decentralized Backstepping Output-Feedback Control for Nonlinear Large-Scale Systems With Time Delays , 2011, IEEE Transactions on Neural Networks.

[48]  C. L. Philip Chen,et al.  Adaptive Neural Control for Dual-Arm Coordination of Humanoid Robot With Unknown Nonlinearities in Output Mechanism , 2015, IEEE Transactions on Cybernetics.

[49]  Cong Wang,et al.  Identification and Learning Control of Ocean Surface Ship Using Neural Networks , 2012, IEEE Transactions on Industrial Informatics.

[50]  Frank L. Lewis,et al.  Reinforcement adaptive learning neural-net-based friction compensation control for high speed and precision , 2000, IEEE Trans. Control. Syst. Technol..

[51]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part II—Implementation , 1985 .

[52]  Chun-Yi Su,et al.  Neural-Adaptive Control of Single-Master–Multiple-Slaves Teleoperation for Coordinated Multiple Mobile Manipulators With Time-Varying Communication Delays and Input Uncertainties , 2013, IEEE Transactions on Neural Networks and Learning Systems.

[53]  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).

[54]  Jing Li,et al.  Trajectory Planning and Optimized Adaptive Control for a Class of Wheeled Inverted Pendulum Vehicle Models , 2013, IEEE Transactions on Cybernetics.

[55]  Shuzhi Sam Ge,et al.  Adaptive Neural Network Control of Robotic Manipulators , 1999, World Scientific Series in Robotics and Intelligent Systems.

[56]  Homayoun Seraji,et al.  Direct adaptive impedance control of robot manipulators , 1993, J. Field Robotics.

[57]  Max Q.-H. Meng,et al.  Impedance control with adaptation for robotic manipulations , 1991, IEEE Trans. Robotics Autom..