Adaptive neural control for an uncertain robotic manipulator with joint space constraints

ABSTRACT In this paper, adaptive neural tracking control is proposed for a robotic manipulator with uncertainties in both manipulator dynamics and joint actuator dynamics. The manipulator joints are subject to inequality constraints, i.e., the joint angles are required to remain in some compact sets. Integral barrier Lyapunov functionals (iBLFs) are employed to address the joint space constraints directly without performing an additional mapping to the error space. Neural networks (NNs) are utilised to compensate for the unknown robot dynamics and external force. Adapting parameters are developed to estimate the unknown bounds on NN approximations. By the Lyapunov synthesis, the proposed control can guarantee the semi-global uniform ultimate boundedness of the closed-loop system, and the practical tracking of joint reference trajectory is achieved without the violation of predefined joint space constraints. Simulation results are given to validate the effectiveness of the proposed control scheme.

[1]  Youxian Sun,et al.  NN-based asymptotic tracking control for a class of strict-feedback uncertain nonlinear systems with output constraints , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[2]  Jun Huang,et al.  An adaptive neural network switching control approach of robotic manipulators for trajectory tracking , 2014, Int. J. Comput. Math..

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

[4]  TongShaocheng,et al.  Barrier Lyapunov Functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints , 2016 .

[5]  Marios M. Polycarpou,et al.  A Robust Adaptive Nonlinear Control Design , 1993, 1993 American Control Conference.

[6]  Hao-Bo Kang,et al.  Adaptive control of 5 DOF upper-limb exoskeleton robot with improved safety. , 2013, ISA transactions.

[7]  Shaocheng Tong,et al.  Barrier Lyapunov Functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints , 2016, Autom..

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

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

[10]  Shaocheng Tong,et al.  A Unified Approach to Adaptive Neural Control for Nonlinear Discrete-Time Systems With Nonlinear Dead-Zone Input , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[11]  Tzyh Jong Tarn,et al.  Effect of motor dynamics on nonlinear feedback robot arm control , 1991, IEEE Trans. Robotics Autom..

[12]  F. J. Narcowich,et al.  Persistency of Excitation in Identification Using Radial Basis Function Approximants , 1995 .

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

[14]  Chien Chern Cheah,et al.  Adaptive Jacobian tracking control of robots with uncertainties in kinematic, dynamic and actuator models , 2006, IEEE Transactions on Automatic Control.

[15]  Frank L. Lewis,et al.  Robust backstepping control of nonlinear systems using neural networks , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[16]  Keng Peng Tee,et al.  Adaptive NN control for uncertain pure-feedback nonlinear systems with state constraints subject to unknown disturbances , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[17]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Autonomous Robot Vehicles.

[18]  Shuzhi Sam Ge,et al.  Position/force control of uncertain constrained flexible joint robots , 2006 .

[19]  Alan S. I. Zinober,et al.  Nonlinear and Adaptive Control , 2003 .

[20]  Kok Kiong Tan,et al.  Further results on adaptive control for a class of nonlinear systems using neural networks , 2003, IEEE Trans. Neural Networks.

[21]  Haizhou Li,et al.  Adaptive admittance control of a robot manipulator under task space constraint , 2010, 2010 IEEE International Conference on Robotics and Automation.

[22]  Michael Athans,et al.  Nonlinear and Adaptive Control , 1989 .

[23]  Andrea Maria Zanchettin,et al.  Safety Control of Industrial Robots Based on a Distributed Distance Sensor , 2014, IEEE Transactions on Control Systems Technology.

[24]  Zhongliang Tang.  Adaptive Neural Network Control of Uncertain State-Constrained Nonlinear Systems , 2014 .

[25]  Shaocheng Tong,et al.  Adaptive output feedback control for a class of nonlinear systems with full-state constraints , 2014, Int. J. Control.

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

[27]  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).

[28]  Keng Peng Tee,et al.  Control of state-constrained nonlinear systems using Integral Barrier Lyapunov Functionals , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[29]  Haizhou Li,et al.  Adaptive control for robot manipulators under ellipsoidal task space constraints , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[30]  Hong Chen,et al.  Approximation capability to functions of several variables, nonlinear functionals, and operators by radial basis function neural networks , 1993, IEEE Trans. Neural Networks.

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

[32]  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.

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

[34]  Andrea Maria Zanchettin,et al.  Safety Assessment and Control of Robotic Manipulators Using Danger Field , 2013, IEEE Transactions on Robotics.

[35]  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.

[36]  Shuzhi Sam Ge,et al.  Adaptive Predictive Control Using Neural Network for a Class of Pure-Feedback Systems in Discrete Time , 2008, IEEE Transactions on Neural Networks.

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

[38]  Keng Peng Tee,et al.  Tangent Barrier Lyapunov Functions for the Control of Output-Constrained Nonlinear Systems , 2013, ICONS.

[39]  Keng Peng Tee,et al.  Control of nonlinear systems with partial state constraints using a barrier Lyapunov function , 2011, Int. J. Control.

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

[41]  Robert M. Sanner,et al.  Gaussian Networks for Direct Adaptive Control , 1991, 1991 American Control Conference.

[42]  Frank L. Lewis,et al.  Neural Network Control Of Robot Manipulators And Non-Linear Systems , 1998 .

[43]  Jun Huang,et al.  Trajectory Switching Control of Robotic Manipulators Based on RBF Neural Networks , 2013, Circuits, Systems, and Signal Processing.

[44]  Yunong Zhang,et al.  Variable Joint-Velocity Limits of Redundant Robot Manipulators Handled by Quadratic Programming , 2013, IEEE/ASME Transactions on Mechatronics.

[45]  Jun Huang,et al.  Design of Robust Adaptive Neural Switching Controller for Robotic Manipulators with Uncertainty and Disturbances , 2014, Journal of Intelligent & Robotic Systems.