Neural Network Sliding-Mode-PID Controller Design for Electrically Driven Robot Manipulators

This paper addresses a neural-network-based chattering free sliding mode control (SMC) for robot manipulators including structured and unstructured uncertainties in both manipulator and actuator dynamics by incorporating a PID outer loop. The main idea is that the robustness property of SMC and good response characteristics of PID are combined to achieve more acceptable performance. Uncertainties in the robot dynamics and actuator model are compensated by a two-layer neural network. External disturbance and approximation error are counteracted by robust signal with adaptive gain. The stability of closed-loop system is guaranteed by developed control scheme. Finally, the proposed methodology is applied to a two-link elbow robot as a case of study. The simulation results show the effectiveness of the method and its robustness to uncertainties and disturbances.

[1]  A. Mohammad,et al.  Sliding mode PID-controller design for robot manipulators by using fuzzy tuning approach , 2008, 2008 27th Chinese Control Conference.

[2]  Ilyas Eker,et al.  Sliding mode control with PID sliding surface and experimental application to an electromechanical plant. , 2006, ISA transactions.

[3]  Peter Kwong-Shun Tam,et al.  A fuzzy sliding controller for nonlinear systems , 2001, IEEE Trans. Ind. Electron..

[4]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[5]  Peng-Yung Woo,et al.  Fuzzy supervisory sliding-mode and neural-network control for robotic manipulators , 2006, IEEE Transactions on Industrial Electronics.

[6]  Rong-Jong Wai,et al.  Robust Neural-Fuzzy-Network Control for Robot Manipulator Including Actuator Dynamics , 2006, IEEE Transactions on Industrial Electronics.

[7]  Kok Kiong Tan,et al.  Adaptive neural network algorithm for control design of rigid-link electrically driven robots , 2008, Neurocomputing.

[8]  Okyay Kaynak,et al.  The fusion of computationally intelligent methodologies and sliding-mode control-a survey , 2001, IEEE Trans. Ind. Electron..

[9]  Rong-Jong Wai,et al.  Tracking control based on neural network strategy for robot manipulator , 2003, Neurocomputing.

[10]  Martin T. Hagan,et al.  Neural network design , 1995 .

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

[12]  Zhongcheng Yu,et al.  THE SLIDING MODE VARIABLE STRUCTURE CONTROL BASED ON COMPOSITE REACHING LAW OF ACTIVE MAGNETIC BEARING , 2008 .

[13]  Yeong-Chan Chang,et al.  An intelligent robust tracking control for electrically-driven robot systems , 2008, Int. J. Syst. Sci..

[14]  Weibing Gao,et al.  Variable structure control of nonlinear systems: a new approach , 1993, IEEE Trans. Ind. Electron..

[15]  Vadim I. Utkin,et al.  Sliding Modes and their Application in Variable Structure Systems , 1978 .

[16]  Y.-C. Chang,et al.  Robust tracking control for a class of uncertain electrically driven robots , 2009 .

[17]  Frank L. Lewis,et al.  Multilayer neural-net robot controller with guaranteed tracking performance , 1996, IEEE Trans. Neural Networks.

[18]  Antonella Ferrara,et al.  Design and experimental validation of a second-order sliding-mode motion controller for robot manipulators , 2009, Int. J. Control.

[19]  Okyay Kaynak,et al.  Neuro-sliding mode control of robotic manipulators , 1997, 1997 8th International Conference on Advanced Robotics. Proceedings. ICAR'97.

[20]  Rainer Palm,et al.  Model based fuzzy control - fuzzy gain schedulers and sliding mode fuzzy controllers , 1996 .

[21]  Mark W. Spong,et al.  Robot dynamics and control , 1989 .

[22]  Fuchun Sun,et al.  Neural network control of flexible-link manipulators using sliding mode , 2006, Neurocomputing.

[23]  John Y. Hung,et al.  Variable structure control: a survey , 1993, IEEE Trans. Ind. Electron..