Observer-based adaptive control of robot manipulators: Fuzzy systems approach

This paper presents a fuzzy adaptive control suitable for motion control of multi-link robot manipulators with structured and unstructured uncertainties. When joint velocities are available, full state fuzzy adaptive feedback control is designed to ensure the stability of the closed loop dynamic. If the joint velocities are not measurable, an observer is introduced and an adaptive output feedback control is designed based on the estimated velocities. In the proposed control scheme, we need not derive the linear formulation of robot dynamic equation and tune the parameters. To reduce the number of fuzzy rules of the fuzzy controller, we consider the properties of robot dynamics and the decomposition of the uncertainties terms. The proposed controller is robust against uncertainties and external disturbance. Further, it is shown that required stability conditions, in both cases, can be formulated as LMI problems and solved using dedicated software. The validity of the control scheme is demonstrated by computer simulations on a two-link robot manipulator.

[1]  Chen Bin,et al.  Fuzzy adaptive output feedback control for MIMO nonlinear systems , 2005, Fuzzy Sets Syst..

[2]  W. Ham.  Adaptive control based on explicit model of robot manipulator , 1993, IEEE Trans. Autom. Control..

[3]  M. Hanmandlu,et al.  Adaptive generalized model-based control of robot manipulators , 1993 .

[4]  Oscar Castillo,et al.  Intelligent adaptive model-based control of robotic dynamic systems with a hybrid fuzzy-neural approach , 2003, Appl. Soft Comput..

[5]  H. Hemami,et al.  Nonlinear Adaptive Control of an N-Link Robot with Unknown Load , 1987 .

[6]  Mark W. Spong,et al.  Adaptive motion control of rigid robots: a tutorial , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[7]  Shaocheng Tong,et al.  A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems , 2003, IEEE Trans. Fuzzy Syst..

[8]  Meng Joo Er,et al.  Hybrid adaptive fuzzy controllers of robot manipulators with bounds estimation , 2000, IEEE Trans. Ind. Electron..

[9]  Meng Joo Er,et al.  Adaptive control of robot manipulators using fuzzy neural networks , 2001, IEEE Trans. Ind. Electron..

[10]  Bor-Sen Chen,et al.  Robust tracking enhancement of robot systems including motor dynamics: a fuzzy-based dynamic game approach , 1998, IEEE Trans. Fuzzy Syst..

[11]  Frank L. Lewis,et al.  Control of Robot Manipulators , 1993 .

[12]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control , 1994 .

[13]  C. Lee Giles,et al.  Pruning recurrent neural networks for improved generalization performance , 1994, IEEE Trans. Neural Networks.

[14]  J. Lin,et al.  Fuzzy logic control for flexible link robot arm by singular perturbation approach , 2002, Appl. Soft Comput..

[15]  S. Shankar Sastry,et al.  Adaptive Control of Mechanical Manipulators , 1987, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[16]  Choo Min Lim,et al.  Application of fuzzy logic control to a manipulator , 1991, IEEE Trans. Robotics Autom..

[17]  Jennie Si,et al.  The best approximation to C/sup 2/ functions and its error bounds using regular-center Gaussian networks , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[18]  Guy Jumarie,et al.  Tracking control of mechanical systems via sliding Lagrangian , 1995, J. Intell. Robotic Syst..

[19]  R. Tanscheit,et al.  Experiments with the use of a rule-based self-organising controller for robotics applications , 1988 .

[20]  J. Slotine,et al.  On the Adaptive Control of Robot Manipulators , 1987 .

[21]  Tong Shaocheng,et al.  Fuzzy adaptive output tracking control of nonlinear systems , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[22]  S. Shankar Sastry,et al.  Adaptive Control of Mechanical Manipulators , 1987 .

[23]  Amar Goléa,et al.  Stable indirect fuzzy adaptive control , 2003, Fuzzy Sets Syst..