Regular Papers

International Journal of Control, Automation and Systems 2006; 4(2): 139-145

© The International Journal of Control, Automation, and Systems

Tracking Control of Robotic Manipulators based on the All-Coefficient Adaptive Control Method

Yongjun Lei and Hongxin Wu

Chinese Academy of Space Technology, China

Abstract

A multi-variable Golden-Section adaptive controller is proposed for the tracking control of robotic manipulators with unknown dynamics. With a small sample time, the unknown dynamics of the robotic manipulator are denoted equivalently by a characteristic model of a 2-order multivariable time-varying difference equation. The coefficients of the characteristic model change slowly with time and some of their valuable characteristic relationships emerge. Based on the characteristic model, an adaptive algorithm with a simple form for the control of robotic manipulators is presented, which combines the multi-variable Golden-Section adaptive control law with the weighted least squares estimation method. Moreover, a compensation neural network law is incorporated into the designed controller to reduce the influence of the coefficients estimation error on the control performance. The results of the simulations indicate that the developed control scheme is effective in robotic manipulator control.

Keywords Adaptive control, all-coefficient adaptive control, characteristic models, manipulators, multivariable control, golden-section control.

Article

Regular Papers

International Journal of Control, Automation and Systems 2006; 4(2): 139-145

Published online April 1, 2006

Copyright © The International Journal of Control, Automation, and Systems.

Tracking Control of Robotic Manipulators based on the All-Coefficient Adaptive Control Method

Yongjun Lei and Hongxin Wu

Chinese Academy of Space Technology, China

Abstract

A multi-variable Golden-Section adaptive controller is proposed for the tracking control of robotic manipulators with unknown dynamics. With a small sample time, the unknown dynamics of the robotic manipulator are denoted equivalently by a characteristic model of a 2-order multivariable time-varying difference equation. The coefficients of the characteristic model change slowly with time and some of their valuable characteristic relationships emerge. Based on the characteristic model, an adaptive algorithm with a simple form for the control of robotic manipulators is presented, which combines the multi-variable Golden-Section adaptive control law with the weighted least squares estimation method. Moreover, a compensation neural network law is incorporated into the designed controller to reduce the influence of the coefficients estimation error on the control performance. The results of the simulations indicate that the developed control scheme is effective in robotic manipulator control.

Keywords: Adaptive control, all-coefficient adaptive control, characteristic models, manipulators, multivariable control, golden-section control.

IJCAS
July 2024

Vol. 22, No. 7, pp. 2055~2340

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