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Robust control of a two-link flexible manipulator with neural networks based quasi-static deflection compensation

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4 Author(s)
Yuanchun Li ; Dept. of Control Sci. & Eng., Jilin Univ., Changchun, China ; Guangjun Liu ; Tao Hong ; Keping Liu

A robust control method of a two-link flexible manipulator with neural networks based quasi-static distortion compensation is proposed and experimentally investigated. The dynamics equation of the flexible manipulator is divided into a slow subsystem and a fast subsystem based on the assumed mode method and singular perturbation theory. A decomposition based robust controller is proposed with respect to the slow subsystem, and H control is applied to the fast subsystem represented by the elastic mode . The overall closed loop control is determined by the composite algorithm that combines the two control laws. Furthermore, a neural network compensation scheme is also integrated into the control system to compensate for quasi-static deflection. The proposed control method has been implemented on a two-link flexible manipulator for precise end-tip tracking control. Experimental results are presented in this paper along with discussions.

Published in:

American Control Conference, 2003. Proceedings of the 2003  (Volume:6 )

Date of Conference:

4-6 June 2003