Title :
Robust control of a two-link flexible manipulator with neural networks based quasi-static deflection compensation
Author :
Li, Yuanchun ; Guangjun Liu ; Hong, Tao ; Liu, Keping
Author_Institution :
Dept. of Control Sci. & Eng., Jilin Univ., Changchun, China
Abstract :
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.
Keywords :
H∞ control; closed loop systems; compensation; flexible manipulators; neurocontrollers; perturbation theory; position control; robust control; H∞ control; assumed mode method; composite algorithm; decomposition based robust controller; elastic mode; fast subsystem; neural network based quasistatic deflection compensation; neural network compensation scheme; overall closed loop control; robust control; singular perturbation theory; slow subsystem; two-link flexible manipulator; Adaptive control; Aerodynamics; Equations; Manipulator dynamics; Neural networks; Nonlinear dynamical systems; Payloads; Robust control; Trajectory; Uncertainty;
Conference_Titel :
American Control Conference, 2003. Proceedings of the 2003
Print_ISBN :
0-7803-7896-2
DOI :
10.1109/ACC.2003.1242562
