Expert Skill-Based Gain Tuning in Discrete-Time Adaptive Control for Robots

Author:

Kawasaki Haruhisa, ,Li Geng

Abstract

This paper presents a gain tuning method based on the sampling period in discrete-time adaptive control for robots. Gain matrices of model-based adaptive control in a continuous-time system are allowed a high gain positive definite. The maximum of the gains depends on the sampling period, however, and gain tuning is very time-consuming. It is thus desirable to give a gain tuning rule in discrete-time adaptive control. The proposed gain tuning consists of two steps. The first is gain tuning at the basic sampling period by a skilful specialist by trial and error. The second step, executed if the sampling period changes, is a new gain calculation based on a new sampling period. The simulation and experiments with 1-dof and 3-dof robots demonstrate that the robot controller is stable at the large variance of sampling period changes and more accurate than a fixed gain controller.

Publisher

Fuji Technology Press Ltd.

Subject

Electrical and Electronic Engineering,General Computer Science

Reference10 articles.

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3. D. E. Koditschek, “Adaptive Techniques for Mechanical Systems,” Proc. of the Fifth Yale Workshop on the Applications of Adaptive Systems Theory, pp. 259-265, 1987.

4. H. Berghuis, R. Ortega and H. Nijmeijer, “A Robust Adaptive Controller for Robot Manipulators,” IEEE Int. Conf. on Robotics Automat., pp. 1876-1881,1992.

5. R. R. Y. Zhen, “An Adaptive Approach to Constrained Robot Motion Control, IEEE lnt. Conf. on Robotics and Automation,” pp. 1833-1838, 1995.

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