Comparison Study of Adaptive Controllers for Robot Manipulators

Article type: Research Article

Authors: Neo, S.S. | Er, M.J.

Affiliations: School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 2263, e-mail: essneo@ntuvax.ntu.ac.sg

Abstract: The performance of two adaptive robot control algorithms, namely the adaptive algorithm by Slotine and Li and the proposed direct adaptive fuzzy control algorithm, were studied. In Slotine and Li's method, the algorithm consists of proportional derivative feedback and a full dynamics feed forward part, with the unknown manipulator and payload parameters being estimated on-line. The algorithm depends heavily on the particular structure of manipulator dynamics and needed three simplifying properties to derive the adaptive law. The direct adaptive fuzzy algorithm uses a fuzzy logic system as the controller. The derivation of the controller does not require any knowledge of the manipulator dynamics and the uncertainty in the system, only the boundary of the dynamics. The predominant concern of the two adaptation laws is to reduce the tracking errors. In particular, they require no feedback of joint accelerations. Theoretical results and simulation studies on a two-link robot manipulator show that both methods are robust and stable. The direct adaptive fuzzy controller outperforms the adaptive controller in mass variation.

DOI: 10.3233/IFS-1996-4203

Journal: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 2, pp. 107-119, 1996