Extended dynamic fuzzy logic system for a class of MIMO nonlinear systems and its application to robotic manipulators

Abstract

SUMMARY: This paper presents an indirect adaptive fuzzy control scheme for a class of unknown multi-input multi-output (MIMO) nonlinear systems with external disturbances. Within this scheme, the dynamic fuzzy logic system (DFLS) is employed to identify the unknown nonlinear MIMO systems. The control law and parameter adaptation laws of DFLS are derived based on the Lyapunov synthesis approach. The control law is robustified in H^∞ sense to attenuate external disturbance, model uncertainties, and fuzzy approximation errors. It is shown that under appropriate assumptions it guarantees the boundness of all signals in the closed-loop system and the asymptotic convergence to zero of tracking errors. An extensive simulation on the tracking control of a two-link rigid robotic manipulator verifies the effectiveness of the proposed algorithms.