Tracking control of a robot manipulator using a direct model reference adaptive fuzzy control

Abstract

A direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal. The suggested design technique is applied to tracking control of a two-link robot manipulator.