Adaptive fuzzy learning control for a class of nonlinear dynamic systems

This paper presents an adaptive iterative learning control scheme that is a pplicable to a class of nonlinear systems. The control scheme guarantees sy stem stability and boundedness by using the feedback controller coupled wit h the fuzzy compensator and achieves precise tracking by using the iterativ e learning rules. In the feedback plus fuzzy compensator unit, the feedback control part stabilizes the overall closed-loop system and keeps its error bounded, and the fuzzy compensator estimates and compensates for the nonli near part of the system, thereby keeping the feedback gains reasonably low in the feedback controller. The fuzzy compensator is designed by applying t he fuzzy approximation technique to the uncertain nonlinear term to be comp ensated. In the iterative learning controller, a simple learning control ru le is used to achieve precise tracking of the reference signal and a parame ter learning algorithm is used to update the parameters in the fuzz, compen sator so as to identify the uncertain nonlinearity as much as possible. (C) 2000 John Wiley & Sons, Inc.