An implementation of an evolving fuzzy controller

Abstract

A fuzzy model reference adaptive control approach is proposed in the paper where the antecedent part of fuzzy rules evolves with the measured data. The consequent part consists of a controller with integral nature and the adaptation scheme is a direct one. The proposed algorithm is capable of controlling a plant with poorly known and/or time-varying nonlinearity which is an advantage over approaches with fixed antecedent part. It is intended for control of a large class of nonlinear plant models with the dominant dynamics of the first order. Such plants occur quite often in process industries. It is shown in the paper that the approach is also suitable for controlling an under-damped mechanical system.