Robust Evolving Fuzzy Adaptive Control with Input-Domain Clustering

Abstract The paper proposes a fuzzy model reference adaptive control approach with evolving antecedent part. The proposed algorithm has the possibility 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.