An indirect approach to adaptive control of nonlinear systems using quasi-ARMAX model

Abstract

This paper presents an adaptive control scheme for nonlinear systems based on a quasi-ARMAX prediction model that is a specially constructed associative memory network consisting of multiple neurofuzzy models and is distinctive to usual neural networks in that it is linear in both the parameters to be estimated and the input variables to be synthesized in a control system. This advantage is taken to develop a nonlinear adaptive control scheme similarly to linear one.