Investigation of Adjustable Radial Basis Function estimations for Non-Linear System

Abstract

This paper gives idea about design method for adaptive neural controller is proposed and it is applied to the non-linear system Continuous stirred tank reactor CSTR. The investigating controller used in this paper is designed in tuned with adaptive process. To analyze the performance of effect of foot print of uncertainty on the controllers’ performance two various types of algorithms namely state feedback control and observer based control are used Radial basis function Neural network is utilized for approximation of the nonlinear function . Software validation result of suggested method is discussed below.