Improving transient response of adaptive control systems using multiple neural network models

Abstract

Multiple Radial Basis Function (RBF) neural network models are used to approximate a kind of discrete time nonlinear system described by a combination of nonlinear and linear part. Based on these models, Multiple model adaptive control strategy is given to improve the transient response of closed-loop system. Simulations according to different uncertain changing parameters in the model of the system are studied to show the efficiency of the proposed method. © 2010 Springer-Verlag Berlin Heidelberg.