Neural Network Control for Uncertain Nonlinear Time-Delay Systems

Abstract

Based on stability theory, a class of neural network controller design of uncertain nonlinear time-delay systems is studied. Using the ability that neural network can approximate any nonlinear function, a kind of weights correction law based on radial basis function (RBF) neural network (NN) and the adaptive controller design scheme are proposed. According to Lyapunov stability analysis method, this paper gives the sufficient conditions that neural network controller can make this kind of uncertain nonlinear time-delay systems stable in the sense of Lyapunov. At last, the proposed neural network controller is verified to be correct and effective by the simulation examples.