Neural network learning algorithm for a class of interconnected nonlinear systems

Abstract

In this paper, an adaptive neural network algorithm is developed for a class of interconnected nonlinear systems. Neural networks (NNs) are used to approximate the unknown nonlinear functions and interconnections in the subsystems. A systematic approach is established to synthesize the adaptive NN learning control scheme that ensures the boundedness of all the signals in the closed-loop system. The effectiveness of the proposed scheme is demonstrated by computer simulations. © 2008 Elsevier B.V. All rights reserved.