Neural Networks In Dynamical Systems

Multilayer networks and recurrent neural networks have proved extremely successful in pattern recognition problems as well as in associative learning. In this paper an attempt is made to demonstrate that both types of networks, combined in arbitrary configurations, will find application in complex dynamical systems. Well known results in linear systems theory and their extensions to conventional adaptive control theory are used to suggest models for the identification and control of nonlinear dynamic systems. The use of neural networks in dynamical systems raises many theoretical questions, some of which are discussed in the paper.