An enhanced neural adaptive control scheme for discrete-time non-affine nonlinear systems

Abstract

An adaptive control procedure utilising neural networks is presented. The method is based on the model reference control technique and can be applied to multi-input multi-output discrete-time nonlinear systems of unknown structure.Multi-layered neural networks are used to approximate the plant Jacobian and synthesise the controller. An enhanced reference model is proposed that generates the desired output response and enables sufficient conditions for the convergence of the tracking error between the desired output and controlled output to be derived. Lyapunov theory is used to show that the overall system is stable. Simulation studies demonstrate that the proposed scheme performs well even in the presence of dynamic perftubations.