A new neural network structure dedicated to the control of nonlinear systems

Abstract

Proposes a new neural network structure to design a robust controller for non-exactly known nonlinear systems. Based on input-output data, the neural network structure provides a global affine model of the controlled system which is compatible with well known nonlinear control techniques. An affine neural tracking controller is developed and applied to an inverted pendulum submitted to random perturbations. The performance of the controller and the main advantage of the proposed approach are discussed.