Adaptive observer for a class of nonlinear systems using neural networks

Abstract

This paper presents an adaptive observer using neural networks for a class of nonlinear systems. The adaptive observer follows the nonlinear model estimation method for automated fault diagnosis. The contributions of this article include: modification of the estimation model as appropriate for certain nonlinear control applications; modification of the stability proofs; investigation of the observer performance through an illustrative simulation.