A neural-based adaptive control method study on a class of nonaffine nonlinear systems

Discussion on the stability and tracking problem of the nonlinear systems and especially nonaffine nonlinear systems is presented in this paper. A neural-based adaptive controller is designed in the paper to solve the tracking control problems of some unknown nonlinear systems. Robustness of modeling error has been effectively improved under the action of feedback-linearization with direct neural adaptive law; the method is less dependent on modeling accuracy as well. The tracking error of the nonaffine system can converge into a small neighborhood of the origin with the controller and the stability of the closed-loop system is guaranteed.