Adaptive neural network dynamic surface control for a class of nonlinear systems with uncertain time delays

This paper presents a solution to tracking control problem for a class of nonlinear systems with unknown parameters and uncertain time-varying delays. A new adaptive neural network (NN) dynamic surface controller (DSC) is developed. Some assumptions on uncertain time delays, which were required to be satisfied in previous works, are removed by introducing a novel indirect neural network algorithm into dynamic surface control framework. Also, the designed controller is independent of the time delays. Moreover, the dynamic compensation terms are introduced to facilitate the controller design. It is shown that the closed-loop tracking error converges to a small neighborhood of zero. Finally, a chaotic circuit system is initially bench tested to show the effectiveness of the proposed method. © 2016, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg.