Tracking Control of Nonlinear Systems with Uncertain Multiple Time Delays Based on Dynamic Adaptive Neural Network

For a class of nonlinear systems with uncertain multiple time delays, a kind of adaptive robust tracking controller is presented in this paper. First, a time-delay compensator as one of the controller´s important components is designed based on Lyapunov-Krasovskii function in order to deal with the multiple time delays. Then the other important component, a dynamic adaptive neural network, is introduced to ensure the system stable, which not only has adaptive parameters but has alterable topological structure that the number of hidden units can increase with the tracking error growing. Finally, a given demonstration shows the control scheme is effective in a chaotic system.