Adaptive Control Design for High-order MIMO Nonlinear Time-delay Systems Based on Neural Network

An adaptive controller for a class of high-order MIMO nonlinear time-delay systems in block-triangular form is proposed in the paper. The radial basis function neural network is chosen to approximate the unknown nonlinear ftmetions in the system dynamics at first. Lyapunov-Krasovskii fi.mctionals are used to compensate the influence of delay terms. Then an adaptive neural network output tracking controller is designed by using the back-stepping recursive method. Based on Lyapunov stability theory, the proposed controller can guarantee all closed-loop signals are globally, uniformly and ultimately bounded, while the output tracking is able to converge to a neighborhood of the origin. Finally, a simulation example is given to illustrate the correctness of the theoretical results.