Adaptive NN tracking control of nonlinear discrete-time systems

For a class of uncertain discrete-time nonlinear MIMO systems, a neural controller is proposed based on the adaptive backstepping technique. The high-order neural networks are used to approximate the unknown nonlinear functions. The result show all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of zero by choosing the design parameters appropriately. Compared with the previous research for discrete-time MIMO systems, robustness of the proposed adaptive algorithm is obvious improved.