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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...
This paper studies an adaptive fuzzy control problem for a class of uncertain nonlinear systems in the pure-feedback form. Compared with the existing approaches, the two main advantages are that the proposed algorithm can be implemented by utilizing only one fuzzy logic systems (FLS) approximator and the robustness of the closed-loop system is improved. The proposed adaptive fuzzy control algorithm...
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