Fuzzy input-output controllers are universal approximators
Fuzzy Sets and Systems
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Explicit formulas for fuzzy controller
Fuzzy Sets and Systems
Brief Robust tracking control for nonlinear MIMO systems via fuzzy approaches
Automatica (Journal of IFAC)
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Fuzzy neural network adaptive tracking controller is designed to realize the tracking control for a class of unknown nonlinear interconnected systems. No constraint or matching conditions of the uncertain terms are required. For the low dimensions unknown dynamic of the subsystems and the high one of the interconnected terms, two classes of fuzzy rules are adopted respectively to approximate the unknowns. The neural network is used to counteract the extra gains of the controller. The fuzzy sliding mode control is developed to compensate for the exterior disturb and the fuzzy neural network approximation errors. By the Simultaneity, based on Lyapunov method, the parameters of the systems are regulated on line by the adaptive laws. Global asymptotic stability is assured with the tracking errors converging to a neighborhood of zero.