Abstract
In this paper, an observer-based adaptive fuzzy tracking control is considered for a class of strict-feedback nonlinear systems. The nonlinear functions and unmeasured states in the system are estimated by means of fuzzy logic systems and fuzzy state observers, respectively. In addition, the tan-type barrier Lyapunov specifies that the tracking error is limited to a given area. An improved event-triggered technique is introduced in the controller design to save the network resources and avoid the Zeno-behavior. It is proven that the proposed controller can ensure that all the signals of the closed-loop system are uniformly and ultimately bounded. Finally, the simulation results verify the feasibility of the design scheme.
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