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.

本文针对一类严格反馈非线性系统，考虑了基于观测器的自适应模糊跟踪控制。分别通过模糊逻辑系统和模糊状态观测器估算系统中的非线性函数和未测状态。此外，棕褐色势垒Lyapunov指定跟踪误差仅限于给定区域。控制器设计中引入了一种改进的事件触发技术，以节省网络资源并避免Zeno行为。事实证明，所提出的控制器可以确保闭环系统的所有信号均一且最终有界。最后，仿真结果验证了该设计方案的可行性。