This paper investigates an adaptive fuzzy tracking controller for uncertain strict-feedback nonlinear systems suffering from asymmetric time-varying state constraints, unmeasured states, and unknown external disturbances. Firstly, a state observer with a simplified structure is constructed to approximate the unavailable system states based on fuzzy logic systems. The difficulties caused by time-varying state constraints are effectively addressed in a direct approach via the nonlinear state-dependent functions. Compared to the classical barrier Lyapunov functions-based (BLFs-based) method, the strict condition imposed on the virtual controller is eliminated, which significantly enhances the applicability of the controller in practical systems. Meanwhile, to handle the issue of “explosion of complexity,” a novel adaptive fuzzy tracking control technique is proposed by using the sliding-mode differentiator. Finally, rigorous stability analysis is employed to verify that the error between the system output signal and the reference signal can converge to an arbitrarily small set around the origin, and all closed-loop signals are bounded without time-varying state constraints violation. The effectiveness of the theoretical result is further illustrated by two simulation examples.

本文研究了一种自适应模糊跟踪控制器，用于处理受不对称时变状态约束、不可测量状态和未知外部干扰影响的不确定严格反馈非线性系统。首先，构造一个结构简化的状态观测器来近似基于模糊逻辑系统的不可用系统状态。由时变状态约束引起的困难可以通过非线性状态相关函数以直接方法有效地解决。与经典的基于势垒李亚普诺夫函数（BLF）的方法相比，消除了对虚拟控制器施加的严格条件，显着增强了控制器在实际系统中的适用性。同时，为了解决“复杂性爆炸”的问题，利用滑模微分器提出了一种新颖的自适应模糊跟踪控制技术。最后，采用严格的稳定性分析来验证系统输出信号和参考信号之间的误差可以收敛到原点附近的任意小集合，并且所有闭环信号都有界，不会违反时变状态约束。通过两个仿真算例进一步说明了理论结果的有效性。