This paper presents an adaptive tracking control approach for a class of uncertain nonlinear strict-feedback systems subject to time-varying full state constraints and time-delays. To stabilize such systems, an adaptive tracking controller is structured by combining the neural networks and the backstepping technique. To guarantee all states do not violate the time-varying constraint sets, the appropriate time-varying Barrier Lyapunov functions are employed at each stage of the backstepping procedure. By using the Lyapunov-Krasovskii functionals, the effect of time delay is eliminated. It is proved that the output follows the desired signal well without violating any constraints, and all the signals in the closed-loop system are semiglobal uniformly ultimately bounded by using the Lyapunov analysis. Finally, a comparison study simulation is provided to illustrate the effectiveness of the proposed control strategy.

中文翻译：

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具有时变全状态约束的非线性时滞系统的自适应跟踪控制

本文针对一类受时变全状态约束和时滞影响的不确定非线性严格反馈系统提出了一种自适应跟踪控制方法。为了稳定这样的系统，通过结合神经网络和反步技术构建了一个自适应跟踪控制器。为了保证所有状态不违反时变约束集，在反步过程的每个阶段都采用了适当的时变 Barrier Lyapunov 函数。通过使用 Lyapunov-Krasovskii 泛函，消除了时间延迟的影响。通过李雅普诺夫分析证明了输出很好地跟随期望信号而不违反任何约束，并且闭环系统中的所有信号都是半全局一致的，最终有界。最后，