This paper considers the fixed-time tracking control problem for system-constrained nonlinear pure-feedback systems involving input saturation and output constraints. A sequence of auxiliary virtual and actual input signals is designed to obtain an expression for the system tracking error and stabilize the system. A combination of the fixed-time stability theory, barrier Lyapunov function, and radial basis function neural network is employed to develop the proposed method for obtaining the expected performance from the considered system. Further, a theorem is proposed to ensure that the designed controller allows the system output to track the reference signal within a fixed time, ensuring that the tracking error is limited to a small neighborhood of origin within a fixed time and that all the signals in the system are bounded. The aforementioned problem can be solved using the proposed control method, and the simulation experiments indicate the effectiveness of the designed controller.

本文考虑了具有输入饱和和输出约束的系统约束非线性纯反馈系统的固定时间跟踪控制问题。设计一系列辅助虚拟和实际输入信号，以获取系统跟踪误差的表达式并稳定系统。结合固定时间稳定性理论，势垒Lyapunov函数和径向基函数神经网络来开发所提出的方法，以从考虑的系统中获得预期的性能。此外，提出了一个定理，以确保所设计的控制器允许系统输出在固定时间内跟踪参考信号，从而确保将跟踪误差限制在固定时间内的小原点邻域中，并确保系统是有界的。