This article presents a control scheme for the robot manipulator’s trajectory tracking task considering output error constraints and control input saturation. We provide an alternative way to remove the feasibility condition that most BLF-based controllers should meet and design a control scheme on the premise that constraint violation possibly happens due to the control input saturation. A bounded barrier Lyapunov function is proposed and adopted to handle the output error constraints. Besides, to suppress the input saturation effect, an auxiliary system is designed and emerged into the control scheme. Moreover, a simplified RBFNN structure is adopted to approximate the lumped uncertainties. Simulation and experimental results demonstrate the effectiveness of the proposed control scheme.

中文翻译：

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具有轨迹跟踪约束和输入饱和度的机器人机械手的神经控制

本文提出了一种考虑输出误差约束和控制输入饱和的机器人机械手轨迹跟踪任务的控制方案。我们提供了一种替代方法来消除大多数基于 BLF 的控制器应该满足的可行性条件，并在可能由于控制输入饱和而发生约束违反的前提下设计控制方案。提出并采用有界障碍李雅普诺夫函数来处理输出误差约束。此外，为了抑制输入饱和效应，设计了一个辅助系统并将其引入控制方案。此外，采用简化的 RBFNN 结构来近似集总不确定性。仿真和实验结果证明了所提出的控制方案的有效性。