论文标题
具有状态和输入约束的不确定Euler-Lagrange系统的自适应跟踪控制
Adaptive Tracking Control of Uncertain Euler-Lagrange Systems with State and Input Constraints
论文作者
论文摘要
本文提出了一种具有参数不确定性的状态和输入约束的Euler-Lagrange（E-L）系统的新型控制体系结构。简单的饱和控制器从策略上与基于Lyapunov的障碍函数（BLF）控制器结合在一起，以确保状态和输入约束满意度。据作者所知，这是通过用户指定状态和输入约束来保证渐近跟踪的E-L系统的第一个结果。拟议的控制器还确保所有闭环信号保持界限。使用机器人操纵器系统上的仿真来验证所提出的控制器在约束满意度和跟踪性能方面的功效。
This paper proposes a novel control architecture for state and input constrained Euler-Lagrange (E-L) systems with parametric uncertainties. A simple saturated controller is strategically coupled with a Barrier Lyapunov Function (BLF) based controller to ensure state and input constraint satisfaction. To the best of the authors' knowledge, this is the first result for E-L systems that guarantee asymptotic tracking with user-specified state and input constraints. The proposed controller also ensures that all the closed-loop signals remain bounded. The efficacy of the proposed controller in terms of constraint satisfaction and tracking performance is verified using simulation on a robot manipulator system.
