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Lyapunov function-based control laws for revolute robot arms: tracking control, robustness, and adaptive control

机译:基于Lyapunov的旋转机器人手臂基于功能的控制定律:跟踪控制,鲁棒性和自适应控制

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摘要

A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to an energy-like Lyapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates.
机译:引入了一类用于全旋转机器人手臂的联合级控制律。该分析类似于类似能量的Lyapunov函数方法,不同之处在于,根据潜在的联合空间拓扑对闭环势函数进行了成形。这种方法让分析变得更加简单,并导致了一类新的控制设计,它既保证了全局渐近稳定性,又保证了局部指数稳定性。当库仑和粘滞摩擦以及参数不确定性作为模型扰动存在时,对控制律的类似滑模的修改会导致增强鲁棒性的外环。自适应控制是在同一框架内制定的。采用线性参数公式,通过简单地将未知模型参数替换为其估计值,即可得出全局渐近稳定的自适应控制律。

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