基于迭代学习的柔性关节机械臂鲁棒输出跟踪

Iterative learning observer based robust output feedback tracking control for flexible manipulator

针对柔性关节机械臂的输出反馈跟踪控制问题,提出了基于迭代学习观测器(iterative learning observer,ILO)的鲁棒控制策略。本文对柔性关节机械臂进行数学建模,分析了系统不可测状态和模型不确定性对跟踪控制精度带来的影响。设计了ILO对系统的内部状态和由模型不确定性引起的复合扰动进行在线估计,设计滤波反步控制器完成对输入指令的跟踪。利用Lyapunov稳定性理论分析了闭环控制系统的全局稳定性。仿真结果表明,提出的方法能够有效实现柔性关节机械臂的输出反馈跟踪控制,获得较高的跟踪精度,且对于模型不确定性具有较强的鲁棒性。

For the output feedback tracking control of a flexible joint manipulator, an iterative learning observer （ ILO）-based robust controller was proposed. First, the mathematical model of the flexible joint manipulator was established, and the influence caused by an immeasurable state of system and model uncertainties to the control accuracy was analyzed. The ILO was proposed to estimate the composite disturbance arising from the interior system states and the uncertainties of model online. A command-filtered backstepping controller was designed to track the input command. Finally, global stability of the closed-loop system was analyzed based on Lyapunov theory. Simula- tions show that the proposed control strategy could successfully deal with the output feedback tracking control for the flexible joint manipulator. The proposed control strategy demonstrated high control accuracy, with robustness a- gainst system uncertainties.