基于迭代学习的柔性关节机械臂鲁棒输出跟踪

摘要

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 es-tablished , and the influence caused by an immeasurable state of system and model uncertainties to the control accu-racy 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.