摘要
针对不同重力环境条件下柔性关节空间机械臂的末端轨迹跟踪问题,为提高其跟踪精度和系统抗干扰能力,提出一种基于奇异摄动理论的自适应迭代学习控制。首先建立了地面重力条件下和空间微重力条件下柔性关节机械臂的动力学模型,这2种模型考虑了摩擦带来的影响。利用奇异摄动法将系统分为快变子系统和慢变子系统。针对快变子系统设计速度反馈控制率,来抑制柔性关节带来的弹性振动。针对慢变子系统设计自适应迭代学习控制,该控制方法是在PD反馈结构的基础上增加了一个迭代项,可以很好地处理未知参数和扰动,提高整个系统的稳定性和抗干扰能力。仿真结果表明,该方法可以使柔性关节空间机械臂在不同重力环境下都具有良好的轨迹跟踪效果和抖动抑制能力,验证了该方法的有效性。
In order to improve the tracking accuracy and anti-jamming ability of flexible joint space manipulator,an adaptive iterative learning control based on singular perturbation theory is proposed for different gravity conditions.Firstly,the dynamic models of flexible joint manipulator under ground gravity and space microgravity are established,which consider the influence of friction.The system is divided into fast subsystem and slow subsystem by singular perturbation method.A speed feedback control rate is designed for the fast variable subsystem to suppress the elastic vibration caused by flexible joints.An adaptive iterative learning control is designed for slow-varying subsystems.The control method adds an iteration term on the basis of PD feedback structure,which can deal with unknown parameters and disturbances well,and improve the stability and anti-interference ability of the whole system.The simulation results show that this method can make the flexible joint space manipulator have good trajectory tracking effect and jitter suppression ability in different gravity environments,and verify the effectiveness of this method.
作者
孟玲聪
刘福才
赵文娜
刘剑鸣
Meng Lingcong;Liu Fucai;Zhao Wenna;Liu Jianming(Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004)
出处
《高技术通讯》
EI
CAS
北大核心
2020年第10期1078-1084,共7页
Chinese High Technology Letters
基金
载人航天领域预研(2016040301)
河北省自然科学基金(F2019203505)资助项目。
关键词
空间机械臂
柔性关节
重力
迭代学习
自适应
space manipulator
flexible-joint
gravity
iterative learning
self-adaption
