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全柔性空间机器人运动振动一体化输入受限重复学习控制

付晓东 陈力

付晓东, 陈力. 全柔性空间机器人运动振动一体化输入受限重复学习控制[J]. 力学学报, 2020, 52(1): 171-183. doi: 10.6052/0459-1879-19-289
引用本文: 付晓东, 陈力. 全柔性空间机器人运动振动一体化输入受限重复学习控制[J]. 力学学报, 2020, 52(1): 171-183. doi: 10.6052/0459-1879-19-289
Fu Xiaodong, Chen Li. AN INPUT LIMITED REPETITIVE LEARNING CONTROL OF FLEXIBLE-BASE TWO-FLEXIBLE-LINK AND TWO-FLEXIBLE-JOINT SPACE ROBOT WITH INTEGRATION OF MOTION AND VIBRATION[J]. Chinese Journal of Theoretical and Applied Mechanics, 2020, 52(1): 171-183. doi: 10.6052/0459-1879-19-289
Citation: Fu Xiaodong, Chen Li. AN INPUT LIMITED REPETITIVE LEARNING CONTROL OF FLEXIBLE-BASE TWO-FLEXIBLE-LINK AND TWO-FLEXIBLE-JOINT SPACE ROBOT WITH INTEGRATION OF MOTION AND VIBRATION[J]. Chinese Journal of Theoretical and Applied Mechanics, 2020, 52(1): 171-183. doi: 10.6052/0459-1879-19-289

全柔性空间机器人运动振动一体化输入受限重复学习控制

doi: 10.6052/0459-1879-19-289
基金项目: 1) 国家自然科学基金(11372073);国家自然科学基金(11072061);福建省工业机器人基础部件技术重大研发平台(2014H21010011)
详细信息
    通讯作者:

    陈力

  • 中图分类号: TP241

AN INPUT LIMITED REPETITIVE LEARNING CONTROL OF FLEXIBLE-BASE TWO-FLEXIBLE-LINK AND TWO-FLEXIBLE-JOINT SPACE ROBOT WITH INTEGRATION OF MOTION AND VIBRATION

  • 摘要: 探究基座、臂、关节全柔性影响下空间机器人动力学模拟、运动控制及基座、臂、关节三重柔性振动主动抑制的问题, 设计了不基于系统模型信息的运动振动一体化输入受限重复学习控制算法. 将柔性基座与关节等效为线性弹簧与扭转弹簧, 柔性臂视为欧拉-伯努利梁模型, 利用拉格朗日方程与假设模态法建立动力学模型, 然后, 用奇异摄动理论将模型分解为包含刚性变量与臂柔性振动的慢变子系统, 包含基座、关节柔性振动的快变子系统, 并分别设计相应的子控制器, 构成了带关节柔性补偿的一体化控制算法. 针对慢变子系统, 提出输入受限重复学习控制算法, 由双曲正切函数, 饱和函数与重复学习项构成, 双曲正切函数与饱和函数实现输入力矩受限要求, 重复学习项补偿周期性系统误差, 以完成对基座姿态、关节铰周期轨迹的渐进稳定追踪. 然而, 为了同时抑制慢变子系统臂的柔性振动, 运用虚拟力的概念, 构造同时反映臂柔性振动与系统刚性运动的混合轨迹, 提出了基于虚拟力概念的输入受限重复学习控制器, 保证基座、关节轨迹精确追踪的同时, 对臂的柔性振动主动抑制. 针对快变子系统, 采用线性二次最优控制算法抑制基座与关节的柔性振动. 仿真结果表明: 控制器适用于一般柔性非线性系统, 满足输入力矩受限要求, 实现对周期信号的高精度追踪, 有效抑制基座、臂、关节的柔性振动, 证实算法的可行性.

     

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出版历程
  • 收稿日期:  2019-10-21
  • 刊出日期:  2020-02-10

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