引用本文:
刘哲,邹涛,孙威,陆云松.基于实时优化遗传算法的磨削机器人阻抗控制方法研究[J].控制理论与应用,2018,35(12):1788~1795.[点击复制]
Liu Zhe,Zou Tao,Sun Wei,Lu Yun-song.Research on Impedance Control Method Based on Real-time Optimization Genetic Algorithm[J].Control Theory and Technology,2018,35(12):1788~1795.[点击复制]
基于实时优化遗传算法的磨削机器人阻抗控制方法研究
Research on Impedance Control Method Based on Real-time Optimization Genetic Algorithm
摘要点击 2026  全文点击 937  投稿时间:2018-07-20  修订日期:2019-01-02
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DOI编号  10.7641/CTA.2018.80542
  2018,35(12):1788-1795
中文关键词  机械臂力控制  磨削机器人  模型预测控制
英文关键词  The force control of robot  Grinding robot  Model predictive control.
基金项目  国家自然科学基金(61773366)
作者单位邮编
刘哲 
中国科学院沈阳自动化研究所 中国科学院网络化控制系统重点实验室 110016
邹涛* 中国科学院沈阳自动化研究所 中国科学院网络化控制系统重点实验室 110016
孙威 中国科学院沈阳自动化研究所 中国科学院网络化控制系统重点实验室 
陆云松 中国科学院沈阳自动化研究所 中国科学院网络化控制系统重点实验室 
中文摘要
      针对机械臂与环境接触时恒力跟踪动态响应速度慢的问题,提出了基于实时优化遗传算法的阻抗控制方法。在研究过程中,依据机械臂恒力跟踪的响应速度和控制精度的综合性能指标,改进了离线优化中遗传算法的交叉、变异和计算适应度值等操作算子的处理方式,实现了阻抗控制方法中的控制参数的实时优化。仿真结果表明:与传统控制方法相比,该方法可以在保证控制精度的前提下,提高了机械臂与环境接触力的动态响应速度,降低了控制过程超调量,获得了较好的调节品质。
英文摘要
      Aiming at the problem of slow dynamic response during constant force tracking when the manipulator is in contact with the environment. An impedance control method based on real-time optimization genetic algorithm is proposed. In the research process, according to the comprehensive performance index of the response speed and control precision of the mechanical arm constant force tracking, the processing methods of the operator, such as the crossover, variation and calculation fitness value of the genetic algorithm in offline optimization, are improved, and the real-time optimization of control parameters for the impedance control is realized. The simulation results show that compared with the traditional control method, the method can improve the dynamic response speed of the mechanical arm and the environment contact force under the premise of ensuring the control precision, reduce the overshoot of the control process, and obtain better adjustment quality.