结合实时优化遗传算法的磨削机器人阻抗控制  

Impedance control of grinding robot based on real-time optimization genetic algorithm

作　　者：刘哲[1,2,3] 邹涛[1,2] 孙威 陆云松[1,2] LIU Zhe;SUN Wei;LU Yun-song(Key Laboratory of Networked Control System of Chinese Academy of Sciences, Shenyang Institute of Automationof Chinese Academy of Sciences, Shenyang Liaoning 110016, China;Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang Liaoning 110016, China;University of Chinese Academy of Sciences, Beijing 110049, China)

机构地区：[1]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,辽宁沈阳110016 [2]中国科学院机器人与智能制造创新研究院,辽宁沈阳110016 [3]中国科学院大学,北京100049

出　　处：《控制理论与应用》2018年第12期1788-1795,共8页Control Theory & Applications

基　　金：国家自然科学基金项目(61773366;61533015)资助~~

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,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,通过改进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.Aiming at the problem of slow dynamic response during constant force tracking when the manipulator is in contact with the environment. 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 off line 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.

关 键 词：磨削机器人 遗传算法 机械臂力控制 

分 类 号：TP242.2[自动化与计算机技术—检测技术与自动化装置]