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

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.

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.