基于PSO优化的模糊PID恒力控制研究

针对工业机器人在抛磨等工作过程中对接触压力的要求，提出了一种基于粒子群(PSO)优化的模糊PID恒力控制方法。对柔性力控法兰装置的受力和气体流量模型进行分析，建立柔性力控法兰装置的数学模型；设计了基于PSO算法的模糊PID控制器，自适应调节模糊PID的控制参数，通过MATLAB仿真对比了普通PID、模糊PID和基于PSO算法优化的模糊PID这3种控制方法的性能；最后，通过搭建基于柔性力控法兰装置的打磨实验平台，对柔性力控法兰的恒力控制输出性能进行实验验证。仿真实验结果表明，与传统PID和模糊PID控制方法相比，基于PSO算法优化的模糊PID控制没有超调，系统响应速度更快，在0.43 s时系统达到稳定；在进行恒力打磨实验时，柔性力控法兰实际接触力输出误差小于0.85 N;打磨后的壳体表面各区域粗糙度稳定在Ra0.1～Ra0.2之间。该方法能够有效地抑制接触压力波动，具有更强的鲁棒性。

Fuzzy PID constant force control based on PSO optimization

For the requirements of contact force in the process of industrial robots such as polishing, a fuzzy PID constant force control method based on particle swarm (PSO) optimization is proposed. Firstly, the force and gas flow model of the flexible force-controlled flange are analyzed to establish the system model of the flexible force-controlled flange device; secondly, the fuzzy PID controller based on PSO algorithm is designed so that the control parameters of fuzzy PID can be adaptively adjusted, and the fuzzy PID control optimized based on PSO algorithm is compared with ordinary PID, fuzzy PID and PSO algorithm through MATLAB simulation; finally, the experimental verification of the constant force control output performance of the flexible force-controlled flange is carried out by building a LabVIEW-based grinding experiment platform. The simulation experiment results show that: Compared with the traditional PID and fuzzy PID control methods, the fuzzy PID control optimized based on PSO algorithm has no overshoot, the system response is faster, and the system reaches stability at 0.43 s; the actual contact force output error of the flexible force control flange is less than 0.85 N when the constant force grinding experiment is conducted; the roughness of each area of the shell surface after grinding is stable between Ra0.1~Ra0.2. The method can effectively suppress the contact pressure fluctuation and has stronger robust performance.