基于粒子群模糊PID控制的自整角机伺服系统  

Servo Systems for Self-adjusting Angle Machines Based on PSO Fuzzy PID Control

作　　者：刘祎玮 唐路平 李清源 郭迎庆[1] 杨蓉 LIU Yi-wei;TANG Lu-ping;LI Qing-yuan;GUO Ying-qing;YANG Rong(School of Mechanical and Electronic Engineering,Nanjing Forestry University,Jiangsu Nanjing 210000,China)

机构地区：[1]南京林业大学机械电子工程学院,江苏南京210000

出　　处：《林业机械与木工设备》2022年第8期28-32,共5页Forestry Machinery & Woodworking Equipment

基　　金：国家自然科学基金项目(52001168);大学生创新训练计划项目(202110298065Y)。

摘　　要：针对自整角机伺服系统的控制问题,提出将粒子群优化算法应用于模糊控制当中,以改良伺服系统的控制性能。系统将粒子群优化得到的比例因子与量化因子送入模糊控制中的模糊化与反模糊化环节动态调节控制系统的权重因子,再由控制系统调节自整角机的伺服系统。在Matlab/Simulink环境中进行系统的仿真实验测试,试验结果表明:粒子群模糊PID控制系统的超调量仅有3.4%,调节时间为3.945 s。在针对自整角机伺服系统的实验中粒子群模糊PID控制器展现了良好的动态性能,收敛速度快,控制精度高,适应性更强,抗干扰能力强,且在角度跟踪问题上具有良好的跟踪特性,对实际的自整角机伺服系统设计具有参考意义。Aiming at the control problem of servo systemsfor self-adjustingangle machines, a solution was proposed by combining particle swarm optimization algorithm with fuzzy control.The scale factor and quantization factor were obtained through particle swarm optimization, and then the weight factor was dynamically adjusted by fuzzy and anti-fuzzy processing in fuzzy control, then the control system adjusted the servo system of the self-adjusting angle machine.The system simulation and anti-interference experiment were carried out in Matlab/Simulink environment.The experimental results show that the overshoot of PSO fuzzy PID control system was only 3.4%,and the adjusting time was 3.945s.The PSO fuzzy PID controller showed good dynamic performance, fast convergence speed, high control precision, strong adaptability, strong anti-interference ability, and had good tracking characteristics in angle tracking problem, which has reference significance for the actual design of servo systems for self-adjusting angle machines.

关 键 词：RBF神经网络 模糊控制 粒子群优化控制 自整角机 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]