Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (34): 221-224.

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Research and application of particle swarm optimization in parameter tuning on PID controller

TANG Yulan1, XU Mingliang1, MEI Juan1,2, CHEN Jianhui3   

  1. 1.Department of Electronics and Information Engineering, Wuxi City College, Wuxi, Jiangsu 214151, China
    2.College of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
    3.College of Electronics and Information Technology, Wuxi Institute of Technology, Wuxi, Jiangsu 214121, China
  • Online:2012-12-01 Published:2012-11-30

粒子群算法在PID控制器参数整定中的研究与应用

唐玉兰1,徐明亮1,梅  娟1,2,陈建慧3   

  1. 1.无锡城市学院 电子信息工程系,江苏 无锡 214151
    2.江南大学 物联网工程学院,江苏 无锡 214122
    3.无锡职业技术学院 电子与信息技术学院,江苏 无锡 214121

Abstract: A design method of PID controller based on particle swarm algorithm is proposed to solve the difficult problems of parameter tuning on PID controller in automatic control system. And the specific experimental structure is also given. The transfer function of DC servo generator is found with identification of system parameters, and the PID parameters are searched by particle swarm algorithm. MATLAB simulation is used to demonstrate the feasibility and advantages of this approach. The simulation result is compared to the result of searching PID parameters based on genetic algorithm, and it is show that the seeking time to tune the PID parameters by using the particle swarm algorithm is faster than by using the genetic algorithm method.

Key words: genetic algorithm, PID control, parameters tuning, particle swarm algorithm

摘要: 针对自动化控制系统中PID控制器参数整定困难的问题,提出了基于粒子群算法的PID控制器的设计方法,给出了具体的实验架构。采用系统参数鉴定的方式得到直流伺服发电机的传递函数,并利用粒子群算法搜寻PID参数。实验采用MATLAB仿真证明了该方法的可行性和优越性。所得到模拟结果跟遗传算法搜索PID参数的结果做比较,结果显示用粒子群算法调整PID参数所得到的运算时间比用遗传算法的运算时间要短。

关键词: 遗传算法, PID控制, 参数整定, 粒子群算法