›› 2016, Vol. 29 ›› Issue (7): 43-.

• 论文 • 上一篇    下一篇

智能PID控制算法研究及Matlab实现

蔡淑敏1,王亚刚1,田涛2   

  1. (1上海理工大学 光电信息与计算机工程学院,上海 200093;2上海华虹集成电路有限责任公司,上海 201203)
  • 出版日期:2016-07-15 发布日期:2016-07-15
  • 作者简介:蔡淑敏(1993-),女,硕士研究生。研究方向:嵌入式芯片等。王亚刚(1967-),男,博士,硕士生导师。研究方向:工业过程控制等。田涛(1979-),男,教授级高工。研究方向:嵌入式。

Research on Intelligent PID Control Algorithm and Matlab Simulation

CAI Shumin1, WANG Yagang1, TIAN Tao2   

  1. (1School of opticalElectrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China; 2Shanghai Huahong Integrated Circuit Co. Ltd., Shanghai 201203, China)
  • Online:2016-07-15 Published:2016-07-15

摘要:

针对滞后大、非线性等复杂的系统,常规PID控制算法已无法满足控制任务要求。为解决此类问题,文中提出从智能PID控制中的模糊PID控制、BP神经网络PID控制着手,仿真比较智能PID控制与常规PID控制的控制结果。实验表明,智能PID控制的超调量可达到0,稳定时间也大幅缩短,使系统整体的动静态特性得到了有效地改善。

关键词: PID控制, 智能控制, 模糊控制, 神经网络, Matlab仿真

Abstract:

With the rapid development of modern industry, the conventional PID control algorithm can not meet the requirements of the control task. In order to solve these problems, the fuzzy PID control and BP neural network PID control are included in intelligent PID control for simulation and comparison of the control results of the intelligent PID control and conventional PID control. The experiments show that the overshoot of the intelligent PID control can reach 0 with the stability time greatly shortened and the dynamic and static characteristics of the system improved.

Key words: PID control, intelligence control, fuzzy control, neural network, Matlab simulation

中图分类号: 

  • TP273+.5