中国民航大学学报

• 工程技术 • 上一篇    下一篇

基于模糊自适应PID的智能车设计与实现

丁芳a,王蕊a,刘游龙a,林建伟b   

  1. (中国民航大学a.航空自动化学院;b.计算机科学与技术学院,天津300300)
  • 收稿日期:2013-10-18 修回日期:2013-11-22 出版日期:2014-12-25 发布日期:2014-12-05
  • 作者简介:丁芳(1960—),女,山西太原人,副教授,硕士,研究方向为检测技术和智能控制.
  • 基金资助:

    天津市自然基金项目(13JCYBJC39000);国家级大学生创新创业训练计划项目(201210059038)

Fuzzy adaptive PID design and implementation of intelligent car

DING Fanga,WANG Ruia,LIU You-longa,LIN Jian-weib   

  1. (a. College of Aeronautical Automation,b.College of Computer Science & Technology,CAUC,Tianjin 300300,China)
  • Received:2013-10-18 Revised:2013-11-22 Online:2014-12-25 Published:2014-12-05

摘要:

在智能车控制过程中,由于方向控制与速度控制都是非线性的、时变的,采用传统的PID算法进行控制效果不理想。模糊自适应PID算法能够在线修改参数,从而使智能车能够根据路况的变化做出适当的控制决策。该模糊自适应PID 算法,通过Simulink 在Freescale单片机MK60DN512ZVLQ10环境中编程实现,并与传统的PID算法的控制结果相比较。仿真和实验结果表明模糊自适应PID 控制器具有超调量小,响应快,适应能力强的优点。

关键词: 模糊控制, PID 控制, 智能车, Simulink

Abstract:

As directional control and speed control are nonlinear and time-varying during intelligent car controlling process,it's not ideal to use traditional PID algorithm. With online parameter modifying ability,fuzzy adaptive PID algorithm helps smart cars make appropriate controlling decisions according to road conditions. Fuzzy adaptive PID algorithm is achieved by Simulink in Freescale microcontroller (MK60DN512ZVLQ10)programming environment,and is compared with traditional PID control algorithm. Simulation and experimental results show that fuzzy adaptive PID controller has smaller overshoot, faster response and stronger adaptability.

Key words: fuzzy control, PID control, intelligent car, simulink

中图分类号: