On-line tuning PID parameters in idle-speed engine based on modified BP neural network by particle swarm optimization

Jia Meng Yin, Ji Sun Shin, Hee Hyol Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

PID control systems are widely used in many fields, and many methods to tune parameters of PID controller are known. When the characteristics of the object are changed, the traditional PID control should be adjusted by empirical knowledge. It may bring a worse performance to the system. In this paper, a new method to tune PID parameters called as the modified back propagate network by Particle swarm optimization is proposed. This algorithm combines the conventional PID control with the back propagate neural network (BPNN) and the particle swarm optimization (PSO). This method is demonstrated in the engine idle-speed control problem; the proposed method provides prominent performance benefits over the traditional controller in this simulation.

Original languageEnglish
Title of host publicationProceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09
Pages50-54
Number of pages5
Publication statusPublished - 2009 Dec 1
Event14th International Symposium on Artificial Life and Robotics, AROB 14th'09 - Oita, Japan
Duration: 2008 Feb 52009 Feb 7

Publication series

NameProceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09

Conference

Conference14th International Symposium on Artificial Life and Robotics, AROB 14th'09
CountryJapan
CityOita
Period08/2/509/2/7

Keywords

  • BP neural network
  • Engine idle-speed control
  • PID control
  • Particle swarm optimization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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  • Cite this

    Yin, J. M., Shin, J. S., & Lee, H. H. (2009). On-line tuning PID parameters in idle-speed engine based on modified BP neural network by particle swarm optimization. In Proceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09 (pp. 50-54). (Proceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09).