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

*この研究の対応する著者

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09
ページ50-54
ページ数5
出版ステータスPublished - 2009 12月 1
イベント14th International Symposium on Artificial Life and Robotics, AROB 14th'09 - Oita, Japan
継続期間: 2008 2月 52009 2月 7

出版物シリーズ

名前Proceedings 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
国/地域Japan
CityOita
Period08/2/509/2/7

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ビジョンおよびパターン認識
  • 人間とコンピュータの相互作用

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