Learning type PID control system using input dependence reinforcement scheme

Hideharu Sawada, Ji Sun Shin, Fumihiro Shoji, Hee Hyol Lee

研究成果: Conference contribution

抄録

PID control has widely used in the field of process control and a lot of methods have been used to design PID parameters. When the characteristic values of a controlled object are changed due to a change over the years or disturbance, the skilled operators observe the feature of the controlled responses and adjust the PID parameters using their knowledge and know-how, and a lot of labors are required to do it. In this research, we design a learning type PID control system using the stochastic automaton with learning function, namely learning automaton, which can autonomously adjust the control parameters updating the state transition probability using relative amount of controlled error. We show the effectiveness of the proposed learning type PID control system by simulations.

本文言語English
ホスト出版物のタイトルProceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08
ページ389-392
ページ数4
出版ステータスPublished - 2008
イベント13th International Symposium on Artificial Life and Robotics, AROB 13th'08 - Oita, Japan
継続期間: 2008 1 312008 2 2

出版物シリーズ

名前Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08

Conference

Conference13th International Symposium on Artificial Life and Robotics, AROB 13th'08
CountryJapan
CityOita
Period08/1/3108/2/2

ASJC Scopus subject areas

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

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