Inteligent control system taking account of system evaluation using weighted observational and explicit information

Masaki Takahashi, Keiyo Hatano, Naoko Hatano, Kazuo Yoshida

Research output: Contribution to journalArticle

Abstract

This study considers an intelligent control system to integrate flexibly its components by using weighted information where the system evaluation is reflected. Such system evaluates the information flowing through the components and converts them by weighting depending on the degree of importance. Integration of components based on the system evaluation enables a system consisting of them to realize various, flexible and adaptive control. In this study, the intelligent control method is applied to a swing up and stabilization control problem of a number of cart and pendulum systems on a restricted straight guide. To stabilize the pendulum in a restricted environment, each system should realize not only a swing-up and stabilization control of the pendulum, but also a position control of the cart to avoid collision or deadlock. The experiment using a real apparatus demonstrated that the controller learning light interaction acquires egoistic character, the controller learning heavy interaction behaves altruistically, and the controller equally considering self cart and another cart becomes cooperative. In other words, these autonomous decentralized controllers can acquire various characters and flexibility for cooperation.

Original languageEnglish
Pages (from-to)1085-1092
Number of pages8
JournalNippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
Volume70
Issue number4
Publication statusPublished - 2004 Apr

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Pendulums
Control systems
Controllers
Intelligent control
Stabilization
Position control
Experiments

Keywords

  • Autonomous Decentralized System
  • Cooperativeness
  • Intelligent Control System
  • Inverted Pendulum

ASJC Scopus subject areas

  • Mechanical Engineering

Cite this

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abstract = "This study considers an intelligent control system to integrate flexibly its components by using weighted information where the system evaluation is reflected. Such system evaluates the information flowing through the components and converts them by weighting depending on the degree of importance. Integration of components based on the system evaluation enables a system consisting of them to realize various, flexible and adaptive control. In this study, the intelligent control method is applied to a swing up and stabilization control problem of a number of cart and pendulum systems on a restricted straight guide. To stabilize the pendulum in a restricted environment, each system should realize not only a swing-up and stabilization control of the pendulum, but also a position control of the cart to avoid collision or deadlock. The experiment using a real apparatus demonstrated that the controller learning light interaction acquires egoistic character, the controller learning heavy interaction behaves altruistically, and the controller equally considering self cart and another cart becomes cooperative. In other words, these autonomous decentralized controllers can acquire various characters and flexibility for cooperation.",
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N2 - This study considers an intelligent control system to integrate flexibly its components by using weighted information where the system evaluation is reflected. Such system evaluates the information flowing through the components and converts them by weighting depending on the degree of importance. Integration of components based on the system evaluation enables a system consisting of them to realize various, flexible and adaptive control. In this study, the intelligent control method is applied to a swing up and stabilization control problem of a number of cart and pendulum systems on a restricted straight guide. To stabilize the pendulum in a restricted environment, each system should realize not only a swing-up and stabilization control of the pendulum, but also a position control of the cart to avoid collision or deadlock. The experiment using a real apparatus demonstrated that the controller learning light interaction acquires egoistic character, the controller learning heavy interaction behaves altruistically, and the controller equally considering self cart and another cart becomes cooperative. In other words, these autonomous decentralized controllers can acquire various characters and flexibility for cooperation.

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