Stabilization of an inverted pendulum by a layered neural network

Minoru Sekiguchi, Tamami Sugasaka, Ryo Kurazume

研究成果: Contribution to journalArticle査読

1 被引用数 (Scopus)

抄録

This paper discusses the stabilization of an inverted pendulum by a neural network. The inverted pendulum is a typical example of an unstable and nonlinear system. Fujitsu has developed a self-learning method that enables a neural network to control an inverted pendulum by using heuristic rules. A system based on this method has been developed which generates teaching data for inversion by trial and error. Then, the neural network learns the teaching data, and acquires the control rules after a period of trial and error. The method proved its effectiveness by stably inverting a pendulum in an experimental inverted pendulum system after a period of trial and error.

本文言語英語
ページ(範囲)278-285
ページ数8
ジャーナルFujitsu Scientific and Technical Journal
29
3
出版ステータス出版済み - 9 1993
外部発表はい

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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