Learning Control of a Closed Loop System Using Feedback-Error-Learning

• GOMI Hiroaki

  ATR Auditory and Visual Perception Lab.

• KAWATO Mitsuo

  ATR Auditory and Visual Perception Lab.

Bibliographic Information

Other Title

• フィードバック誤差学習による閉ループシステムの学習制御
• フィードバック ゴサ ガクシュウ ニ ヨル ヘイ ループ システム ノ ガクシ

Abstract

In this paper, we propose a new learning scheme using feedback-error-learning for a Neural network model applied to an adaptive Nonlinear Feedback Controller (NNFC). This system uses a Conventional Feedback Controller (CFC) both as a usual feedback controller to guarantee global asymptotic stability and as a reference model of the response. The output of the conventional feedback controller is used as the error signal for a neural network model for adaptive nonlinear feedback control. The response of the controlled object follows the response of the reference model after the learning period.<BR>The convergence properties of this learning scheme are provided by using the averaged equation and the Liapunov method. This scheme was successfully applied to the control of an inverted pendulum by computer simulation. We also pointed out the relationship of this learning scheme to the cerebellum's posture and locomotion adaptive control mechanism in animals.

Journal

• Transactions of the Institute of Systems, Control and Information Engineers

  Transactions of the Institute of Systems, Control and Information Engineers 4 (1), 37-47, 1991

  THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

Keywords

• neural network
• adaptive cotrol
• learning
• inverted pendulum
• animal
• motor cotrol

Details

• CRID: 1390282680142678400
• NII Article ID: 130002036198
• NII Book ID: AN1013280X
• DOI: 10.5687/iscie.4.37
• ISSN: 2185811X
• ISSN: 13425668
• NDL BIB ID: 3699333
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I3699333
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed