Parameter Adjustment Based on Genetic Algorithm for Adaptive Periodic-Disturbance Observer

Xiao Feng, Hisayoshi Muramatsu, Seiichiro Katsura

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Periodic disturbances occur during repetitive operation of machines in industrial production. Compensation for the periodic disturbances is an important issue to realize proper machine works beacause the periodic disturbances deteriorate machining precision. In order to eliminate the periodic disturbances, an adaptive periodic-disturbance observer (APDOB) has been proposed as an effective method that can also estimate and compensate for frequency-varying periodic disturbances. However, the APDOB has a problem that design of the APDOB is complicated owing to its six design parameters, which need to be empirically adjusted. Here, we propose an approach based on a genetic algorithm (GA) including a Lévy flight to automatically adjust the six design parameters. The proposed method can remove the conventional empirical design. Moreover, the Lévy flight could improve the exploration ability of the GA by optimizing mutation operator and the best solution found by the GA including Lévy flight could improve the performance of the APDOB.

本文言語English
ホスト出版物のタイトルProceedings
ホスト出版物のサブタイトルIECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
出版社IEEE Computer Society
ページ687-692
ページ数6
ISBN(電子版)9781728148786
DOI
出版ステータスPublished - 2019 10月
イベント45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 - Lisbon, Portugal
継続期間: 2019 10月 142019 10月 17

出版物シリーズ

名前IECON Proceedings (Industrial Electronics Conference)
2019-October

Conference

Conference45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019
国/地域Portugal
CityLisbon
Period19/10/1419/10/17

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 電子工学および電気工学

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