Enhanced Auto-Tuning of Feedback Controllers with Aggressive Search Ensuring Stability and Its Application to Galvano Scanner
Enhanced Auto-Tuning of Feedback Controllers with Aggressive Search Ensuring Stability and Its Application to Galvano Scanner
カテゴリ: 論文誌(論文単位)
グループ名: 【D】産業応用部門(英文)
発行日: 2024/09/01
タイトル(英語): Enhanced Auto-Tuning of Feedback Controllers with Aggressive Search Ensuring Stability and Its Application to Galvano Scanner
著者名: Takuya Shiohara (Electrical and Mechanical Engineering Program, Department of Engineering, Nagoya Institute of Technology), Yoshihiro Maeda (Electrical and Mechanical Engineering Program, Department of Engineering, Nagoya Institute of Technology)
著者名(英語): Takuya Shiohara (Electrical and Mechanical Engineering Program, Department of Engineering, Nagoya Institute of Technology), Yoshihiro Maeda (Electrical and Mechanical Engineering Program, Department of Engineering, Nagoya Institute of Technology)
キーワード: auto-tuning,feedback controller,stability,parameter search space,galvano scanner,genetic algorithm
要約(英語): This paper presents a practical and high-performance auto-tuning method for feedback controllers in industrial servo systems aimed at achieving fast and precise positioning. Conventional auto-tuning approaches generally limit control performance by avoiding an aggressive parameter search for fear of instability of the feedback control system during auto-tuning. To overcome this issue, the proposed method employs a stable parameter search space that ensures specified stability margins and searches for optimal parameters within this space. The proposed method is established by combining it with a genetic algorithm-based parameter search as an example global optimization-based auto-tuning method, and is adopted for fast and precise positioning control of a galvano scanner. The results of auto-tuning experiments demonstrate the effectiveness of the proposed method compared to a conventional auto-tuning method that does not consider a stable parameter space.
本誌: IEEJ Journal of Industry Applications Vol.13 No.5 (2024)
本誌掲載ページ: 539-546 p
原稿種別: 論文/英語
電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejjia/13/5/13_23013778/_article/-char/ja/
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