セルフチューニング一般化最小分散制御系に対する強安定率を用いた安全性の評価

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2014/09/01

タイトル(英語): Safety Assessment of Self-tuning Generalized Minimum Variance Control by Strong Stability Rate

著者名: 矢納　陽（岡山大学大学院自然科学研究科），見浪　護（岡山大学大学院自然科学研究科），松野　隆幸（岡山大学大学院自然科学研究科）

著者名(英語): Akira Yanou (Graduate School of Natural Science and Technology, Okayama University), Mamoru Minami (Graduate School of Natural Science and Technology, Okayama University), Takayuki Matsuno (Graduate School of Natural Science and Technology, Okayama University)

キーワード: 強安定率，既約分解，閉ループ特性，一般化最小分散制御，セルフチューニングコントローラ　　strong stability rate，coprime factorization，closed-loop characteristic，generalized minimum variance control，self-tuning controller

要約(英語): This paper explores safety assessment of self-tuning generalized minimum variance control (GMVC) system by strong stability rate. Strong stability rate is one of the concepts of plant safety and is derived by using coprime factorization approach. Its value is defined by open-loop gain of controlled system through Youla-Kucera parametrization. GMVC is extended by using coprime factorization in this paper. Moreover the extended GMVC is designed so as to make the open-loop gain be closer to the closed-loop gain by new design parameter. In the case that the open-loop gain is closer to the closed-loop one, strong stability rate assesses that the controlled system maintains higher safety in the meaning that the open-loop output will be closer to the closed-loop output even if the feedback signal becomes zero by accident. In this paper numerical example for the self-tuning controller is given in order to verify the validity of the proposed assessment.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.134 No.9 （2014） 特集Ⅰ：制御系設計における適応・学習・同定・モデリングの新展開　特集Ⅱ：インテリジェント・システム

本誌掲載ページ: 1241-1246 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/134/9/134_1241/_article/-char/ja/