E-FRITに基づくニューロPID制御器の設計

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: 2018/05/01

タイトル(英語): Design of Neural Network PID Controller based on E-FRIT

著者名: 木下　健人（広島大学大学院工学研究科），脇谷　伸（広島大学大学院工学研究科），大野　修一（広島大学大学院工学研究科）

著者名(英語): Kento Kinoshita (Graduate School of Engineering, Hiroshima University), Shin Wakitani (Graduate School of Engineering, Hiroshima University), Shuichi Ohno (Graduate School of Engineering, Hiroshima University)

キーワード: PID制御，データ駆動型制御，E-FRIT，ニューラルネットワーク，プロセス制御，非線形システム　　PID control，data-driven control，E-FRIT，neural network，process control，nonlinear systems

要約(英語): PID controllers have been widely used for process systems. However, a good control result is not always obtained with fixed PID gains when a controlled object has nonlinearity. This paper proposes a design method for a nonlinear PID controller that utilizes a neural network to overcome the problem. In the proposed controller, PID gains are tuned online by a neural network and a controlled object is manipulated by the PID controller with the tuned PID gains. The neural network is learned by an offline learning algorithm based on the Extended Fictitious Reference Iterative Tuning (E-FRIT) and the backpropagation. E-FRIT is a method that tunes control parameters directly by using operating data and evaluates not only a controlled output but also the difference of manipulated variable. Simulation examples are provided to show the effectiveness of the proposed method. Moreover, the experimental result of a level control of a tank system is also given to demonstrate the performance of the proposed method.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.138 No.5 （2018） 特集：データの計測・解析と制御技術への応用

本誌掲載ページ: 512-519 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/138/5/138_512/_article/-char/ja/