計測自動制御学会論文集
Online ISSN : 1883-8189
Print ISSN : 0453-4654
ISSN-L : 0453-4654
論文
機械学習の枠組みに基づく能動型探索アルゴリズムのサーボパラメータ調整問題への適用性の検討
野田 哲男長野 陽永谷 達也堂前 幸康長野 鉄明田中 健一小笠原 司
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2017 年 53 巻 3 号 p. 217-228

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Optimization task of the control parameters of industrial positioning systems is a daily occurrence. It is necessary to explore unknown response landscape of the system by performing plural sampling of “control parameters and output combination” if the request specification is severe. Skilled operators have been conducting such tasks based on their experience and knowledge. The challenge is “The Optimization of Unknown Objective Function”. In their study, the authors have proposed their original optimization algorithm as a solution. This paper reports applicability study of their algorithm. Experimental results discovered that the algorithm found the optimal control parameter in 100 combination data set for seven times trial with some required specifications.

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© 2017 公益社団法人 計測自動制御学会
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