Modeling and Control for Plant Dynamics Based on Reinforcement Learning
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概要
- 論文の詳細を見る
The dynamics modeling of a plant was developed by using Q-learning, which is one method of reinforcement learning. We thought the modeling of the dynamical system to be the function approximation problem for the system output response signal, and enhanced reinforcement learning to the modeling method of the dynamical system. We describe that this modeling method guarantee to offer highly accurate dynamics models by numerical samples, which deals with incinerators combustion. Results of numerical simulation show that the predictive control method using these models has robust tracking property.
- 社団法人 電気学会の論文
- 2009-04-01
著者
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Kitamura Akira
Department Of Molecular Cell Dynamics Faculty Of Advanced Life Science Hokkaido University
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Kitamura Akira
Department Of Anesthesia Nippon Medical School
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Kitamura Akira
Department Of Information And Knowledge Engineering Tottori University
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Maeda Tomoyuki
Production System Research Laboratory Kobe Steel Ltd.
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NAKAYAMA Makishi
Production System Research Laboratory, Kobe Steel, Ltd.
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NARAZAKI Hiroshi
Production System Research Laboratory, Kobe Steel, Ltd.
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Narazaki Hiroshi
Production System Research Laboratory Kobe Steel Ltd.
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Nakayama Makishi
Production System Research Laboratory Kobe Steel Ltd.
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