Neural network controller based on the rule of bang-bang control

Chung-Yong Tsai*, Chih Chi Chang

*Corresponding author for this work

研究成果: Paper同行評審

摘要

Applying neural networks or fuzzy systems to the field of optimal control encounters the difficulty of locating adequate samples that can be used to train the neural networks or modify the fuzzy rules such that the optimal control value for a given state can be produced. Instead of an exhaustive search, this work presents a simple method based on the rule of bang-bang control to locate the training samples for time optimal control. Although the samples obtained by the proposed method can be learned by multilayer perceptrons and radial basis networks, a neural network deemed appropriate for learning these samples is proposed as well. Simulation results demonstrate the effectiveness of the proposed method.

原文English
頁面2249-2252
頁數4
出版狀態Published - 1 十二月 1999
事件International Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
持續時間: 10 七月 199916 七月 1999

Conference

ConferenceInternational Joint Conference on Neural Networks (IJCNN'99)
城市Washington, DC, USA
期間10/07/9916/07/99

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