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

Chung-Yong Tsai*, Chih Chi Chang

*Corresponding author for this work

Research output: Contribution to conferencePaper

Abstract

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.

Original languageEnglish
Pages2249-2252
Number of pages4
StatePublished - 1 Dec 1999
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: 10 Jul 199916 Jul 1999

Conference

ConferenceInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period10/07/9916/07/99

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  • Cite this

    Tsai, C-Y., & Chang, C. C. (1999). Neural network controller based on the rule of bang-bang control. 2249-2252. Paper presented at International Joint Conference on Neural Networks (IJCNN'99), Washington, DC, USA, .