Constrained Optimal Control of Bilinear Systems Using Neural Network Based HJB Solution

Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/11609

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DC Field	Value	Language
dc.contributor.author	Adhyaru, D. M.
dc.contributor.author	Kar, I. N.
dc.contributor.author	Gopal, M.
dc.date.accessioned	2023-04-20T11:06:11Z	-
dc.date.available	2023-04-20T11:06:11Z	-
dc.date.issued	2008-06-08
dc.identifier.citation	IEEE International Joint Conference on Neural Networks, (IJCNN 2008, IEEE World Congress on Computational Intelligence) Hong Kong , June 8, 2008, Page No. 4137-4142	en
dc.identifier.issn	1098-7576
dc.identifier.uri	http://10.1.7.192:80/jspui/handle/123456789/11609	-
dc.description.abstract	In this paper, a Hamilton-Jacobi-Bellman (HJB) equation based optimal control algorithm is proposed for a bilinear system, Utilizing the Lyapunov direct method, the controller is shown to be optimal with respect to a cost functional, Which includes penalty on the control effort and the system states. In the proposed algorithm, Nueral Network (NN) is used to find approximate solution of HJB equation using least square method. Proposed algorithm has been applied on bilinear systems. Necessary theoretical and simulation result are presented to validate proposed algorithm.	en
dc.publisher	IEEE	en
dc.relation.ispartofseries	ITFIC002-8	en
dc.subject	IC Faculty Paper	en
dc.subject	Faculty Paper	en
dc.subject	ITFIC002	en
dc.title	Constrained Optimal Control of Bilinear Systems Using Neural Network Based HJB Solution	en
dc.type	Faculty Papers	en
Appears in Collections:	Faculty Papers, E&I

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