Neurodynamics-based robust eigenstructure assignment for second-order descriptor systems

Le, X; Yan, Z; Wang, J

Neurodynamics-based robust eigenstructure assignment for second-order descriptor systems

Le, X Yan, Z

Wang, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Joint Conference on Neural Networks, 2014, pp. 2770 - 2775
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Le, X	en_US
dc.contributor.author	Yan, Z https://orcid.org/0000-0003-3368-2100	en_US
dc.contributor.author	Wang, J	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Proceedings of the International Joint Conference on Neural Networks, 2014, pp. 2770 - 2775	en_US
dc.identifier.isbn	9781479914845	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121306
dc.description.abstract	© 2014 IEEE. In this paper, a neurodynamic optimization approach is proposed for robust eigenstructure assignment problem of second-order descriptor systems via state feedback control. With a novel robustness measure serving as the objective function, the robust eigenstructure assignment problem is formulated as a pseudoconvex optimization problem. Two coupled recurrent neural networks are applied for solving the optimization problem with guaranteed optimality and exact pole assignment. Simulation results are included to substantiate the effectiveness of the proposed approach.	en_US
dc.relation.ispartof	Proceedings of the International Joint Conference on Neural Networks	en_US
dc.relation.isbasedon	10.1109/IJCNN.2014.6889414	en_US
dc.title	Neurodynamics-based robust eigenstructure assignment for second-order descriptor systems	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. In this paper, a neurodynamic optimization approach is proposed for robust eigenstructure assignment problem of second-order descriptor systems via state feedback control. With a novel robustness measure serving as the objective function, the robust eigenstructure assignment problem is formulated as a pseudoconvex optimization problem. Two coupled recurrent neural networks are applied for solving the optimization problem with guaranteed optimality and exact pole assignment. Simulation results are included to substantiate the effectiveness of the proposed approach.

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http://hdl.handle.net/10453/121306