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On Extension of a Gradient-Based Co-Design Algorithm to Linear Descriptor Systems

Wang, Yebin and Wang, Yuh-Shyang and Bortoff, Scott A. (2016) On Extension of a Gradient-Based Co-Design Algorithm to Linear Descriptor Systems. In: Intelligent Control and Automation (WCICA), 2016. IEEE , Piscataway, NJ, pp. 2388-2393. ISBN 978-1-4673-8414-8. http://resolver.caltech.edu/CaltechAUTHORS:20161007-112103787

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Abstract

As a holistic approach, optimal co-design of a control system determines both the plant and controller simultaneously to optimize certain performance metrics. Prior co-design work typically assume a control system in the classic state space form, and thus compromise the range of applicability. This paper considers co-design for control systems in the linear descriptor form, with the purpose to minimize the H2 norm of a closed-loop transfer function. We demonstrate that the gradient of the cost function with respect to plant parameters can be computed analytically, and thus extend the previous gradient-based co-design algorithm to the linear descriptor system case.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1109/WCICA.2016.7578834DOIArticle
http://ieeexplore.ieee.org/document/7578834/PublisherArticle
ORCID:
AuthorORCID
Wang, Yuh-Shyang0000-0001-7357-7247
Additional Information:© 2016 IEEE. Date Added to IEEE Xplore: 29 September 2016.
Record Number:CaltechAUTHORS:20161007-112103787
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20161007-112103787
Official Citation:Y. Wang, Y. S. Wang and S. A. Bortoff, "On extension of a gradient-based co-design algorithm to linear descriptor systems," 2016 12th World Congress on Intelligent Control and Automation (WCICA), Guilin, China, 2016, pp. 2388-2393. doi: 10.1109/WCICA.2016.7578834
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:70953
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:12 Oct 2016 22:14
Last Modified:03 Nov 2017 22:57

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