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Reducing uncertain systems and behaviors

Beck, Carolyn and Doyle, John (1996) Reducing uncertain systems and behaviors. In: Proceedings of 35th IEEE Conference on Decision and Control. Vol.1. IEEE , Piscataway, NJ, pp. 712-714. ISBN 0-7803-3590-2.

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This paper considers the problem of reducing the dimension of a model for an uncertain system whilst bounding the resulting error. Model reduction methods with guaranteed upper error bounds have previously been established for uncertain systems described by a state-space type realization; specifically, by a linear fractional transformation (LFT) of a constant realization matrix over a structured uncertainty operator. In contrast to traditional 1-D model reduction where upper bounds on reduction are matched with comparable lower bounds, in the uncertain system problem there have previously been no lower bounds established. The computation of both upper and lower bounds is discussed in this paper, including a discussion of the use of Hankel-like matrices. These model reduction methods and error bound computations are then discussed in the context of kernel representations of behavioral uncertain systems.

Item Type:Book Section
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Doyle, John0000-0002-1828-2486
Additional Information:© 1996 IEEE. The first author would like to thank Lennart Andersson for sharing in numerous discussions related to the topics in this paper.
Record Number:CaltechAUTHORS:20190315-144945947
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Official Citation:C. Beck and J. Doyle, "Reducing uncertain systems and behaviors," Proceedings of 35th IEEE Conference on Decision and Control, Kobe, Japan, 1996, pp. 712-714 vol.1. doi: 10.1109/CDC.1996.574435
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:93893
Deposited By: Tony Diaz
Deposited On:15 Mar 2019 21:56
Last Modified:16 Nov 2021 17:01

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