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Optimal input for identification versus sensitivity reduction of systems with large parameter variations

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Abstract

In this article, we present an algorithm leading to an optimal controller gain for the automatic regulation of a linear system (closed-loop policy) and to an optimal auxiliary input. This is used for the purpose of either system identification, resulting in the maximum sensitivity measure and thus increased accuracy (Refs. 1–25), or system sensitivity reduction, resulting in the minimum sensitivity measure and thus reliable operation (Refs. 26–46). These results, which are robust in terms of parameter variations, are developed without constraints on the input functions.

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Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, University of Illinois at Chicago, Chicago, Illinois

    M. Eslami (Associate Professor)

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  1. M. Eslami
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Communicated by J. B. Cruz, Jr.

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Eslami, M. Optimal input for identification versus sensitivity reduction of systems with large parameter variations. J Optim Theory Appl 77, 591–612 (1993). https://doi.org/10.1007/BF00940452

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