American Journal of Computational Mathematics

Volume 3, Issue 2 (June 2013)

ISSN Print: 2161-1203   ISSN Online: 2161-1211

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Eigenvector Sensitivity: A Kharitonov Result

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DOI: 10.4236/ajcm.2013.32024    5,462 Downloads   8,262 Views  


This study is motivated by a need to effectively determine the difference between a system fault and normal system operation under parametric uncertainty using eigenstructure analysis. This involves computational robustness of eigenvectors in linear state space systems dependent upon uncertain parameters. The work involves the development of practical algorithms which provide for computable robustness measures on the achievable set of eigenvectors associated with certain state space matrix constructions. To make connections to a class of systems for which eigenvalue and characteristic root robustness are well understood, the work begins by focusing on companion form matrices associated with a polynomial whose coefficients lie in specified intervals. The work uses an extension of the well known theories of Kharitonov that provides computational efficient tests for containment of the roots of the polynomial (and eigenvalues of the companion matrices) in desirable regions, such as the left half of the complex plane.

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V. Winstead, "Eigenvector Sensitivity: A Kharitonov Result," American Journal of Computational Mathematics, Vol. 3 No. 2, 2013, pp. 158-168. doi: 10.4236/ajcm.2013.32024.

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