Abstract
The paper considers the problem of determining optimal sensors locations so as to estimate unknown parameters in a class of distributed parameter systems when the measurement errors are correlated. Given a finite set of possible sensor positions, the problem is formulated as the selection of the gaged sites so as to maximize the log-determinant of the Fisher information matrix associated with the estimated parameters. The search for the optimal solution is performed using a GRASP method combined with a multipoint exchange algorithm. In order to alleviate the problem of excessive computational costs for large-scale problems, a parallel version of the GRASP solver is developed aimed at computations on a Linux cluster of PCs. The resulting numerical scheme is validated on a simulation example.
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Baranowski, P., Uciński, D. (2008). A Parallel Sensor Selection Technique for Identification of Distributed Parameter Systems Subject to Correlated Observations. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2007. Lecture Notes in Computer Science, vol 4967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68111-3_49
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DOI: https://doi.org/10.1007/978-3-540-68111-3_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68105-2
Online ISBN: 978-3-540-68111-3
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