Probabilistically-robust performance optimization for controlled linear stochastic systems

This study discusses a robust controller synthesis methodology for linear time invariant systems characterized by probabilistic parameter uncertainty. The optimization of the robust performance is considered. The extension of pre-existing, synthesis approaches, such as multi-objective H 2 design, to...

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Bibliographic Details
Published in2009 American Control Conference pp. 4557 - 4562
Main Authors Taflanidis, A.A., Scruggs, J.T.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2009
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Summary:This study discusses a robust controller synthesis methodology for linear time invariant systems characterized by probabilistic parameter uncertainty. The optimization of the robust performance is considered. The extension of pre-existing, synthesis approaches, such as multi-objective H 2 design, to account for probabilistic uncertainty is investigated. A design based on the concept of the reliability of the system response output is also considered. Analysis and synthesis methodologies based on stochastic simulation techniques are discussed. The design approach is applied in a structural control example. The results illustrate the differences between the various probabilistic performance objectives and the importance of adopting a probabilistic characterization for model uncertainty when compared to nominal design or to the design using a worst-case scenario approach.
ISBN:142444523X
9781424445233
ISSN:0743-1619
2378-5861
DOI:10.1109/ACC.2009.5160249