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Probabilistic μ-analysis for system performances assessment

Falcoz, Alexandre and Alazard, Daniel and Pittet, Christelle Probabilistic μ-analysis for system performances assessment. (2017) In: IFAC World Congress 2017, 9 July 2017 - 14 July 2017 (Toulouse, France).

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Official URL: http://dx.doi.org/10.1016/j.ifacol.2017.08.181

Abstract

Hinfinity/μ methods are commonly used in Airbus Defence and Space for the design and validation of control solutions. Formulated in a worst-case paradigm, these methods necessarily lead to overly conservative solutions since sized on the extreme cases. However, the acceptance for relaxed control performances requires mastering the risk associated to the detected unlikely events calling for probabilistic performances metrics in the validation process. A probabilistic μ-analysis method is presented in this paper to exhaustively explore the uncertain parametric domain while evaluating the cumulative probability density function of the performance index. Recent μ-analysis tools implemented in the ONERA’s SMAC toolbox are coupled with a dichotomic search algorithm in order to delimit the safe parametric domain while incrementing the probability of success of criteria. The proposed algorithm is applied to a didactic second order system to demonstrate the performances of the method.

Item Type:Conference or Workshop Item (Paper)
Additional Information:vol. 50, n° 1
HAL Id:hal-01738121
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Other partners > Airbus (FRANCE)
French research institutions > Centre National d'Études Spatiales - CNES (FRANCE)
Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
Laboratory name:
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Deposited By: Daniel Alazard
Deposited On:20 Mar 2018 10:24

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