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Communication Dans Un Congrès Année : 2012

Robust automatic tuning of diagnosis methods via an efficient use of costly simulations

Résumé

The robust tuning methodology developed in this paper aims at adjusting automatically the hyperparameters of fault-diagnosis procedures for complex case studies. The strategy should make an efficient use of computer simulations of these case studies, which will usually be computationally expensive. To this end, Kriging-based optimization is called upon. Robustness to environmental disturbances is achieved by continuous minimax optimization, and handled through an iterative relaxation procedure. This strategy is applied to the automatic tuning of a model-based fault-diagnosis scheme for a realistic aerospace application.
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Dates et versions

hal-00680764 , version 1 (20-03-2012)

Identifiants

  • HAL Id : hal-00680764 , version 1

Citer

Julien Marzat, Eric Walter, Frédéric Damongeot, Hélène Piet-Lahanier. Robust automatic tuning of diagnosis methods via an efficient use of costly simulations. 16th IFAC Symposium on System Identification, Jul 2012, Bruxelles, Belgium. pp.398-403. ⟨hal-00680764⟩
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