Some Optimal CUSUM Rule Extensions in Dynamic Model Parameter Change-Point Detection Problems System Identification

Nadine Hilgert 1 Ghislain Verdier 2 Jean-Pierre Vila 1
1 MISTEA - Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie
2 SFL-ENSMSE - Département Sciences de la Fabrication et Logistique
Abstract : This paper proposes three extensions of the usual CUSUM rule for change point detection in dynamic systems, in situations where the application of the rule is problematic. The first two ones concerns the case of nonlinear state-space systems indirectly observed and the case of uncertain systems. The third one improves the performance of the usual rule when applied to nonstationary systems, by ensuring a constant rate of false alarms. They all rely on kernel-based nonparametric estimation approaches.
Keywords : Fault Detection and Diagnosis Filtering and Smoothing
Type de document :
Communication dans un congrès
15th IFAC Symposium on System Identification, 2009 System Identification, Jul 2009, Saint-Malo, France. 15 (1), 2010, 〈10.3182/20090706-3-FR-2004.0116〉
Liste complète des métadonnées
https://hal-emse.ccsd.cnrs.fr/emse-00466787
Contributeur : Sabine Salmeron <>
Soumis le : mercredi 24 mars 2010 - 17:49:10
Dernière modification le : jeudi 22 octobre 2015 - 01:03:44

Identifiants

Collections

EMSE | CMP-ENSMSE | SFL-ENSMSE | INRA | AGROPOLIS

Citation

Nadine Hilgert, Ghislain Verdier, Jean-Pierre Vila. Some Optimal CUSUM Rule Extensions in Dynamic Model Parameter Change-Point Detection Problems System Identification. 15th IFAC Symposium on System Identification, 2009 System Identification, Jul 2009, Saint-Malo, France. 15 (1), 2010, 〈10.3182/20090706-3-FR-2004.0116〉. 〈emse-00466787〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

107

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD