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

Nadine Hilgert; Ghislain Verdier; Jean-Pierre Vila

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

Document type :

Conference papers

Complete list of metadatas

https://hal-emse.ccsd.cnrs.fr/emse-00466787
Contributor : Sabine Salmeron <>
Submitted on : Wednesday, March 24, 2010 - 5:49:10 PM
Last modification on : Tuesday, March 5, 2019 - 9:12:01 AM

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

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

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