COSTA, Eduardo; DE SAPORTA, Benoîte

Métadonnées

Licence d’utilisation du document

COSTA, Eduardo
Instituto de Ciências Mathemàticas e de Computação [São Carlos] [ICMC-USP]

DE SAPORTA, Benoîte
Quality control and dynamic reliability [CQFD]
Institut Montpelliérain Alexander Grothendieck [IMAG]

Langue

Communication dans un congrès

Ce document a été publié dans

CT 2017 - SIAM Conference on Control and Its Applications, 2017-07-10, Pittsburgh. 2017

Résumé en anglais

Minimum mean square error estimation for linear systems with Markov jump parameters is addressed. The jump variable is assumed to be observed, however only cluster information is taken into account in the filter design, allowing one to seek for the best implementable estimator via the cardinality and choice of the clusters. With this new approach we introduce a set of filters that can be compared in terms of performance according to the refines of clusters of the Markov chain. Moreover, it includes as particular cases the well known Kalman filter with as many clusters as Markov states, as well as the linear Markovian estimator with only one cluster. The Riccati-like formulas for pre-computation of gains are given, and we explore the trade-off between complexity and performance via numerical examples.< Réduire

URI

https://oskar-bordeaux.fr/handle/20.500.12278/193635

Project ANR

Ergodicité, contrôle et statistique pour les PDMP - ANR-12-JS01-0006

Origine

Importé de hal

Unités de recherche

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251