COSTA, Eduardo; DE SAPORTA, Benoîte

doi:10.1109/TAC.2017.2692180

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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]

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Article de revue

Ce document a été publié dans

IEEE Transactions on Automatic Control. 2017, vol. 62, n° 7, p. 3567-3572

Institute of Electrical and Electronics Engineers

Résumé en anglais

New linear minimum mean square estimators are introduced in this paper by considering a cluster information structure in the filter design. The set of filters constructed in this way can be ordered in a lattice according to the refines of clusters of the Markov chain, including the linear Markovian estimator at one end (with only one cluster) and the Kalman filter at the other hand (with as many clusters as Markov states). The higher is the number of clusters, the heavier are pre-compuations and smaller is the estimation error, so that the cluster cardinality allows for a trade-off between performance and computational burden. In this paper we propose the estimator, give the formulas for pre-computation of gains, present some properties, and give an illustrative numerical example.< Réduire