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State Estimation for a Class of Piecewise Affine State-Space Models

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Details

Original languageEnglish
Pages (from-to)61-65
Number of pages5
JournalIEEE Signal Processing Letters
Volume24
Issue number1
Early online date1 Dec 2016
DOIs
Publication statusPublished - Jan 2017
Publication typeA1 Journal article-refereed

Abstract

We propose a filter for piecewise affine state-space models. In each filtering recursion, the true filtering posterior distribution is a mixture of truncated normal distributions. The proposed filter approximates the mixture with a single normal distribution via moment matching. The proposed algorithm is compared with the extended Kalman filter (EKF) in a numerical simulation, where the proposed method obtains, on average, better root mean square error than the EKF.

Keywords

  • piecewise affine, state-space models, nonlinear filtering, Kalman filtering

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