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A UD factorization‐based nonlinear adaptive set‐membership filter for ellipsoidal estimation
Author(s) -
Zhou Bo,
Han Jianda,
Liu Guangjun
Publication year - 2007
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.1289
Subject(s) - robustness (evolution) , computation , ellipsoid , kernel adaptive filter , nonlinear system , filter (signal processing) , adaptive filter , control theory (sociology) , factorization , computer science , mathematics , mathematical optimization , algorithm , filter design , artificial intelligence , biochemistry , chemistry , physics , control (management) , quantum mechanics , astronomy , computer vision , gene
The extended set‐membership filter (ESMF) for nonlinear ellipsoidal estimation suffers from numerical instability, computation complexity as well as the difficulty in filter parameter selection. In this paper, a UD factorization‐based adaptive set‐membership filter is developed and applied to nonlinear joint estimation of both time‐varying states and parameters. As a result of using the proposed UD factorization, combined with a new sequential and selective measurement update strategy, the numerical stability and real‐time applicability of conventional ESMF are substantially improved. Furthermore, an adaptive selection scheme of the filter parameters is derived to reduce the computation complexity and achieve sub‐optimal estimation. Simulation results have shown the efficiency and robustness of the proposed method. Copyright © 2007 John Wiley & Sons, Ltd.