Rethinking the Mathematical Framework and Optimality of Set-Membership Filtering

Set-membership filter (SMF) has been extensively studied for state estimation in the presence of bounded noises with unknown statistics. Since it was first introduced in the 1960s, the studies on SMF have used the set-based description as its mathematical framework. One important issue that has been...

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Veröffentlicht in:	IEEE transactions on automatic control 2022-05, Vol.67 (5), p.2544-2551
Hauptverfasser:	Cong, Yirui, Wang, Xiangke, Zhou, Xiangyun
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayes’ rule for uncertain variables Ellipsoids Equivalence Hidden Markov models Kalman filters law of total range Linear systems Markov processes Mathematical analysis Nonlinear systems optimality Optimization Probability distribution set-membership filtering (SMF) State estimation uncertain variables
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