Chen, Bo; Hu, Guoqiang; Ho, Daniel W. C.; Yu, Li Distributed Kalman filtering for time-varying discrete sequential systems. (English) Zbl 1406.93341 Automatica 99, 228-236 (2019). Summary: Discrete sequential system (DSS) consisting of different dynamical subsystems is a sequentially-connected dynamical system, and has found applications in many fields such as automation processes and series systems. However, few results are focused on the state estimation of DSSs. In this paper, the distributed Kalman filtering problem is studied for time-varying DSSs with Gaussian white noises. A locally optimal distributed estimator is designed in the linear minimum variance sense, and a stability condition is derived such that the mean square error of the distributed estimator is bounded. An illustrative example is given to demonstrate the effectiveness of the proposed methods. Cited in 6 Documents MSC: 93E11 Filtering in stochastic control theory 93E10 Estimation and detection in stochastic control theory 93A14 Decentralized systems 60H40 White noise theory 93-04 Software, source code, etc. for problems pertaining to systems and control theory 93A15 Large-scale systems 93D05 Lyapunov and other classical stabilities (Lagrange, Poisson, \(L^p, l^p\), etc.) in control theory Keywords:distributed Kalman filtering; stability analysis; time-varying discrete sequential systems PDF BibTeX XML Cite \textit{B. Chen} et al., Automatica 99, 228--236 (2019; Zbl 1406.93341) Full Text: DOI References: [1] Anderson, B. D.O.; Moore, J. B., Optimal filtering, (1979), Prentice-Hall: Prentice-Hall Englewood Cliffs, NJ · Zbl 0688.93058 [2] Bezzi, M.; Celada, F.; Ruffo, S.; Seiden, P. E., The transition between immue and discrete states in a celluar automaton model of clonal immune response, Physical A, 245, 1-2, 145-163, (1997) [3] Chen, B.; Ho, D. 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