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Distributed full-order optimal fusion filters and smoothers for discrete-time stochastic singular systems

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  • Jiabing Sun
  • Chengjin Zhang
  • Bing Guo

Abstract

The optimal fusion problem for the state estimation of discrete-time stochastic singular systems is considered. The key idea is to convert a stochastic singular system with multiple sensors and correlated noises into an equivalent group of non-singular systems. Based on the state estimation for each local non-singular system, the optimal full-order filters and smoothers with a three-layer fusion structure are obtained for the original system using the optimal weighted fusion algorithms in the linear minimum variance sense. A simulation example shows that the fusion estimator is better than each local one.

Suggested Citation

  • Jiabing Sun & Chengjin Zhang & Bing Guo, 2011. "Distributed full-order optimal fusion filters and smoothers for discrete-time stochastic singular systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(3), pages 507-516.
    • Handle: RePEc:taf:tsysxx:v:42:y:2011:i:3:p:507-516
    DOI: 10.1080/00207721003611649
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