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Distributed Fuzzy Extended Kalman Filter for Multiagent Systems

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  • Intelligent Control and Applications
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Abstract

In this study, a novel distributed Kalman filter based on a possibilistic framework was proposed to mitigate fuzzy noisein nonlinear multiagent systems. To describe fuzzy uncertainty, noises were modeled as fuzzy random variables with trapezoidal probability distributions instead of Gaussian distributions. A fuzzy information fusion (FIF) algorithm was proposed to fuse fuzzy state estimations from neighboring nodes. The nonlinear problem was solved by using local linearization. A distributed extended fuzzy information filter was designed by combining the FIF algorithm and local linearization in distributed sensor networks. The stability of this filter was analyzed. Finally, a target tracking simulation was performed to detail the effectiveness of the proposed filter algorithm.

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Authors and Affiliations

  1. Department of Electronic Engineering, PLA Rocket Force University of Engineering, Xi’an, Shaanxi, 710025, China

    Xiaobo Zhang, Haoshen Lin, Gang Liu & Bing He

Authors
  1. Xiaobo Zhang
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  2. Haoshen Lin
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  3. Gang Liu
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  4. Bing He
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Correspondence to Xiaobo Zhang.

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Conflicts of Interest

No conflict of interest exists in the submission of this manuscript, and the manuscript is approved by all authors for publication.

Xiaobo Zhang received his B.S. and M.S. degrees from the Space Engineering University, China, in 2007 and 2011, respectively. He is currently pursuing a Ph.D. degree in control science and engineering with the Rocket Force University of Engineering (RFUE), China. His research interests include information processing, control theory, and distributed estimation.

Haoshen Lin received his Ph.D. degree in control science and engineering from the RFUE, China, in 2021. His research interests include information processing, control theory, and distributed estimation.

Gang Liu received his B.S. and M.S. degrees from the RFUE, in 1988 and 1991, respectively, and a Ph.D. degree from Northwestern Polytechnical University, in 1998. He is currently a Professor with RFUE. His research interests include adaptive signal processing, system modeling, and fault diagnosis.

Bing He received his B.S., M.S., and Ph.D. degrees from the RFUE, in 2005, 2008, and 2012, respectively. He is currently a Professor with RFUE. His research interests include signal processing, control theory, and artificial intelligence technology.

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Zhang, X., Lin, H., Liu, G. et al. Distributed Fuzzy Extended Kalman Filter for Multiagent Systems. Int. J. Control Autom. Syst. 21, 1692–1703 (2023). https://doi.org/10.1007/s12555-021-1060-6

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  • DOI: https://doi.org/10.1007/s12555-021-1060-6

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