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Accuracy analysis for distributed dynamic state estimation in large-scale systems with a cyclic network graph

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  • Special Topic: Control, Optimization, and Learning for Networked Systems
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Abstract

This paper addresses a distributed dynamic state estimation problem in large-scale systems characterized by a cyclic network graph. The objective is to develop a distributed estimation algorithm for each node to generate local state estimations, based on the coupled measurements and boundary information exchanged with neighboring nodes. Our proposed approach is grounded in the maximum a posteriori (MAP) estimation method, which yields suboptimal results in acyclic network graphs compared with the centralized MAP approach. We extend this approach to systems with a cyclic network graph. Furthermore, we provide an accuracy analysis by deriving bounds for the differences in estimation error covariance and state estimation between the proposed distributed algorithm and the suboptimal centralized MAP method. These bounds apply to a specific category of systems that satisfy certain conditions, including cyclic topology and sparse connections. We demonstrate that these bounds converge asymptotically, with the rate of convergence determined by the loop-free depth of the graph. The loop-free depth of the graph refers to the maximum number of nodes that can be traversed in a cycle without revisiting any node. Finally, we demonstrate the validity of the algorithm through numerical examples.

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Acknowledgements

This work was supported by National Key R&D Program of China (Grant Nos. 2018YFB1700100, 2020YFB1708600), National Natural Science Foundation of China (Grant Nos. 62173057, 62033006, 61906088), Liaoning Revitalization Talents Program (Grant No. XLYC2007187), Natural Science Foundation of Liaoning (Grant No. 2020-MS-122), and Dalian Young Talents Program (Grant No. 2021RQ038).

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Authors and Affiliations

  1. School of Control Science and Engineering, Dalian University of Technology, Dalian, 116024, China

    Mingyan Zhu & Tianju Sui

  2. School of Aeronautics and Astronautics, Dalian University of Technology, Dalian, 116024, China

    Rui Wang

  3. School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing, 211816, China

    Xiaodong Miao

  4. Key Laboratory of Advanced Technology for Aerospace Vehicles, Liaoning Province, Dalian, 116024, China

    Rui Wang

  5. Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian, 116024, China

    Mingyan Zhu & Tianju Sui

Authors
  1. Mingyan Zhu
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  2. Rui Wang
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  3. Xiaodong Miao
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  4. Tianju Sui
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Corresponding authors

Correspondence to Rui Wang or Xiaodong Miao.

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Zhu, M., Wang, R., Miao, X. et al. Accuracy analysis for distributed dynamic state estimation in large-scale systems with a cyclic network graph. Sci. China Inf. Sci. 66, 190206 (2023). https://doi.org/10.1007/s11432-022-3846-1

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  • DOI: https://doi.org/10.1007/s11432-022-3846-1

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