JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (6): 62-68.doi: 10.6040/j.issn.1672-3961.0.2016.095

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Distributed state estimation algorithm for large-scale dynamic systems

SUN Yibing1, FU Minyue2,3*, WANG Bingchang1, ZHANG Huanshui1   

  1. 1. School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China;
    2. School of Electrical Engineering and Computer Science, University of Newcastle, NSW 2308, Australia;
    3. School of Automation, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
  • Received:2016-03-18 Online:2016-12-20 Published:2016-03-18

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Abstract: The problem of distributed state estimation over discrete-time large-scale dynamic systems was studied. The system was divided into some subsystem, and based on the local measurement and the information received from its neighbors, each subsystem utilized the proposed algorithm to estimate its local state, which reduced the dimension of the state vector, and enjoyed low computational complexity and communication load. This algorithm was run independently and in parallel to effectively reduce the overall execution time. By weakening the constraint condition, the mathematical induction was used to prove that the state estimation and prediction error covariance matrices obtained from this algorithm were positive definite. The rank criterion of system observability together with the inequality technique were utilized to prove that error covariance matrices had upper bounds and the upper bounds were also existence and bounded, which supported the feasibility of this algorithm in applications. At last, simulations of an example were provided to demonstrate the main results.

Key words: state estimation, power system, dynamic system, distributed state estimation, MAP estimation

CLC Number: 

  • TM744
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