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A fuzzy-rule-based Couzin model

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Abstract

This paper proposes a modified Couzin and velocity-adaptive Couzin flocking model based on fuzzy rules. In the models, agents update their positions through a fuzzy-rule-based decision-making scheme in three perception zones. Stability of the systems are guaranteed. Simulations demonstrate that the convergence probability and relative converging size are both improved.

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Authors and Affiliations

  1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China

    Hairong Dong & Shigen Gao

  2. Beijing Corona Science & Technology Co., Ltd., Beijing, 100083, China

    Yan Zhao

Authors
  1. Hairong Dong
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  2. Yan Zhao
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  3. Shigen Gao
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Corresponding author

Correspondence to Hairong Dong.

Additional information

This work was supported by the National Natural Science Foundation of China (No. 61233001), the Fundamental Research Funds for Central Universities (No. 2013JBZ007), and the Beijing Jiaotong University Research Program (No. RCS2012ZZ003).

Hairong DONG received her B.S. and M.S. degrees in Automatic Control and Basic Mathematics from Zhengzhou University, Zhengzhou, China, in 1996 and 1999, respectively, and Ph.D. degree in General and Fundamental Mechanics from Peking University, Beijing, China, in 2002. She is currently a professor with the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University. She was a visiting scholar with the University of Southampton, Southampton, U.K., in 2006; the University of Hong Kong, Pokfulam, Hong Kong, in 2008; the City University of Hong Kong, Kowloon, Hong Kong, in 2009; the Hong Kong Polytechnic University, Kowloon, in 2010; and KTH Royal Institute of Technology, Sweden, in 2011. In 2007, she served as a project level-3 expert with the Department of Transportation for the Beijing Organizing Committee for the Olympic Games. Her research interests include stability and robustness of complex systems control theory, intelligent transportation systems, automatic train operation, and parallel control and management for urban rail transportation systems and high-speed railway systems.

Yan ZHAO received her B.S. degree from School of Computer and Information Engineering, Chongqing Technology and Business University, Chongqing, China in 2008, and M.S. degree from School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China in 2012. Her primary research interests is flocking control based on multi-agents.

Shigen GAO received his B.S. degree in Electrical Engineering and Automation from Tianjin University of Technology, Tianjin, China, in 2009, and is pursuing the Ph.D. degree at Beijing Jiaotong University, Beijing, China. From August to November 2011, he was a research assistant in the City University of Hong Kong. His primary research interests are automatic train operation, optimal control, parallel control and management for urban rail transportation systems and high-speed railway systems.

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Dong, H., Zhao, Y. & Gao, S. A fuzzy-rule-based Couzin model. J. Control Theory Appl. 11, 311–315 (2013). https://doi.org/10.1007/s11768-013-1193-0

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  • DOI: https://doi.org/10.1007/s11768-013-1193-0

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