A Multi-Center PSO Algorithm with Memory Ability and Its Application to the Online Modelling of an Underwater Vehicle Thruster

  • Gaofei Xu
  • Guanqun WangEmail author
  • Yiping Li
  • Xiaohui Wang
  • Xiangyu Qu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 582)


To improve the performance of Particle swarm optimization (PSO) in online optimization problems, a multi-center PSO algorithm with memory ability was proposed. Main strategies of the proposed algorithm include the initial population optimization based on historical optimal solution and improved chaos mapping and the multi-center collaborative search. To verify online optimization performance, the proposed algorithm is applied to the online modelling process of an underwater vehicle thruster to optimize the modeling parameters. Result proves the superiority of the proposed algorithm in online optimization problem.


Online optimization PSO Tent mapping Multi-center collaborative search Online modeling Underwater vehicles 



This work is supported by the National key research and development program (2017YFC0305901), National Natural Science Foundation of China (91648204).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Gaofei Xu
    • 1
    • 3
    • 4
  • Guanqun Wang
    • 1
    • 2
    Email author
  • Yiping Li
    • 1
    • 3
  • Xiaohui Wang
    • 1
    • 3
  • Xiangyu Qu
    • 1
    • 3
    • 4
  1. 1.State Key Lab of RoboticsShenyang Institute of Automation, CASShenyangChina
  2. 2.Chengde Petroleum CollegeChengdeChina
  3. 3.Institutes for Robotics and Intelligent Manufacturing, CASShenyangChina
  4. 4.University of Chinese Academy of SciencesBeijingChina

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