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The application of an improved chaos-particle swarm optimization algorithm to the real submersible path-planning

  • Fei Yu
  • , Meikui Zou
  • , Chongyang Lv
  • Harbin Engineering University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Path planning is one of hot research topics of underwater vehicle, and the real submarine path planning needs a concise and short line. This paper presents a new improved chaos particle swarm algorithm (GCPSO), where the particle swarm algorithm (PSO) is changed by using nonlinear strategy to change the inertial weights and a variable learning factor. The numerical example shows that the improved GCPSO has better convergence and stronger optimization ability than standard particle swarm algorithm. On this basis, the algorithm is used in the simulation of underwater vehicle path planning. The path planning problem is transformed into the optimization problem of pursuing path points through the novel modeling with condition constraint to get a better path, and then an optimal line is obtained.

Original languageEnglish
Title of host publicationProceedings - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
Pages316-319
Number of pages4
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013 - Hangzhou, Zhejiang, China
Duration: 26 Aug 201327 Aug 2013

Publication series

NameProceedings - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
Volume2

Conference

Conference2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
Country/TerritoryChina
CityHangzhou, Zhejiang
Period26/08/1327/08/13

Keywords

  • Chaos optimization
  • Chaos particle swarm optimization algorithm
  • Path planning
  • Submersible navigation

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