Optimization of aircraft flight control system based on an improved MOPSO algorithm

Kejun Bi, Baoning Liu, Weiguo Zhang, Rui Nie

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

1 Scopus citations

Abstract

With regard to the disadvantage of the basic particle swarm optimization algorithm trapped into the local optimal easily, an improved multi-objective particle swarm optimization (MOPSO) is proposed. Firstly, a method of initial population assignment which based on the uniform design is adopted. And it could make the initial population distribute as evenly as possible in the whole decision space. Secondly, the improved generation distance index is used as the judging condition when the algorithm trapped into the local optimal, and the chaos mutation operator is adopted to jump out the local optimal. Additionally, a new adaptive inertia weight is used to maintain diversity of population. Finally, the improved algorithm is applied to design the longitudinal control system of a certain type of aircraft. The results of the numerical simulation show the effectiveness of the improved algorithm.

Original languageEnglish
Title of host publication2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings
Pages4842-4845
Number of pages4
DOIs
StatePublished - 2011
Event2nd Annual Conference on Electrical and Control Engineering, ICECE 2011 - Yichang, China
Duration: 16 Sep 201118 Sep 2011

Publication series

Name2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings

Conference

Conference2nd Annual Conference on Electrical and Control Engineering, ICECE 2011
Country/TerritoryChina
CityYichang
Period16/09/1118/09/11

Keywords

  • chaos mutation
  • flight control system
  • multi-objective particle swarm optimization
  • uniform design

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