An improved particle swarm optimization and its application in maneuvering control laws design of the unmanned aerial vehicle

Jie Guo*, Shengjing Tang, Qian Xu

*Corresponding author for this work

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

Abstract

An improved particle swarm optimization algorithm with dynamic population mechanism is introduced in this paper aiming at the optimal design of the maneuvering flight scheme of the unmanned aerial vehicle system which confronts complex nonlinear flight characteristics. The control law of the typical S maneuver in vertical plane is parameterized through spline method and the constraints are disposed by the penalty function method in a weighted objective function. A practical design example of the unmanned aerial vehicle maneuvering scheme is given at last, and the simulation results show the availability of the method proposed in this paper and also a good application prospects in the flight scheme optimal design of the unmanned aerial vehicles.

Original languageEnglish
Title of host publicationProceedings - 2012 8th International Conference on Natural Computation, ICNC 2012
Pages1107-1111
Number of pages5
DOIs
Publication statusPublished - 2012
Event2012 8th International Conference on Natural Computation, ICNC 2012 - Chongqing, China
Duration: 29 May 201231 May 2012

Publication series

NameProceedings - International Conference on Natural Computation
ISSN (Print)2157-9555

Conference

Conference2012 8th International Conference on Natural Computation, ICNC 2012
Country/TerritoryChina
CityChongqing
Period29/05/1231/05/12

Keywords

  • maneuvering flight
  • particle swarm optimization
  • unmanned aerial vehicle

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