• DocumentCode
    2737060
  • Title

    Rapid trajectory optimization based on Migrant PSO

  • Author

    Xie, Fuqiang ; Wang, Yongji ; Li, Chuanfeng ; Zhao, Dangjun

  • Author_Institution
    Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    20-22 Nov. 2009
  • Firstpage
    777
  • Lastpage
    781
  • Abstract
    This paper proposes a rapid trajectory optimization approach using a novel PSO algorithm, the Migrant particle swarm optimization (Migrant PSO). Imitating the behavior of a flock of migrant birds, the Migrant PSO algorithm employs stochastic search method and adaptive linear search method respectively for PSO search spaces including both continuous space and discrete space. In the example of the minimum control energy reentry trajectory optimization for X-33 vehicle model with free terminal time, some key problems such as parameterized method are argued in detail. The simulation results indicate that the Migrant PSO algorithm proves to be able to generate a complete and optimal 3DOF reentry trajectory rapidly.
  • Keywords
    adaptive control; aerospace control; particle swarm optimisation; position control; search problems; Migrant PSO; Migrant particle swarm optimization; X-33 vehicle model; adaptive linear search method; continuous space; discrete space; migrant birds; minimum control energy; rapid trajectory optimization; stochastic search method; trajectory optimization; Adaptive control; Birds; Design optimization; Optimization methods; Particle swarm optimization; Programmable control; Search methods; Space technology; Stochastic processes; Vehicles; PSO; migrant; optimal control; trajectory optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-4754-1
  • Electronic_ISBN
    978-1-4244-4738-1
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2009.5358292
  • Filename
    5358292