• DocumentCode
    1795351
  • Title

    Angular constrained guidance law and its optimization with hybrid optimization algorithm

  • Author

    Chao Tao ; Wang Songyan ; Yang Ming

  • Author_Institution
    Control & Simulation Center, Harbin Inst. of Technol., Harbin, China
  • fYear
    2014
  • fDate
    8-10 Aug. 2014
  • Firstpage
    2455
  • Lastpage
    2460
  • Abstract
    A new guidance law with terminal trajectory angle constraint is designed for bank to turn flight vehicle, which aims at the fixed position ground target. The general form of guidance law with sight angle and sight angle velocity as feedback variables is presented, and the stability of it is proved via finite time convergent stability theory, which makes traditional optimal guidance as a specific example of this general form guidance law. Parameters optimization of this guidance law is proposed using a hybrid optimization algorithm in order to help the designer to find suitable parameters, which can have the specific characteristics they are seeking for. Numerical simulation shows that the proposed guidance law is effective and the hybrid optimization algorithm can get the optimal solution of the guidance law design problem more quickly than before.
  • Keywords
    aerospace computing; aircraft control; convergence; genetic algorithms; numerical analysis; stability; angular constrained guidance law; finite time convergent stability theory; flight vehicle; genetic algorithm; guidance law design problem; hybrid optimization algorithm; numerical simulation; optimal guidance; parameters optimization; support vector machine; terminal trajectory angle constraint; Equations; Genetic algorithms; Mathematical model; Optimization; Support vector machines; Trajectory; Vehicles; Angular Constraints; Bank to Turn; Genetic Algorithm; Guidance; Support Vector Machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4799-4700-3
  • Type

    conf

  • DOI
    10.1109/CGNCC.2014.7007554
  • Filename
    7007554