• DocumentCode
    510144
  • Title

    An Adaptive Evolutionary Strategy and its Application in the Optimization of the Aircraft Control Law in the Large Flight Envelope

  • Author

    Li, Guangwen ; Jia, Qiuling ; Shi, Jingping

  • Author_Institution
    Coll. of Autom., Northwestern Polytech. Univ., Xi´´an, China
  • Volume
    1
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    563
  • Lastpage
    567
  • Abstract
    The searching precision and the global searching ability of Evolutionary Strategy (ES) depend on the selection of the mutation step. In order to enhance the global searching ability and precision, an adaptive evolutionary strategy based on the feedback and sharing mechanism (ESBFSM) is proposed, in which the information of the current optimal searching result and sharing degree is fed into the mutating formula. By tuning the variance of the mutation operator according to the feedback information, the mutation step of ES is changed with the current searching result. And a part of individuals of the population in the later searching procedure keep higher probability of jumping out of the local minimum by the sharing mechanism. To validate the optimizing effect of the ESBFSM, the optimization of an transport aircraf´s control law in the large flight envelope is done by this method, the result shows the ESBFSM is effective in optimization of the complex control system.
  • Keywords
    aircraft control; evolutionary computation; large-scale systems; optimisation; relevance feedback; search problems; adaptive evolutionary strategy; aircraft control law; complex control system; feedback information; large flight envelope; mutating formula; mutation step selection; optimal searching; optimization; searching precision; sharing mechanism; Adaptive control; Aerospace control; Aircraft; Automation; Control systems; Educational institutions; Feedback; Genetic mutations; Optimization methods; Programmable control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.218
  • Filename
    5376307