• DocumentCode
    1090401
  • Title

    A Genetic Algorithm Convergence and Models for Eigenstructure Assignment via Linear Quadratic Regulator (LQR)

  • Author

    Viana Fonseca, J. ; Silva Abreu, I. ; Moraes Rego, P.H. ; de Paulo Melo Wolff, M. ; Silva, O.F.

  • Volume
    6
  • Issue
    1
  • fYear
    2008
  • fDate
    3/1/2008 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    In this article, models and a genetic algorithm convergence analysis method for the LQR weight matrices determination are presented. The control goal is the eigenstructures allocation in multivariable dynamic systems imposed by the optimal control law, and the analysis procedure goal is the speeding up of the convergence through metrics based upon first and second order statistical momentum. The proposal performance is evaluated under the initial populations building point of view and the populations search process, whereas the convergence analysis leads to the development of rules based upon fitness function metrics. Tests for the genetic search models performance evaluation and for the control law efficiency are conducted with a 6th order dynamic model representing an aircraft.
  • Keywords
    eigenvalues and eigenfunctions; genetic algorithms; linear quadratic control; matrix algebra; multivariable control systems; eigenstructure assignment; eigenstructures allocation; fitness function metrics; genetic algorithm convergence; linear quadratic regulator; multivariable dynamic systems; optimal control; Aircraft; Algorithm design and analysis; Control systems; Convergence; Genetic algorithms; Optimal control; Performance analysis; Proposals; Regulators; Testing; Eigenstructure assignment; convergence analysis; genetic algorithm; linear quadratic regulator;
  • fLanguage
    English
  • Journal_Title
    Latin America Transactions, IEEE (Revista IEEE America Latina)
  • Publisher
    ieee
  • ISSN
    1548-0992
  • Type

    jour

  • DOI
    10.1109/TLA.2008.4461626
  • Filename
    4461626