• DocumentCode
    3628999
  • Title

    Ant Colony Optimization for optimal control

  • Author

    Jelmer van Ast;Robert Babuska;Bart De Schutter

  • Author_Institution
    Delft Center for Systems and Control of the Delft University of Technology, Mekelweg 2, 2628 CD, Netherlands
  • fYear
    2008
  • Firstpage
    2040
  • Lastpage
    2046
  • Abstract
    Ant Colony Optimization (ACO) has proven to be a very powerful optimization heuristic for Combinatorial Optimization Problems (COPs). It has been demonstrated to work well when applied to various NP-complete problems, such as the traveling salesman problem. In this paper, an ACO approach to optimal control is proposed. This approach requires that a continuous-time, continuous-state model of the system, together with a finite action set, is formulated as a discrete, non-deterministic automaton. The control problem is then translated into a stochastic COP. This method is applied to the time-optimal swing-up and stabilization of a pendulum.
  • Keywords
    "Torque","Automata","Optimization","Quantization","Aerospace electronics","Probability distribution","Optimal control"
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • ISSN
    1089-778X
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    1941-0026
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631068
  • Filename
    4631068