• DocumentCode
    1743728
  • Title

    Noncausal robust set-point regulation of nonminimum-phase scalar systems

  • Author

    Piazzi, Aurelio ; Visioli, Antonio

  • Author_Institution
    Dipt. di Ingegneria dell´´Inf., Parma Univ., Italy
  • Volume
    4
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    4098
  • Abstract
    In this paper we propose a method, based on dynamic inversion, for the set-point-regulation of uncertain nonminimum-phase scalar systems. In particular the worst-case settling time is minimized taking into account an amplitude constraint on the control variable and limits on the overshoot and undershoot of the output function. The application of the devised methodology yields to the connected design of both the controller and the reference command input. The latter is obtained by solving a special stable inversion problem on the nominal dynamic system that leads to a noncausal signal, causing the preaction control. Eventually, an optimization problem arises and its solution is gained by means of genetic algorithms. A simulation example shows the effectiveness of the overall methodology, despite the inherent difficulty of the addressed problem
  • Keywords
    control system synthesis; genetic algorithms; minimisation; optimal control; robust control; uncertain systems; GA; amplitude constraint; dynamic inversion; genetic algorithms; noncausal robust set-point regulation; optimization problem; overshoot limits; preaction control; reference command input; set-point-regulation; stable inversion problem; uncertain nonminimum-phase scalar systems; undershoot limits; worst-case settling time minimization; Analytical models; Control system synthesis; Control systems; Genetic algorithms; Linear feedback control systems; Linear systems; Performance analysis; Robustness; Signal synthesis; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2000. Proceedings of the 39th IEEE Conference on
  • Conference_Location
    Sydney, NSW
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-6638-7
  • Type

    conf

  • DOI
    10.1109/CDC.2000.912357
  • Filename
    912357