• DocumentCode
    2850562
  • Title

    1 adaptive output feedback controller for minimum phase systems

  • Author

    Kharisov, E. ; Hovakimyan, N.

  • fYear
    2011
  • fDate
    June 29 2011-July 1 2011
  • Firstpage
    1182
  • Lastpage
    1187
  • Abstract
    This paper presents an £1 adaptive output feed back controller for a class of uncertain nonlinear systems in the presence of time and output dependent unknown nonlinearities. As compared to earlier introduced £1 adaptive output feedback control architectures, the architecture in this paper relies on system inversion, and is therefore limited to minimum phase systems. Similar to prior solutions in £1 adaptive control theory, the feedback structure is comprised of the three main elements, involving predictor, adaptation laws and low-pass filter, with the only difference that the predictor here is an input predictor and not a state predictor. Whereas in prior architectures of £1 adaptive output feedback control the verification of the sufficient condition for stability, written in terms of £1 norm of cascaded systems, was not straightforward, the solution proposed in this paper, under mild assumptions on system dynamics, provides a complete parametrization of the low-pass filters for the design purposes. The closed-loop system achieves arbitrarily close tracking of the input and the output signals of the reference system. Simulations verify the theoretical findings.
  • Keywords
    adaptive control; cascade systems; closed loop systems; control nonlinearities; control system synthesis; feedback; low-pass filters; nonlinear control systems; stability; uncertain systems; £ι adaptive output feedback controller architecture; cascaded system; closed-loop system; feedback structure; low-pass filter; minimum phase system; output signal tracking; state predictor; uncertain nonlinear system; Adaptation models; Adaptive control; Output feedback; Polynomials; Transient analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2011
  • Conference_Location
    San Francisco, CA
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4577-0080-4
  • Type

    conf

  • DOI
    10.1109/ACC.2011.5991012
  • Filename
    5991012