• DocumentCode
    114927
  • Title

    Multi-parametric extremum seeking-based auto-tuning for robust Input-Output linearization control

  • Author

    Benosman, Mouhacine

  • Author_Institution
    Mitsubishi Electr. Res. Labs., Cambridge, MA, USA
  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    2685
  • Lastpage
    2690
  • Abstract
    We study in this paper the problem of iterative feedback gains tuning for a class of nonlinear systems. We consider Input-Output linearizable nonlinear systems with additive uncertainties. We first design a nominal Input-Output linearization-based controller that ensures global uniform boundedness of the output tracking error dynamics. Then, we complement the robust controller with a model-free multi-parametric extremum seeking (MES) control to iteratively auto-tune the feedback gains. We analyze the stability of the whole controller, i.e. robust nonlinear controller plus model-free learning algorithm. We use numerical tests to demonstrate the performance of this method on a mechatronics example.
  • Keywords
    feedback; iterative methods; learning systems; linearisation techniques; mechatronics; nonlinear control systems; optimal control; robust control; MES control; additive uncertainties; global uniform boundedness; input-output linearizable nonlinear systems; iterative autotuning; iterative feedback gain tuning problem; mechatronics; model-free learning algorithm; model-free multiparametric extremum seeking control; nominal input-output linearization-based controller design; numerical tests; output tracking error dynamics; robust nonlinear controller; stability analysis; Coils; Cost function; Robustness; Trajectory; Tuning; Uncertainty; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-1-4799-7746-8
  • Type

    conf

  • DOI
    10.1109/CDC.2014.7039800
  • Filename
    7039800