• DocumentCode
    3483172
  • Title

    Adaptive inverse control using kernel identification

  • Author

    Abelli, A. ; Ferrari, A. ; Monaco, S. ; Richard, Cedric

  • Author_Institution
    Lab. J.L. Lagrange, Univ. de Nice-Sophia Antipolis, Sophia Antipolis, France
  • fYear
    2012
  • fDate
    27-29 June 2012
  • Firstpage
    202
  • Lastpage
    207
  • Abstract
    Kernel methods are exploited to implement an adaptive inverse control scheme of which a first introductory presentation is given. The resulting controller has faster convergence than the solutions proposed in literature utilizing Support Vector Machines (SVMs) [1] and Artificial Neural Networks (ANNs) [2]. Smaller residual errors are obtained for trajectory tracking. Simulations are carried out for different scenarios.
  • Keywords
    adaptive control; trajectory control; adaptive inverse control; kernel identification; residual error; trajectory tracking; Adaptation models; Dictionaries; Heuristic algorithms; Kernel; Least squares approximation; Support vector machines; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2012
  • Conference_Location
    Montreal, QC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4577-1095-7
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2012.6315449
  • Filename
    6315449
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3483172