This chapter presents a number of simple methods for accelerating the convergence of the Norm-Optimal Iterative Learning control (NOILC) algorithm as measured by the number of online experiments required to achieve a desired tracking accuracy. The approaches require algorithm modifications and/or additional offline, model-based calculations but have discernible beneficial effects although some reduction in robustness can be anticipated. The notation and models assumed are precisely those used in the NOILC Chap. 5. A familiarity with the ideas, techniques, and examples used in that chapter will be of great value to the reader.


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    Titel :

    Accelerating NOILC Convergence


    Weitere Titelangaben:

    Advances in Industrial Control


    Beteiligte:
    Chu, Bing (Autor:in) / Owens, David H. (Autor:in)


    Erscheinungsdatum :

    13.06.2025


    Format / Umfang :

    40 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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