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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    Title :

    Accelerating NOILC Convergence


    Additional title:

    Advances in Industrial Control


    Contributors:
    Chu, Bing (author) / Owens, David H. (author)


    Publication date :

    2025-06-13


    Size :

    40 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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