Basic learning control law designs are summarized, and conditions for convergence of the learning process are developed when several different choices of filter frequency cutoffs are used for robustification. This paper presents a cliff harmonic-frequency filter with a sharp frequency cutoff and a weighted harmonic-frequency filter with frequency weighting, that are applied each iteration in iterative learning control. Filter matrices based on the state-space model of a finite-difference digital filter are derived for Matlab’s and Gustafsson’s forward and backward filtering which are commonly called filtfilt methods. Furthermore, filter matrices for Matlab’s and Gustafsson’s filtfilts are revised to make the input convergence matrix to be monotonically stable. Numerical examples are used to demonstrate the effectiveness of the harmonic-frequency filters comparing with Matlab’s and Gustafsson’s filtfilt methods based on Butterworth filters of different orders and cutoff frequencies. It is found that the singular values of filter matrices are related to the squared amplitude of the Butterworth filter at harmonic frequencies.


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    Title :

    Iterative Learning Control Inverse Problem Using Harmonic Frequency Filters


    Additional title:

    J Astronaut Sci


    Contributors:

    Published in:

    Publication date :

    2021-09-01


    Size :

    18 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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