Abstract
Norm Optimal Iterative Learning Control is formulated quite generally and illustrated by applications to discrete and continuous state space systems. Convergence conditions are established and frequency attenuation and eigenstructure interpretations presented. Robustness conditions are put forward and written in frequency domain terms for discrete state space systems. The effect of non-minimum-phase zeros on performance is described in terms of the “flat-lining” phenomenon.
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