Norm Optimal Iterative Learning Control is formulated and illustrated by applications to discrete and continuous state-space systems. Convergence conditions and other properties are established. Frequency attenuation and eigenstructure interpretations are derived and some insight into parameter choice is revealed. Robustness conditions are put forward and written in frequency domain terms for discrete state-space systems. Issues that affect algorithm performance are discussed.
Norm Optimal Iterative Learning Control
Advances in Industrial Control
13.06.2025
43 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Predictive Norm Optimal Iterative Learning Control
Springer Verlag | 2025
|Norm Optimal Iterative Learning Control with ConstraintsNOILC, Constraints
Springer Verlag | 2025
|Computationally‐light non‐lifted data‐driven norm‐optimal iterative learning control
British Library Online Contents | 2018
|British Library Online Contents | 2015
|