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Novel iterative learning controls for linear discrete-time systems based on a performance index over iterations

Authors
Journal
Automatica
0005-1098
Publisher
Elsevier
Publication Date
Volume
44
Issue
5
Identifiers
DOI: 10.1016/j.automatica.2007.10.024
Keywords
  • Iterative Learning Control
  • Quadratic Performance Index
  • Iteration Domain
  • Optimality
Disciplines
  • Design

Abstract

Abstract An optimal iterative learning control (ILC) is proposed to optimize an accumulative quadratic performance index in the iteration domain for the nominal dynamics of linear discrete-time systems. Properties of stability, convergence, robustness, and optimality are investigated and demonstrated. In the case that the system under consideration contains uncertain dynamics, the proposed ILC design can be applied to yield a guaranteed-cost ILC whose solution can be found using the linear matrix inequality (LMI) technique. Simulation examples are included to demonstrate feasibility and effectiveness of the proposed learning controls.

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