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

    Authors

    S. Y. Yang; Z. H. Qu; X. P. Fan;X. H. Nian

    Comments

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    Abbreviated Journal Title

    Automatica

    Keywords

    iterative learning control; quadratic performance index; iteration; domain; optimality; CONTROL ALGORITHM; QUADRATIC CRITERION; NONLINEAR-SYSTEMS; FEEDBACK; UNCERTAINTY; DESIGN; Automation & Control Systems; Engineering, Electrical & Electronic

    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. (c) 2008 Elsevier Ltd. All rights reserved.

    Journal Title

    Automatica

    Volume

    44

    Issue/Number

    5

    Publication Date

    1-1-2008

    Document Type

    Article

    Language

    English

    First Page

    1366

    Last Page

    1372

    WOS Identifier

    WOS:000256113400022

    ISSN

    0005-1098

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