Article ID Journal Published Year Pages File Type
697627 Automatica 2007 6 Pages PDF
Abstract

The paper proposes a noise tolerant iterative learning control (ILC) for a class of linear continuous-time systems, which achieves high-precision tracking for uncertain plants by iteration of trials in the presence of heavy measurement noise. The robustness against measurement noise is achieved through (i) projection of continuous-time I/O   signals onto a finite-dimensional parameter space, (ii) using error data of all past iterations via an integral operation in the learning law and (iii) noise reduction by H2H2 optimization subject to a specified convergence speed of the ILC.

Related Topics
Physical Sciences and Engineering Engineering Control and Systems Engineering
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