Projection Based Iterative Learning Control with Its Application to Continuous-Time System Identification

The paper proposes a new iterative learning control 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) projectio...

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Bibliographic Details
Published inSecond International Conference on Informatics Research for Development of Knowledge Society Infrastructure (ICKS'07) pp. 95 - 102
Main Authors Sugie, T., Sakai, F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2007
Subjects
Automatic control
Control systems
Design methodology
Educational institutions
Noise measurement
Noise reduction
Noise robustness
Signal to noise ratio
System identification
Working environment noise
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Summary:The paper proposes a new iterative learning control 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 H 2 optimization. Then, based on the proposed control method, a novel approach to identification of continuous-time systems directly from the sampled I/O data is presented. Its effectiveness is demonstrated through numerical examples
ISBN:9780769528113
0769528112
DOI:10.1109/ICKS.2007.23