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

• Published in: Second 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
• Language: English
• 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
• DOI: 10.1109/ICKS.2007.23
• ISBN: 9780769528113; 0769528112

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