Examination of iterative learning control for repetitive fast and precise positioning motion combining short and long interval periods

• Published in: IEEE/ASME International Conference on Advanced Intelligent Mechatronics pp. 1382 - 1387
• Main Authors: Ito, Makoto, Maeda, Yoshihiro, Iwasaki, Makoto
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2017
• Subjects: Control systems; Gain; Iterative learning control; Mathematical model; Mechatronics; Resonant frequency; Uncertainty
• ISBN: 1509059989; 9781509059980
• ISSN: 2159-6255
• DOI: 10.1109/AIM.2017.8014211

This paper examines an application of the iterative learning control (ILC) scheme for fast and precise positioning of galvano scanners with a combination of short and long interval times. The ILC scheme is well-known as one of the effective control approaches for high-precision motion control of mechatronic systems, and a variety of ILC methods have been proposed in the former literature. Most of the ILC methods are applied to fixed repetitive motions and perform the learning process to compensate effects of model errors, disturbances, and uncertainties. However, the galvano scanners often require sequential repetitive short interval motions between long interval positioning trials for the laser processing, which means that the learning interval time varies between the short and long interval trials. In such special positioning motions, ILC cannot compensate undesired responses sufficiently. In this study, we consider the ILC property for a sequential repetitive movement combining short and long interval motions by theoretical examinations and numerical simulations, and subject matters to be solved are clarified as an initial consideration.