Chidanand Apté, Fred Damerau, et al.
ACM Transactions on Information Systems (TOIS)
This paper presents a learning self-tuning (LSTR) regulator which improves the tracking performance of itself while performing repetitive tasks. The controller is a self-tuning regulator based on learning parameter estimation. Experimentally, the controller was used to control the movement of a nonlinear piezoelectric actuator which is a part of the tool positioning system for a diamond turning lathe. Experimental results show that the controller is able to reduce the tracking error through the repetition of the task. © 1993 by ASME.
Chidanand Apté, Fred Damerau, et al.
ACM Transactions on Information Systems (TOIS)
Chi-Leung Wong, Zehra Sura, et al.
I-SPAN 2002
Raghu Krishnapuram, Krishna Kummamuru
IFSA 2003
Michael Ray, Yves C. Martin
Proceedings of SPIE - The International Society for Optical Engineering