Elliot Linzer, M. Vetterli
Computing
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.
Elliot Linzer, M. Vetterli
Computing
Frank R. Libsch, Takatoshi Tsujimura
Active Matrix Liquid Crystal Displays Technology and Applications 1997
Corneliu Constantinescu
SPIE Optical Engineering + Applications 2009
Raymond F. Boyce, Donald D. Chamberlin, et al.
CACM