Arun Viswanathan, Nancy Feldman, et al.
IEEE Communications Magazine
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.
Arun Viswanathan, Nancy Feldman, et al.
IEEE Communications Magazine
Sonia Cafieri, Jon Lee, et al.
Journal of Global Optimization
M.J. Slattery, Joan L. Mitchell
IBM J. Res. Dev
Khalid Abdulla, Andrew Wirth, et al.
ICIAfS 2014