Paper Info
Title
First order iterative learning control for a single axis piezostage system
Abstract
Nowadays many machines and robots are programmed to perform the same task repeatedly. The Iterative Learning Control (ILC) paradigm is based on the idea that the performance of a system that executes the same trial multiple times can be improved by learning from the previous iterations. The objective of ILC is to improve the batch process performance by incorporating past trials error information into the control reference signal for the subsequent iteration. The ILC algorithms are categorized with respect to the number of past iterations considered to compute the next control signal and the first order ILC includes those algorithms considering only information about the last trial. In this paper different first order ILC update laws have been considered and compared controlling a Single-Input Single-Output (SISO) micro-positioning piezostage system. The proposed comparison allows to evaluate the performance of different first order ILC algorithms tested on the considered real world case study.
Year
DOI
Venue
2018
10.1109/CoDIT.2018.8394873
2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)
Keywords
Field
DocType
robots,Iterative Learning Control paradigm,batch process performance,control reference signal,ILC algorithms,control signal,Single-Input Single-Output micropositioning piezostage system,piezostage system
Task analysis,First order,Computer science,Control engineering,Batch processing,Iterative learning control,Robot,Trajectory
Conference
ISSN
ISBN
Citations 
2576-3555
978-1-5386-5066-0
0
PageRank 
References 
Authors
0.34
11
10
Name
Order
Citations
PageRank
luca cavanini172.95
Maria Letizia Corradini228130.10
Andrea Di Donato351.54
Marco Farina432415.97
Lennart Hoffhues500.34
Gianluca Ippoliti623230.44
Davide Mencarelli700.34
Giuseppe Orlando834234.74
Luca Pierantoni900.34
Markus F. Wieghaus1000.34