Iterative Learning Control with Advanced Output Data for an Unknown Number of Non-minimum Phase Zeros

Gu-Min JEONG  Chanwoo MOON  Hyun-Sik AHN  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E95-A   No.8   pp.1416-1419
Publication Date: 2012/08/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E95.A.1416
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Systems and Control
Keyword: 
iterative learning control,  non-minimum phase system,  learning algorithm,  advanced time,  

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Summary: 
This letter investigates an iterative learning control with advanced output data (ADILC) scheme for non-minimum phase (NMP) systems when the number of NMP zeros is unknown. ADILC has a simple learning structure that can be applied to both minimum phase and NMP systems. However, in the latter case, it is assumed that the number of NMP zeros is already known. In this paper, we propose an ADILC scheme in which the number of NMP zeros is unknown. Based on input-to-output mapping, the learning starts from the relative degree. When the input becomes larger than a certain upper bound, we redesign the input update law which consists of the relative degree and the estimated value for the number of NMP zeros.