DocumentCode
2724784
Title
LMI Approach to Iterative Learning Control Design
Author
Ahn, Hyo-Sung ; Moore, Kevin L. ; Chen, YangQuan
Author_Institution
Electron. & Telecommun. Res. Inst.
fYear
2006
fDate
24-26 July 2006
Firstpage
72
Lastpage
77
Abstract
This paper uses linear matrix inequalities to design iterative learning controller gains. Comparisons are made between Arimoto-style gains, causal gains, and non-causal gains, using the supervector approach. The results show that linear time-varying gains have better performance than linear time invariant gains and non-causal terms make the system more stable in the sense of monotonic convergence
Keywords
adaptive control; convergence; iterative methods; learning systems; linear matrix inequalities; linear systems; time-varying systems; LMI; iterative learning control design; linear matrix inequalities; linear time-varying gains; monotonic convergence; Control design; Control systems; Design engineering; Hydrogen; Intelligent systems; Iterative methods; Linear matrix inequalities; MIMO; Performance gain; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Adaptive and Learning Systems, 2006 IEEE Mountain Workshop on
Conference_Location
Logan, UT
Print_ISBN
1-4244-0166-6
Type
conf
DOI
10.1109/SMCALS.2006.250694
Filename
4016765
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