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LMI approach to robust monotonically convergent iterative learning control for uncertain linear discrete-time systems

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5 Author(s)
Li Zhifu ; Coll. of Autom., Sci. & Eng., South China Univ. of Technol., Guangzhou, China ; Yuan Peng ; Hu Yueming ; Guo Qiwei
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This paper presents a robust monotonically convergent (RMC) iterative learning control (ILC) design for a class of uncertain linear discrete-time systems with non-zero constant initial error. The learning law under consideration is an anticipatory ILC. Based on a simple quadratic performance function, a sufficient condition for robust monotonic convergence of the proposed learning algorithm is presented in terms of linear matrix inequality (LMI). Finally, a simulation example is given to show the effectiveness of the proposed scheme.

Published in:

Control Conference (CCC), 2012 31st Chinese

Date of Conference:

25-27 July 2012