Monotonically convergent ILC systems designed using bounded real lemma

被引:14
|
作者
Meng, Deyuan [1 ,2 ]
Jia, Yingmin [1 ,2 ,3 ]
Du, Junping [4 ]
Yu, Fashan [5 ]
机构
[1] Beihang Univ BUAA, Res Div 7, Beijing 100191, Peoples R China
[2] Beihang Univ BUAA, Dept Syst & Control, Beijing 100191, Peoples R China
[3] Beihang Univ BUAA, Key Lab Math Informat & Behav Semant, Beijing 100191, Peoples R China
[4] Beijing Univ Posts & Telecommun, Sch Comp Sci & Technol, Beijing Key Lab Intelligent Telecommun Software &, Beijing 100876, Peoples R China
[5] Henan Polytech Univ, Sch Elect Engn & Automat, Jiaozuo 454000, Henan, Peoples R China
关键词
iterative learning control; monotonic convergence; bounded real lemma; linear matrix inequality; ITERATIVE LEARNING CONTROL; IMPROVED LMI REPRESENTATIONS; CONTINUOUS-TIME SYSTEMS;
D O I
10.1080/00207721.2011.564324
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article is devoted to iterative learning control (ILC) systems design for multiple-input multiple-output (MIMO), linear time-invariant (LTI) plants. With the bounded real lemma (BRL) applied, a linear matrix inequality (LMI) design approach is presented to develop sufficient conditions for the monotonic convergence of the ILC process. It is shown that regardless of a system relative degree, the convergence conditions can be expressed in terms of LMIs, and formulas can be derived for the learning gain matrices design. For ILC determined in this way, two illustrative examples are provided to verify its effectiveness and robustness against structured and polytopic-type uncertainties.
引用
收藏
页码:2062 / 2071
页数:10
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