PD-Type Iterative Learning Control for Uncertain Spatially Interconnected Systems

被引：70

作者：

Zhou, Longhui ^{[1
]}

Tao, Hongfeng ^{[1
]}

Paszke, Wojciech ^{[2
]}

Stojanovic, Vladimir ^{[3
]}

Yang, Huizhong ^{[1
]}

机构：

[1] Jiangnan Univ, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Jiangsu, Peoples R China

[2] Univ Zielona Gora, Inst Automat Elect & Elect Engn, PL-65516 Zielona Gora, Poland

[3] Univ Kragujevac, Fac Mech & Civil Engn, Dept Automat Control Robot & Fluid Tech, Kraljevo 36000, Serbia

来源：

MATHEMATICS | 2020年 / 8卷 / 09期

基金：

中国国家自然科学基金;

关键词：

iterative learning control; spatially interconnected systems; norm uncertainty; repetitive process; PD-type; DISCRETE-TIME-SYSTEMS; DISTRIBUTED CONTROL; STABILITY ANALYSIS; DESIGN;

D O I：

10.3390/math8091528

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This paper puts forward a PD-type iterative learning control algorithm for a class of discrete spatially interconnected systems with unstructured uncertainty. By lifting and changing the variable of discrete space model, the uncertain spatially interconnected systems is converted into equivalent singular system, and the general state space model is derived in view of singular system theory. Then, the state error and output error information are used to design the iterative learning control law, transforming the controlled system into an equivalent repetitive process model. Based on the stability theory of repetitive process, sufficient condition for the stability of the system along the trial is given in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed algorithm is verified by the simulation of ladder circuits.

引用

页数：18

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