Data-Driven based Iterative Learning Control for A Class of Discrete-Time Descriptor Systems

被引：0
|
作者：
Zhang, Daqing [1 ]
Yu, Jie [1 ]
Zhu, Baoyan [2 ]
机构：
[1] Univ Sci & Technol Liaoning, Sch Sci, Anshan 114051, Liaoning Provin, Peoples R China
[2] Shenyang Jianzhu Univ, Sch Sci, Shenyang 110168, Liaoning Provin, Peoples R China
来源：
PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016 | 2016年
关键词：
Descriptor systems; Iteration Learning Control; Data-driven; Tikhonov regularization; Norm-optimal; SINGULAR SYSTEMS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Data-driven iterative learning control (ILC) for discrete-time descriptor systems is concerned. The input-output property of single-input and single-output (SISO) discrete-time descriptor system is analyzed firstly. Then the relative degree of the underlying descriptor is investigated. Under the assumption that the system is causal, an ILC algorithm is presented based on the lifted form of descriptor system with zero relative degree. The ILC algorithm update the inputs serial by using the system tracking error, and does not need to know the inner structure of the target descriptor system in advance. Simulation results shows that, the presented ILC algorithm can make the target descriptor system's output track the desired output well.
引用
收藏
页码：3178 / 3182
页数：5
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