An iterative identification method for linear continuous-time systems

被引：32
|
作者：
Campi, Marco C. [1 ]
Sugie, Toshiharu [2 ]
Sakai, Fumitoshi [3 ]
机构：
[1] Univ Brescia, Dept Elect Automat, I-25123 Brescia, Italy
[2] Kyoto Univ, Grad Sch Informat, Dept Syst Sci, Kyoto 6110011, Japan
[3] Nara Natl Coll Technol Yamatokoriyama, Dept Mech Engn, Nara 6391080, Japan
来源：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2008年 / 53卷 / 07期
关键词：
continuous-time systems; iterative learning control; Kalman filter; system identification;
D O I：
10.1109/TAC.2008.929371
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 paper presents a novel approach for the identification of continuous-time systems directly from sampled I/O data based on trial iterations. The method achieves identification through iterative learning control (ILC) concepts in the presence of heavy measurement noise. The robustness against measurement noise is achieved through 1) projection of continuous-time I/O signals onto a finite dimensional parameter space and 2) Kalman filter type noise reduction. In addition, an alternative simpler method is given with some robustness analysis. The effectiveness of the method is demonstrated through numerical examples for a nonminimum phase plant.
引用
收藏
页码：1661 / 1669
页数：9
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