Input Design for Kernel-Based System Identification From the Viewpoint of Frequency Response

被引：18
|
作者：
Fujimoto, Yusuke [1 ]
Maruta, Ichiro [1 ]
Sugie, Toshiharu [1 ]
机构：
[1] Kyoto Univ, Dept Syst Sci, Grad Sch Informat, Kyoto 6068501, Japan
来源：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2018年 / 63卷 / 09期
关键词：
Identification for control; input design; machine learning; system identification;
D O I：
10.1109/TAC.2018.2791464
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 discusses a method for designing input sequences for kernel-based system identification methods from the frequency perspective. The goal of this paper is to minimize the posterior uncertainty of the spectrum over the frequency band of the interest. A tractable criterion for this purpose is proposed, which is related to the so-called Bayesian A-optimality. An online algorithm that gives a suboptimal input for this criterion is proposed. Moreover, it is shown that the optimal solution can be obtained in an offline manner under a certain condition. The effectiveness of these methods is demonstrated through numerical simulations.
引用
收藏
页码：3075 / 3082
页数：8
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