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

被引：16

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

页码：3075 / 3082

页数：8

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