Non-Parametric Identification in Dynamic Networks

被引：0

作者：

Dankers, Arne ^{[1
]}

Van den Hof, Paul M. J. ^{[2
]}

机构：

[1] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada

[2] Eindhoven Univ Technol, Dept Elect Engn, NL-5600 MB Eindhoven, Netherlands

来源：

2015 54TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2015年

关键词：

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：

In this paper we present a non-parametric approach to identification in networks. The main advantage of a non-parametric approach is that consistent estimates can be obtained with very little prior knowledge about the system. This is a particularly important consideration for a network identification problem which can easily become very complex with high order dynamics and many inputs. We consider a very general framework for dynamic networks that includes measured variables, external excitation variables, process noise, and sensor noise.

引用

页码：3487 / 3492

页数：6

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