Subspace identification of multivariable linear parameter-varying systems

被引：194

作者：

Verdult, V ^{[1
]}

Verhaegen, M ^{[1
]}

机构：

[1] Delft Univ Technol, Fac Informat Technol & Syst, NL-2600 GA Delft, Netherlands

来源：

AUTOMATICA | 2002年 / 38卷 / 05期

关键词：

system identification; subspace methods; state-space methods; linear parameter-varying systems; bilinear systems;

D O I：

10.1016/S0005-1098(01)00268-0

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 [计算机科学与技术];

摘要：

A subspace identification method is discussed that deals with multivariable linear parameter-varying state-space systems with affine parameter dependence. It is shown that a major problem with subspace methods for this kind of system is the enormous dimension of the data matrices involved. To overcome the curse of dimensionality, we suggest using only the most dominant rows of the data matrices in estimating the model. An efficient selection algorithm is discussed that does not require the formation of the complete data matrices, but processes them row by row. (C) 2002 Elsevier Science Ltd. All rights reserved.

引用

页码：805 / 814

页数：10

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