Determination of state-space model uncertainty using bootstrap techniques

被引:6
作者
Lopes, Vitor V. [1 ]
Pinheiro, Carla C. [1 ]
Menezes, Jose C. [1 ]
机构
[1] Univ Tecn Lisboa, Inst Syst & Robot, LaSEEB, Ctr Biol & Chem Engn, P-1049001 Lisbon, Portugal
关键词
state-space parameterization; subspace identification; bootstrap method; parameter uncertainty;
D O I
10.1016/j.jprocont.2006.01.007
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
Robust control theory is widely used as the theoretical basis for the design of controllers with reduced sensibility to model errors. The model parameters variance-covariance (VC) matrix allows to design controllers with a consistent control action, even in the presence of moderate model mismatch. This paper presents a technique to extract the state-space model variance-covariance matrix using bootstrap techniques. The VC matrix is estimated from bootstrapped models using a first-order approximation of the model parameters space. The technique is applied by estimating the nominal model uncertainty of a deisopentanizer petrochemical unit. The model uncertainty is determined more accurately by the proposed method, when compared to the use of minimal canonical parameterization, providing better first-order approximation confidence intervals. (C) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:685 / 692
页数:8
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