Multivariable model validation in the presence of time-variant disturbance dynamics

被引:17
作者
Huang, B [1 ]
机构
[1] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2G6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
detection of abrupt change; model validation; process identification; prediction error method; time-variant systems;
D O I
10.1016/S0009-2509(00)00105-6
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This paper is concerned with dynamic model validation through detection of parameter changes using the local detection approach. The local approach has ability to detect small changes very effectively. To enhance its robustness in the presence of time-variant disturbance dynamics, the local approach based on the output error identification algorithm is proposed. The effectiveness and robustness of the proposed method are illustrated through Monte-Carlo simulations. The result is also extended to multivariable model validation and verified on a multivariable pilot scale process. (C) 2000 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:4583 / 4595
页数:13
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