Optimal deterministic transfer function modelling in the presence of serially correlated noise

被引:7
作者
Rollins, DK [1 ]
Bhandari, N [1 ]
Chin, ST [1 ]
Junge, TM [1 ]
Roosa, KM [1 ]
机构
[1] Iowa State Univ, Dept Chem Engn, Ames, IA 50011 USA
关键词
Wiener system; Hammerstein system; predictive modelling; dynamic modelling; block-oriented modelling; ARMA; serially correlated noise;
D O I
10.1205/cherd.05190
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This article addresses the development of predictive transfer function models for nonlinear dynamic processes under serially correlated model error. This work is presented in the context of the block-oriented exact solution technique (BEST) for multiple input, multiple output (MIMO) processes proposed by Bhandari and Rollins (2003) for continuous-time modelling and Rollins and Bhandari (2004) for constrained discrete-time modelling. This work proposes a model building methodology that is able to separately determine the steady state, dynamic and noise model structures. It includes a pre-whitening procedure that is affective for the general class of discrete ARMA(p, q) noise (Box and Jenkins, 1976). The proposed method is demonstrated using a simulated physical system and a real physical system.
引用
收藏
页码:9 / 21
页数:13
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