Identification of finite impulse response models: Methods and robustness issues

Industrial and Engineering Chemistry Research

Volumn 35, Issue 11, 1996, Pages 4078-4090

  Dayal, Bhupinder S ^a,b   MacGregor, John F ^a  

^a MCMASTER UNIVERSITY   (Canada)

^b GENERAL ELECTRIC COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; IDENTIFICATION (CONTROL SYSTEMS); LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; PREDICTIVE CONTROL SYSTEMS; PROCESS CONTROL; ROBUSTNESS (CONTROL SYSTEMS); STEP RESPONSE; SYSTEM STABILITY;

FINITE IMPULSE RESPONSE MODELS; NONPARSIMONIOUS MODELS; PREDICTION ERROR METHODS;

CHEMICAL OPERATIONS;

EID: 0030287874     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie960180e     Document Type: Article

References (19)

1. Box, G. E. P.; Jenkins, G. W. Time Series Analysis: Forecasting and Control; Holden Day: San Francisco, 1976.
2. Chin, A. A Fundamental Tray-by-Tray Model for MethanolAcetone-Water Extractive Distillation Column Simulation. Department of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada, 1989.
3. Clarke, D. W. Generalized Least Squares Estimation of Parameters of a Dynamic Model. First IFAC Symposium on Identification in Automatic Control Systems, Prague, Czeckoslovakia, 1967.
4. Cutler, C. R.; Ramaker, B. L. Dynamic Matrix Control-A Computer Control Algorithm. AIChE National Meeting, Houston, TX, 1979.
5. Garcia, C. E.; Morari, M. Internal Model Control. 2. Design Procedure for Multivariable Systems. Ind. Eng. Chem. Res. 1985, 24, 472-484.
6. Geladi, P.; Kowalski, B. Partial Least Squares Regression: A Tutorial. Anal. Chem. Acta 1986, 185, 1-17.
7. Goodwin, G. C.; Gevers, M.; Ninness, B. Quantifying the Error in Estimated Transfer Functions with Application to Model Order Selection. IEEE Trans. Autom. Control 1992, 37, 913-927.
8. Hoerl, A. E.; Kennard, R. W. Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics 1970a, 12, 55-67.
9. Hoerl, A. E.; Kennard, R. W. Ridge Regression: Applications to Nonorthogonal Problems. Technometrics 1970b, 12, 69-82.
10. Kozub, D. Personal communication, 1994.
11. Ljung, L. System Identification: Theory for the User; PrenticeHall: Englewood Cliffs, NJ, 1987.
12. MacGregor, J. F.; Kourti, T.; Kresta, J. V. Multivariate Identification: A Study of Several Methods. IFAC ADCHEM Conference Proceedings, Tolouse, France, Oct 1991.
13. Morari, M.; Zafiriou, E. Robust Process Control; Prentice-Hall: Englewood Cliffs, NJ, 1989.
14. Myers, R. H. Classical and Modern Regression with Applications; PWS-Kent Publishing Company: Boston, 1990.
15. Ricker, N. L. The Use of Biased Least-Squares Estimators for Parameters in Discrete-Time Pulse-Response Models. Ind. Eng. Chem. Res. 1988, 27, 343-350.
16. Söderström, T.; Stoica, P. System Identification; Prentice-Hall International: U.K., 1989.
17. Wierda, S. J. Multivariate Statistical Process Control-Recent Results and Directions for Future Research. Statistica Neerlandica 1994, 48, 147-168.
18. Wise, B. M.; Ricker, N. L. Identification of Finite Impulse Response Models by Principal Components Regression: Frequency-Response Properties. Process Control Qual. 1992, 4, 77.
19. Wise, B. M.; Ricker, N. L. Identification of Finite Impulse Response Models with Continuum Regression. J. Chemom. 1993, 7, 1-14.