Grey box modelling of a pickling process using Taylor serial expansion
System Identification, Volume # 14 | Part# 1
Authors
Bjorn Sohlberg
Identifier
10.3182/20060329-3-AU-2901.00015
Index Terms
grey box modelling,identification,nonlinear models,steel industry,Taylor series
Abstract
This paper deals with a case study of grey box modelling where known parts are modelled using a priori information and unknown parts are described as general continuous nonlinear functions, which are approximated by means of Taylor series including higher order terms. In the Taylor series, the partial derivatives are estimated from measured data by minimising the maximum likelihood function. This approach is used to keep the number of estimated parameters low. The modelling procedure follows a structured approach including; basic modelling, data acquisition, model calibration, expanded modelling, stochastic modelling and model appraisal.
References
[1] Bohlin T. (1991). Interactive System Identification:
Prospects and Pitfalls. Springer-Verlag. Berlin.
[2] Bohlin T. and Graebe S.F. (1994). Issues in
nonlinear stochastic grey box identification.
Proceedings of the IFAC SYSID'94. Vol. 3, pp.
213-218.
[3] Bohlin T. (2001). A Grey Box Process
Identification Tool: Theory and Practice, IR-S3-
REG-0103, Royal Institute of Technology,
Stockholm, 2001.
[4] Hudson R.M. and Warning C.J. (1980). Factors
Influencing the Pickling Rate of Hot Rolled
Low-Carbon Steel in Sulfuric and Hydrochloric
Acids. Metal Finishing. Vol. 6, pp. 21-28.
[5] Hudson R.M. (1991). Pickling of Hot Rolled Strip:
An Overview. Iron and Steelmaker (I&S). Vol.
18, No. 9, pp. 31-39.
[6] Lindskog P. and Ljung L. (2000). Ensuring
Monotic Gain Characteristic in Estimated
Models by Fuzzy Model Structures. Automatica.
Vol. 36, pp. 311-317.
[7] Rao C.R. (1973). Linear Statistical Inference and Its
Applications, John Wiley, London.
[8] Sohlberg B. (1998). Supervision and Control for
Industrial Processes. Advances in Industrial
Control. Springer verlag. London.
[9] Sohlberg B. and Sernfält M. (2002). Grey Box
Modelling for River Control. Hydroinformatics.
Vol. 4, pp. 265-280.
[10] Sohlberg B. (2003). Grey Box Modelling for Model
Predictive Control of a Heating Process. Journal
of Process Control. Vol. 13, No. 3, pp. 225-
238.
[11] Sohlberg B. (2005). Hybrid Grey Box Modelling of
a Pickling Process. Control Engineering
practice. Volume 13, Issue 9, pp. 1093-1102.
[12] Thompson M. L. and Kramer M. A. (1994).
Modelling Chemical Processes Using Prior
Knowledge and Neural Networks. AIChE
Journal Vol. 40, No. 8, pp. 1328-1340.
[13] Tulleken H.J.A.F. (1989) Grey Box Modelling &
Identification Using Physical Knowledge and
Bayesian Techniques. IFAC Symposium on
Adaptive Control and Signal Processing,
Glasgow, pp. 591-598.
