Title: System identification for process control: recent experience and outlook

Authors: Yucai Zhu

Addresses: Faculty of Electrical Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands; Tai-Ji Control, Grensheuvel 10, 5685 AG Best, The Netherlands

Abstract: This work reports the development of an identification technology and its application to advanced process control (APC) in the refining/petrochemical industry. The author will introduce model predictive control (MPC) technology which, in the last two decades, has become the standard tool in industrial APC. Model identification plays a crucial role in MPC technology and it is also the most time consuming and difficult task in MPC projects and maintenance. Key issues of identification for MPC will be discussed. The so called ASYM method of identification is outlined that provides systematic solutions to problems from plant test to model validation. Based on the method, both off-line and online identification packages have been developed. A large-scale industrial application will be shown. Considerable benefits are obtained using the new identification technology: 1 reduction of identification test time and model building time by over 70% 2 higher model quality for control 3 easier in use. Then, several MPC relevant identification problems will be introduced. Based on his industrial experience, the author will provide an optimistic outlook of future APC/MPC and he will point out that identification technology can play a key role in next generation control systems.

Keywords: system identification; advanced process control; APC; model predictive control; MPC; oil refining; petrochemicals.

DOI: 10.1504/IJMIC.2009.024325

International Journal of Modelling, Identification and Control, 2009 Vol.6 No.2, pp.89 - 103

Available online: 31 Mar 2009 *

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