Pattern-based identification for process control applications

Author

Toh, Kar-Ann ; Devanathan, R.

Author_Institution

Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore

Volume

4

Issue

6

fYear

1996

fDate

11/1/1996 12:00:00 AM

Firstpage

641

Lastpage

648

Abstract

In this paper, a pattern-based approach to process identification is presented. The process identification problem is formulated using a nonlinear regression model. An algorithm is proposed based on the modified Gauss-Newton search for a least squares estimate, and the condition for the identification is derived. The algorithm is extended via the instrumental variable method to cater for possible correlation of residual error with a Jacobian function. Simulation results are presented to support the theoretical development for a typical range of industrial processes. The proposed method is also compared favorably with methods existing in the literature

Keywords

Jacobian matrices; closed loop systems; identification; least squares approximations; pattern recognition; process control; transfer functions; Gauss-Newton search; Jacobian function; closed loop systems; first order plus dead time models; identification; industrial processes; instrumental variable method; least squares estimate; nonlinear regression model; pattern-based method; process control; residual error; transfer function; Control systems; Curve fitting; Instruments; Jacobian matrices; Least squares approximation; Least squares methods; Newton method; Pattern recognition; Process control; Recursive estimation;

fLanguage

English

Journal_Title

Control Systems Technology, IEEE Transactions on

Publisher

ieee

ISSN

1063-6536

Type

jour

DOI

10.1109/87.541693

Filename

541693