Pattern recognition in process control: an instrumental variable approach

Author

Toh, Kar-Ann ; Devanathan, R.

Author_Institution

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

fYear

1994

fDate

22-26 Aug 1994

Firstpage

966

Abstract

A pattern recognition approach to process identification is proposed in this paper. The process identification problem is first formulated using a nonlinear regression model which is solved according to the nonlinear least squares estimator. The method is then extended via the instrumental variable method to cater for possible correlation of residual error with a Jacobian function. The conditions for the identification are derived. Simulation results are also presented for the methods proposed

Keywords

closed loop systems; control system analysis; identification; image processing; least squares approximations; pattern recognition; process control; statistical analysis; Jacobian function; closed loop systems; instrumental variable approach; nonlinear least squares estimator; nonlinear regression model; pattern recognition; process control; process identification; process identification problem; residual error; simulation results; Control systems; Curve fitting; Instruments; Jacobian matrices; Least squares approximation; Nonlinear control systems; Open loop systems; Pattern recognition; Process control; Transfer functions;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '94. IEEE Region 10's Ninth Annual International Conference. Theme: Frontiers of Computer Technology. Proceedings of 1994

Print_ISBN

0-7803-1862-5

Type

conf

DOI

10.1109/TENCON.1994.369167

Filename

369167