DocumentCode :
2391294
Title :
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
Link To Document :
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