Pattern-based identification for process control applications

Kar Ann Toh, R. Devanathan

Research output: Contribution to journalArticle

9 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)641-648
Number of pages8
JournalIEEE Transactions on Control Systems Technology
Volume4
Issue number6
DOIs
Publication statusPublished - 1996

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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