Estimating the unknown time delay in chemical processes

Siamak Mehrkanoon*, Yuri A. W. Shardt, Johan A. K. Suykens, Steven X. Ding

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Although time delay is an important element in both system identification and control performance assessment, its computation remains elusive. This paper proposes the application of a least squares support vector machines driven approach to the problem of determining constant time delay for a chemical process. The approach consists of two steps, where in the first step the state of the system and its derivative are approximated based on the LS-SVM model. The second step consists of modeling the delay term and estimating the unknown model parameters as well as the time delay of the system. Therefore the proposed approach avoids integrating the given differential equation that can be computationally expensive. This time delay estimation method is applied to both simulation and experimental data obtained from a continuous, stirred, heated tank. The results show that the proposed method can provide accurate estimates even if significant noise or unmeasured additive disturbances are present. (C) 2016 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)219-230
Number of pages12
JournalEngineering Applications of Artificial Intelligence
Volume55
DOIs
Publication statusPublished - Oct 2016
Externally publishedYes

Keywords

  • Input-delay system
  • Least squares support vector machines
  • Continuous stirred tank
  • Open and closed-loop identification
  • FUNCTIONAL-DIFFERENTIAL EQUATIONS
  • PARAMETER-ESTIMATION
  • STATE
  • IDENTIFICATION
  • SYSTEMS

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