A soft sensor for estimation of in-flow rate in a flow process using pole placement and kalman filter methods

Research output: Contribution to journalArticle

Abstract

This article reports the design of a soft sensor for estimation of in-flow to the control valve in a flow process. The objective of the proposed work is to design and compare the performance of pole placement and Kalman filter-based observers. The observer is designed to estimate the in-flow from the measured out-flow. A mathematical model is derived for the considered physical plant using the system identification technique. An observer is designed using Pole Placement and Kalman Filter methods from the derived plant model. The obtained observer is implemented on a real-life setup for estimation of the in-flow rate. Results obtained from the designed observers are then analyzed to select the better observer. Comparison of performance based on results from Kalman Filter and Pole Placement method of observers shows that the former is more accurate, whereas the computation time is smaller in the latter. Results achieved from the designed soft sensor are verified using an electromagnetic flowmeter, and the results have a root-mean-square percentage error of 0.79%..

Original languageEnglish
JournalMachines
Volume7
Issue number4
DOIs
Publication statusPublished - 01-01-2019

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Soft Sensor
Pole Placement
Filter Method
Kalman filters
Flow Rate
Kalman Filter
Observer
Poles
Flow rate
Sensors
Flowmeters
Mean square error
Identification (control systems)
Mathematical models
System Identification
Mean Square
Percentage
Roots
Mathematical Model

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

Cite this

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title = "A soft sensor for estimation of in-flow rate in a flow process using pole placement and kalman filter methods",
abstract = "This article reports the design of a soft sensor for estimation of in-flow to the control valve in a flow process. The objective of the proposed work is to design and compare the performance of pole placement and Kalman filter-based observers. The observer is designed to estimate the in-flow from the measured out-flow. A mathematical model is derived for the considered physical plant using the system identification technique. An observer is designed using Pole Placement and Kalman Filter methods from the derived plant model. The obtained observer is implemented on a real-life setup for estimation of the in-flow rate. Results obtained from the designed observers are then analyzed to select the better observer. Comparison of performance based on results from Kalman Filter and Pole Placement method of observers shows that the former is more accurate, whereas the computation time is smaller in the latter. Results achieved from the designed soft sensor are verified using an electromagnetic flowmeter, and the results have a root-mean-square percentage error of 0.79{\%}..",
author = "Navada, {Bhagya R.} and Venkata, {Santhosh K.} and Swetha Rao",
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AU - Navada, Bhagya R.

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N2 - This article reports the design of a soft sensor for estimation of in-flow to the control valve in a flow process. The objective of the proposed work is to design and compare the performance of pole placement and Kalman filter-based observers. The observer is designed to estimate the in-flow from the measured out-flow. A mathematical model is derived for the considered physical plant using the system identification technique. An observer is designed using Pole Placement and Kalman Filter methods from the derived plant model. The obtained observer is implemented on a real-life setup for estimation of the in-flow rate. Results obtained from the designed observers are then analyzed to select the better observer. Comparison of performance based on results from Kalman Filter and Pole Placement method of observers shows that the former is more accurate, whereas the computation time is smaller in the latter. Results achieved from the designed soft sensor are verified using an electromagnetic flowmeter, and the results have a root-mean-square percentage error of 0.79%..

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