Design of estimator for level monitoring using data driven model

Vighnesh Shenoy, K. V. Santhosh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A state observer estimates the state variables depending on the measurements of the output over a period for an observable system. Luenberger observers can be used when the sensor produces minimal noise. Whereas, for stochastic systems having measurement and process noise Kalman filters are more suitable. This paper reports a state observer model for a liquid level monitoring system using both Luenberger and Kalman methods. A CFD simulation is carried out to investigate the laminar type of water flow through an orifice meter with a definite pipe diameter, which aids in the calculation of pressure difference resulting in liquid level estimation.

Original languageEnglish
Title of host publicationProceedings of 2nd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages81-86
Number of pages6
ISBN (Electronic)9781728194912
DOIs
Publication statusPublished - 19-01-2021
Event2nd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2021 - Dubai, United Arab Emirates
Duration: 19-01-202121-01-2021

Publication series

NameProceedings of 2nd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2021

Conference

Conference2nd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2021
Country/TerritoryUnited Arab Emirates
CityDubai
Period19-01-2121-01-21

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management
  • Control and Optimization

Fingerprint

Dive into the research topics of 'Design of estimator for level monitoring using data driven model'. Together they form a unique fingerprint.

Cite this