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Parameterizing V-notch Weir Equations for Flow Monitoring in a Drainage Control Structure
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Sliding Mode Observer Design for decentralized multi-phase flow estimation.

Abolfazl Varvani Farahani1, Soroush Abolfathi2

  • 1Faculty of Engineering, Shahid Beheshti University, Tehran, Iran.

Heliyon
|February 24, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces two Sliding Mode Observer (SMO) schemes for accurate multi-phase flow measurement, enhancing system understanding and operation. Both methods proved robust and efficient for estimating fluid density, velocity, and phase fractions in complex industrial processes.

Keywords:
DisturbanceMulti-phase flow measurementSliding Mode ObserverUncertainty quantification

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Area of Science:

  • Engineering
  • Control Systems
  • Fluid Dynamics

Background:

  • Robust flow measurement in multi-phase systems is crucial for environmental, energy, and industrial processes.
  • Nonlinearity and spatiotemporal variability in multi-phase flows present significant measurement challenges.
  • Accurate state estimation is vital for the design and operation of these complex systems.

Purpose of the Study:

  • To propose two Sliding Mode Observer (SMO) schemes for state estimation in decentralized multi-phase flow measurement.
  • To address challenges posed by interconnections treated as bounded disturbances (SMOD) or uncertainties (SMOU).
  • To validate the observers' theoretical validity and numerical applicability using real-life case study data.

Main Methods:

  • Development of two Sliding Mode Observer (SMO) schemes: SMOD (disturbance) and SMOU (uncertainty).
  • Utilizing MATLAB and dynamic HYSYS for numerical simulations with field-based multi-phase flow measurement data.
  • Employing Lyapunov-Krasovsky functions to ensure asymptotic stability and improve observer performance.

Main Results:

  • Both SMO schemes accurately estimated multi-phase fluid specifications (density, velocity, volume phase fraction).
  • The proposed observers demonstrated computational efficiency, fast transient response, and low steady-state error.
  • SMOU achieved superior performance with a Root Mean Square Error (RMSE) of 0.24%, compared to SMOD's 0.46%.

Conclusions:

  • The developed Sliding Mode Observers are theoretically sound and numerically applicable for multi-phase flow measurement.
  • Both SMOD and SMOU schemes provide high-precision state estimation in finite time, outperforming traditional methods.
  • The study confirms the robustness and effectiveness of SMO for complex decentralized multi-phase flow systems.