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Virtual sensing for dynamic industrial process based on localized linear dynamical system models with time-delay

Yougao Li1, Wenxue Han1, Weiming Shao1

  • 1Department of Chemical Equipment and Control Engineering, College of New Energy, China University of Petroleum (East China), Qingdao 266580, China.

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|July 9, 2022
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Summary
This summary is machine-generated.

This study introduces a localized linear dynamical system (LoLDS) framework to enhance virtual sensor reliability and accuracy. The new method effectively handles time delays and nonlinearities in industrial processes.

Keywords:
Dynamic industrial processGeneralization reliabilityLocalized linear dynamical systemVariable time delay optimizationVirtual sensor

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Area of Science:

  • Industrial Process Control
  • Data-Driven Modeling

Background:

  • Virtual sensors are crucial for real-time quality monitoring in industrial settings.
  • Linear dynamical systems (LDS) are widely used for virtual sensor development but face challenges with time delays and linearity assumptions.
  • Improving generalization reliability and expanding applicability to nonlinear processes remain key issues.

Purpose of the Study:

  • To propose a novel virtual sensing framework, localized LDS (LoLDS), addressing limitations of existing LDS models.
  • To enhance the accuracy and generalization reliability of dynamic virtual sensors, particularly in the presence of time delays and nonlinearities.
  • To develop an automated framework applicable to real-life industrial processes.

Main Methods:

  • The LoLDS framework incorporates process dynamics and nonlinearities at different scales without increasing model complexity.
  • Intelligent optimization of time delays and a diversified localization scheme are employed during the offline stage.
  • An adaptive online model switching mechanism selects the best LDS models for real-time prediction.

Main Results:

  • The LoLDS framework demonstrated improved generalization performance for dynamic virtual sensors.
  • Offline and online operations synergistically enhance prediction accuracy and reliability.
  • The framework is highly automated and shows promising results in real-world industrial applications.

Conclusions:

  • The LoLDS framework offers a robust solution for developing advanced dynamic virtual sensors.
  • It effectively addresses time delays and nonlinearities, broadening the applicability of LDS-based virtual sensing.
  • The proposed method holds significant potential for real-time quality control in industrial processes.