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Related Concept Videos

Control Systems01:10

Control Systems

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Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
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Control Systems: Applications01:25

Control Systems: Applications

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Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
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Feedback control systems01:26

Feedback control systems

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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
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Cyclic Processes And Isolated Systems01:19

Cyclic Processes And Isolated Systems

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A thermodynamic system with zero heat exchange and work is an isolated system. For these systems, the internal energy remains constant.
In the case of a non-isolated system, the change in the internal energy is zero only if the process is cyclic. A thermodynamic process is considered cyclic if the system undergoes a series of changes and returns to its initial state. 
Consider a cyclic process that returns to its initial state, undergoing a four-step process. The heat transfer along each...
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Open and closed-loop control systems01:17

Open and closed-loop control systems

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Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
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Transfer Function in Control Systems01:21

Transfer Function in Control Systems

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The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
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Twin-Screw Extrusion Process to Produce Renewable Fiberboards
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Data-driven digital twin technology for optimized control in process systems.

Rui He1, Guoming Chen1, Che Dong1

  • 1Centre for Offshore Engineering and Safety Technology (COEST), China University of Petroleum (East China), No.66, Changjiang West Road, Qingdao, China.

ISA Transactions
|May 22, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a data-driven digital twin system for process industries to enhance safety and reduce maintenance challenges. The system integrates virtual modeling, monitoring, diagnosis, and control for robust fault management.

Keywords:
Data-driven methodsDigital twinOptimized control configurationProcess monitoring and diagnosisTennessee Eastman process

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Area of Science:

  • Process Engineering
  • Control Systems
  • Data-Driven Modeling

Background:

  • Process industries face increased accident risks and maintenance difficulties due to complex structures and harsh operating conditions.
  • Ensuring security in process systems is paramount for operational stability and safety.

Purpose of the Study:

  • To develop a data-driven digital twin system for automatic process applications.
  • To integrate virtual modeling, process monitoring, diagnosis, and optimized control into a cooperative architecture.
  • To enhance the safety and reliability of process operations through advanced fault management.

Main Methods:

  • Adaptive system identification for modeling virtual systems and residual signals using fault-free data.
  • Development of robust monitoring and diagnosis systems with improved performance indices to identify apparatus status.
  • Integration of soft-sensors, parameterization control, and model-matching reconfiguration into an optimized control strategy.

Main Results:

  • The proposed digital twin system effectively models unknown parameters and identifies apparatus status.
  • The integrated control configuration ensures stable and safe performance even during apparatus faults.
  • Simulations on the Tennessee Eastman benchmark process demonstrate the system's effectiveness under realistic fault scenarios.

Conclusions:

  • The data-driven digital twin system offers a robust solution for enhancing security and managing faults in process industries.
  • The cooperative architecture enables seamless integration of monitoring, diagnosis, and control functionalities.
  • The system contributes to improved operational safety and reduced maintenance challenges in complex industrial processes.