QLabs Virtual Coupled Tanks

Part No. QLabs Virtual Coupled Tanks

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QLabs Virtual Coupled Tanks is a digital twin platform for process control education, enabling realistic liquid level control experiments with MATLAB/Simulink.

QLabs Virtual Coupled Tanks
Virtual platform for distance and blended undergraduate process control courses

QLabs Virtual Coupled Tanks is a fully instrumented, dynamically accurate digital twin of a Quanser Coupled Tanks system. It behaves in the same way as the physical hardware and can be measured and controlled using MATLAB®/Simulink® and other development environments. With QLabs Coupled Tanks, you can enrich your lectures and activities in traditional labs, or bring credible, authentic model-based lab experiences into your distance and online process control course.

QLabs Virtual Coupled Tanks is available as a 12-month, multi-seat subscription. The platform is compatible with the physical Coupled Tanks curriculum, which covers various modelling and control topics.

Same as the physical Coupled Tanks, the virtual system features a single pump and two tanks. Each tank is instrumented with a pressure sensor to measure the liquid level. The different outflow valves configurations allow to direct the flow of the liquid, while the flow rate can be changed by using outflow orifices of different diameters.

 

Specifications
App Download & Access to Subscription Quanser Academic Portal
App OS Compatibility Microsoft Windows 10 or Later
Required Software Curriculum designed for MATLAB and Simulink R2022a or later, with Python 3 compatibility
Minimum Specifications • Intel Core Ultra 5, Intel Core i5, Ryzen 5
• 8GB RAM
• Intel UHD, or Iris Xe integrated GPU
Recommended Specifications • Intel Core Ultra 7, Intel Core i7, Ryzen 7
• 16GB RAM
• Intel Iris Xe or Arc integrated GPU

• High-fidelity, credible lab experiences equivalent to use of physical lab equipment
• 12-month, multi-seat subscription
• Full access to system parameters through MATLAB®/Simulink®
• Curriculum covering modelling and control topics

• First-principles modelling
• Linearization
• Pole placement
• PID control
• Feed-forward

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