Quarc Library Simulink

An excellent, high-performance real-time extension for Simulink—essential for anyone using Quanser hardware (e.g., QUBE, IP02, Aero) but too specialized and costly for general-purpose real-time tasks.

: Develop once and deploy to various operating systems (Windows, Linux, QNX) by simply changing the target configuration.

Connect the output of your controller to a block to send control signals to the motor or actuator. Step 3: Configure Target Settings Open the Simulink Configuration Parameters ( Ctrl+E ). Navigate to the Code Generation tab. quarc library simulink

Beyond simple input-output loops, QUARC scales effectively to handle complex, enterprise-level applications. Asynchronous Threading

If you have a specific Quanser workstation or controller architecture in mind (e.g., balancing an inverted pendulum or servo control), I can provide more tailored information. Let me know: Step 3: Configure Target Settings Open the Simulink

Engineers do not need to write device drivers. A control loop can be deployed to hardware using purely visual programming. Hard Real-Time Execution

With the model configured, building and deploying is remarkably simple. Starting with MATLAB R2021b, QUARC has its own dedicated tab in the Simulink toolstrip with buttons for building, deploying, and controlling the real-time executable. Clicking “Monitor & Tune” builds the model, generates C/C++ code, compiles it, downloads it to the target, and starts execution—all automatically. Asynchronous Threading If you have a specific Quanser

The key to QUARC's power is the . This specialized Simulink library provides a vast and comprehensive set of blocks that act as the interface between your Simulink model and the real world.

As real-time control systems continue to evolve, QUARC remains at the forefront of integration between simulation and physical implementation. Recent developments include enhanced support for deep learning workflows within Simulink, expanded visualization capabilities, and broader compatibility with emerging hardware platforms. The platform’s tight integration with MATLAB and Simulink ensures that as MathWorks adds new capabilities—such as reinforcement learning toolboxes, model predictive control, and automated code generation—QUARC can leverage these advances for real-time deployment.