A fully integrated dual-motor lab experiment, designed for advanced control research and aerospace applications, with QFLEX 2 myRIO Interface Panel.Includes User Manual, Quick Start Guide, Instructor and Student Workbooks, and Laboratory Guide, and pre-designed controllers. System Configuration: For operation, the system requires:- NI myRIO embedded device
Quanser AERO myRIO
The experiment is reconfigurable for various aerospace systems, from 1 DOF and 2 DOF helicopter to half-quadrotor. Integrating Quanser-developed QFLEX 2 computing interface technology, the Quanser AERO also offers flexibility in lab configurations, using a PC, or microcontrollers, such as NI myRIO, Arduino and Raspberry Pi. With the comprehensive course materials included, you can build a state-of-the-art teaching lab for your mechatronics or control courses, engage students in various design and capstone projects, and validate your research concepts on a high-quality, robust, and precise platform.
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The digital camera mounted overhead captures two-dimensional images of the plate and track coordinates of the ball in real time. Images are transferred quickly to the PC via a FireWire connection. Students can make the ball track various trajectories (a circle, for example), or even stabilize the ball when it is thrown onto the plate using the controller provided with the experiment.
QLabs Virtual Quanser AERO
Same as the physical Quanser AERO, the virtual system is a dual-rotor helicopter model that can be reconfigured for 1 DOF attitude, 2 DOF helicopter, or half-quadrotor experiments. Rotary encoders measure the angular position of the propeller DC motors, the speed of the motors is measured through a software-based tachometer.
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QLabs Virtual Coupled Tanks
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Quanser Controls Board
As automation and connected devices move from industry to commercial products and the home, an understanding of the design and implementation of control systems on hardware is essential. The courseware progression that accompanies the Quanser Controls Board begins with a grounding in the basics of modeling and control. Topics then transition into more complex strategies including optimal control, hybrid control, and digital control.
