Control Systems commonly use "simple" sensors that directly quantify the required measure (e.g., angle, temperature, voltage, ...).
Today, however, more and more Control Systems rely on vision-based sensors (i.e., cameras) to allow for more complex and less intrusive control scenarios. In contrast to "simple" sensors, vision-based systems require additional processing power to extract the required measure from the camera images. As the Image Processing Algorithms are part of the control loop, their processing time (delay) and variation therein (jitter) has to be considered and monitored carefully. Furthermore, as the Vision-based sensing won't be 100% accurate, the resulting error has to be incorporated into the design flow.
To investigate these challenges, a test setup based on a Levitating Ball is being developed.

The goal of this thesis is to develop a Vision-based Control system for a Magnetic Levitating Ball (plant) on a regular Standard PC running Linux (controller).
The Levitating Ball will be interfaced to an FPGA-Board which allows access to the plant's sensor and actuator via Ethernet. Currently, the position of the Levitating Ball is sensed using a simple light barrier. This sensor shall now be replaced by a Camera combined with appropriate Image Processing Algorithms to serve as experimental setup.
For the sake of simplicity, both Image Processing and Control will be performed on a regular PC.