Supervisory System for Monitoring and Tuning PID Control in a Permanent Magnet Bearingless Machine
Bearingless Machine, Supervisory System, Digital Signal Processor, PID Control
Dynamic Stability
The operation of bearingless electric machines is inherently complex due to the need to simultaneously control the torque and the magnetic suspension forces of the rotor. Given the multitude of dynamic variables involved in this process, supervisory systems play a key role by providing real-time visual feedback and centralizing parameter management. Focusing on this demand, this study proposes the development of a supervisory system dedicated to monitoring and parameterizing the the Proportional, Integral, and Derivative (PID) control of a permanent magnet bearingless machine. The system is designed to receive and process data from a Digital Signal Processor (DSP), a Texas Instruments TMS320F28379D model. Based on this integration between the hardware and the interface, the research aims to optimize the tuning of the PID controllers to mitigate deviations in the rotor’s radial position and enhance dynamic stability, resulting in a platform designed for data analysis and continuous equipment operation.