FLC-based PID controller tuning for sensorless speed control of DC motor

Abstract

This study addresses the sensorless speed control of a permanent magnet DC motor using non-ideal voltage and current sensors. A Proportional-Integral-Derivative (PID) type speed controller with Kalman Filter (KF) estimator was used and Integral of Absolute Error (IAE), peak overshoot and settling time were chosen as performance indices. Though KF helped reduce the noise, the PID controller gains tuned via MATLAB resulted in large peak overshoot and IAE with a relatively long settling time. In comparison, a Fuzzy Logic Controller (FLC) based PID (FLC-PID), tuned using genetic algorithms (GA), reduced the settling times by 75.98%, and the IAE and the maximum overshoot by 56.2% and 97.89% respectively. Compared to the conventional PID without KF, the FLC-PID radically improved the reference command speed tracking and sudden load changes disturbance rejection for the dc motor model.