A Sensorless Speed Control of DC Motor Based on an Adaptive Reference Model

This paper presents a new and simple approach to sensorless speed control based on adaptive reference model and applied to a permanent magnet DC motor. A suitable Kalman filter is used to estimate the motor speed necessary for the feedback loop. A reference model adaptive PID using the MIT rule for adapting the controller parameters is used to control the Motor. The model was implemented in MATLAB (Simulink) and the results obtained show a good estimate of the speed with a relative low error of 0.15% and good performance of the adaptive PID (response time, static error) which, despite the variation of Motor parameters manages to calculate optimum controller parameters online.