Sensorless speed control of DC motor using EKF estimator and TSK fuzzy logic controller

In this article, sensorless speed control of DC motor has been proposed using the extended Kalman filter (EKF) estimator and Takagi-Sugeno-Kang (TSK) fuzzy logic controller (FLC). In the industry, high-cost measurement systems/sensors are necessary for better controlling and monitoring, which can be replaced by a sensorless control technique to reduce the cost, size and increase system reliability and robustness. EKF has been used to perform the sensorless speed control by estimating the speed of the DC motor using the armature current only and TSK-FLC is used to reduce the effect of motor parameter variation and load torque nonlinearity in close loop speed control for various speed references. The performance of EKF-based TSK-FLC is compared with EKF-based PID controller. The time-domain specification and absolute error performance indices indicate that EKF-based TSK-FLC is superior to the EKF-based PID under similar conditions. The proposed system is executed in the MATLAB/Simulink environment, and sensorless speed control of DC motor prototype model has been developed for validating the proposed technique with the help of a micro-controller.