Sensorless control of an automated guided vehicle based on extended Kalman filter observer

Abstract

In this paper, sensorless velocity and direction angle control of an automated guided vehicle (AGV) is performed by using extended Kalman filter (EKF) observer. The speed information of each motor is estimated by using armature current data measured from dc motor and command voltages applied to motors. The command voltages are used rather than the measured ones therefore only current sensors are needed. The estimated speeds are used to estimate velocity and direction angle of vehicle. The observed velocity and direction angle are used in the closed loop instead of measured ones for sensorless control of AGV. The experimental results show that the EKF observer can perfectly be implemented for sensorless control without using mechanical sensor.