Rotor speed and resistance estimation using robust extended Kalman filter for sensorless vector control of induction motor drives

Rotor Speed Observer with Extended Current Estimator for Sensorless Control of Induction Motor Drive Systems

“…This confirms and validates the capability and effectiveness of the proposed control system to effectively estimate the correct position, , for the required rotor-winding flux orientation and maintain the rotor flux at a constant command value according to the presented IRFOC scheme. It can also be illustrated from Figure 13 that the q-axis stator-winding current component has effectively tracked its command values, which refers to its corresponding electromagnetic torque variations, shown in Figure 8, according to (7), which verifies the efficacy of the presented speedcontrol drive system.…”

“…Therefore, a speed encoder is needed for this drive system. In general, the speed sensor will add some issues for the adopted drive system such as increasing the overall cost, suffering from reliability issue, and the need of mechanical arrangements [7].…”

“…Generally, the accuracy level of IRFOC for IM speed-control drive systems is mainly based on the speed-signal measurement process using a speed sensor. However, there are several issues associated with using the sensor of speed, such as difficulties of maintenance, additional cost, reliability issue, and the requirement of an extended shaft for the sensor mounting arrangement [6,7]. The main challenge for researchers in this hot topic is to implement the whole drive system without any sensors for speed measurement.…”

“…The main challenge for researchers in this hot topic is to implement the whole drive system without any sensors for speed measurement. Thus, sensorless speed control strategies of induction motors have been given great attention nowadays [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22].…”

“…Various methods for the target of sensorless control of induction motors have been outlined which are based on either signal or model algorithms [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. However, these methods have been suffering from many defects such as the complexity [17][18][19][20], the integration issue for the flux prediction process at low speeds, or the need of an observer [18,19] or Kalman filter [7]. The influence of high-frequency interference on the machine behavior is the main drawback of the speed estimation algorithm-based signal injection [8,9].…”