Sensor fault detection, isolation and system reconfiguration based on extended Kalman filter for induction motor drives

Induction motors (IMs) have been extensively used in industrial applications because of their inexpensiveness, ruggedness and reliability. Generally, to improve the performance of IM drives, one position sensor, one DC-link voltage sensor and at least two AC current sensors are necessary. However, failure of any of these sensors can cause degraded system performance or even instability. Consequently, it is very important to develop a sensor fault resilient control system for IMs drives so that continuous and normal operation is maintained even in cases of sensor faults. This study proposes a compact and robust sensor fault detection, isolation and system reconfiguration algorithm based on extended Kalman filter and reduced number of adaptive observers. A comprehensive set of experimental results are provided to verify the effectiveness of the proposed algorithm.