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Direct Torque Control (DTC) of induction motor drives is a well-established technique owing to features such as fast dynamic and insensibility to motor parameters. However, conventional DTC scheme, based on comparators and the switching table, suffers from large torque and flux ripples. To improve DTC performance, this study aims to propose and implement a sensorless finite-state predictive torque control using extended Kalman Filter in dSPACE environment.

This paper deals with the design of an extended Kalman filter for estimating the state of an induction motor model and for sensorless control of systems using this type of motor as an actuator. A complex-valued model is adopted that simultaneously allows a simpler observability analysis of the system and a more effective state estimation.

Simulation and experimental results reveal that the drive system, associated with this technique, can effectively reduce flux and torque ripples with better dynamic and steady state performance. Further, the proposed approach maintains a constant switching frequency.

The proposed speed observer have been developed and implemented experimentally under different operating conditions such as parameter variation, no-load/load disturbances and speed variations in different speed operation regions.