This paper presents a direct torque control is applied for salient-pole double star synchronous machine without mechanical speed and stator flux linkage sensors. The estimation is performed using the extended Kalman filter known by it is ability to process noisy discrete measurements. Two control approaches using fuzzy logic DTC, and neural network DTC are proposed and compared. The validity of the proposed controls scheme is verified by simulation tests of a double star synchronous machine. The stator flux, torque, and speed are determined and compared in the above techniques. Simulation results presented in this paper highlight the improvements produced by the proposed control method based on the extended Kalman filter under various operation conditions.

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This paper presents an artificial neural networks controller devoted to improve the performance of direct torque control strategy of double star induction machine fed by two five-level diode-clamped inverters. The resulting control scheme presents enough degrees of freedom to control both torque and flux with very low ripple and high dynamics. Unfortunately, the diode-clamped inverter has an inherent problem of DC-link capacitors voltages variations. To overcome this problem, an artificial neural network based direct torque control with balancing strategy is proposed to suppress the unbalance of DC-link capacitor voltages. Simulations results are given to show the effectiveness and the robustness of the suggested control method.

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This work relates to the study of direct torque control based on space vector modulation applied on five-phase induction machine. It is well established that the conventional direct torque control using hysteresis comparators suffers from high torque ripples and variable switching frequency. The most common solution to those problems is the use of space vector modulation. In the other hand, this paper aims also to design an extended Kalman filter observer for speed/flux estimation, which improves not only the control performances by using a sensorless algorithm but also can lower the cost and increase the reliability of the system. Both theoretical principle and simulation results of the sensorless control method of multiphase drive will be conducted to verify the effectiveness of the proposed control approach.