In this paper, a robust active fault tolerant control (AFTC) scheme is proposed for induction motor drives (IMD) via input-output linearization control (IOLC) and nonlinear observer. In order to estimate the states and to reconstruct the faults, two different observers are used; a Luenberger observer (LO) and an extended kalman filter (EKF). Further we introduce feedback linearization strategy by choosing the output function as the rotor speed and flux square. To provide a direct comparison between these FTCs schemes, the performance is evaluated using the control of IMD under failures, variable speed, and variable parameters, finally the obtained results show that the proposed controller with the proposed observers provides a good trajectory tracking, and these schemes are robust with respect to faults, parameter variations, and external load disturbances for induction motor drive system.

In this paper, a robust active fault tolerant control (AFTC) scheme is proposed for induction motor drives (IMD) via input-output linearization control (IOLC) and nonlinear observer. In order to estimate the states and to reconstruct the faults, two different observers are used; a Luenberger observer (LO) and an extended kalman filter (EKF). Further we introduce feedback linearization strategy by choosing the output function as the rotor speed and flux square. To provide a direct comparison between these FTCs schemes, the performance is evaluated using the control of IMD under failures, variable speed, and variable parameters, finally the obtained results show that the proposed controller with the proposed observers provides a good trajectory tracking, and these schemes are robust with respect to faults, parameter variations, and external load disturbances for induction motor drive system.

In this paper, a robust active fault tolerant control (AFTC) scheme is proposed for induction motor drives (IMD) via input-output linearization control (IOLC) and nonlinear observer. In order to estimate the states and to reconstruct the faults, two different observers are used; a Luenberger observer (LO) and an extended kalman filter (EKF). Further we introduce feedback linearization strategy by choosing the output function as the rotor speed and flux square. To provide a direct comparison between these FTCs schemes, the performance is evaluated using the control of IMD under failures, variable speed, and variable parameters, finally the obtained results show that the proposed controller with the proposed observers provides a good trajectory tracking, and these schemes are robust with respect to faults, parameter variations, and external load disturbances for induction motor drive system.

This work is mainly on the detection of the bulk acoustic waves (BAWs), where we have compared two Lithium Niobate cuts (Y-Z and Y-X), during the propagation of the acoustic microwaves in the piezoelectric LiNbO3-substrate. In this paper, we have used the classification by Probabilistic Neural Network (PNN) as a tool for numerical analysis in which we classify all the values of the real and imaginary parts of the attenuation coefficient for the propagation velocity. This analysis can allow us to demonstrate the best possibility in utilization for the BAW generation. This study will be very interesting in modeling and realization of acoustic wave devices (ultrasound) based on the propagation of acoustic microwaves.

This work is mainly on the detection of the bulk acoustic waves (BAWs), where we have compared two Lithium Niobate cuts (Y-Z and Y-X), during the propagation of the acoustic microwaves in the piezoelectric LiNbO3-substrate. In this paper, we have used the classification by Probabilistic Neural Network (PNN) as a tool for numerical analysis in which we classify all the values of the real and imaginary parts of the attenuation coefficient for the propagation velocity. This analysis can allow us to demonstrate the best possibility in utilization for the BAW generation. This study will be very interesting in modeling and realization of acoustic wave devices (ultrasound) based on the propagation of acoustic microwaves.

In order to illustrate the criteria relating to static and dynamic performance, complexity of design, implementation and decoupling, a comparison was made between two asynchronous machine control techniques which are the direct torque control under the base of the SVM (DTC-SVM) and the predictive torque control (MPDTC). The results show the merits of these two control strategies with respect to the variations of the load setpoint for the torque and its influence on the speed and were obtained using a simulation program under the environment Matlab / Simulink

In order to illustrate the criteria relating to static and dynamic performance, complexity of design, implementation and decoupling, a comparison was made between two asynchronous machine control techniques which are the direct torque control under the base of the SVM (DTC-SVM) and the predictive torque control (MPDTC). The results show the merits of these two control strategies with respect to the variations of the load setpoint for the torque and its influence on the speed and were obtained using a simulation program under the environment Matlab / Simulink

In order to illustrate the criteria relating to static and dynamic performance, complexity of design, implementation and decoupling, a comparison was made between two asynchronous machine control techniques which are the direct torque control under the base of the SVM (DTC-SVM) and the predictive torque control (MPDTC). The results show the merits of these two control strategies with respect to the variations of the load setpoint for the torque and its influence on the speed and were obtained using a simulation program under the environment Matlab / Simulink

In order to illustrate the criteria relating to static and dynamic performance, complexity of design, implementation and decoupling, a comparison was made between two asynchronous machine control techniques which are the direct torque control under the base of the SVM (DTC-SVM) and the predictive torque control (MPDTC). The results show the merits of these two control strategies with respect to the variations of the load setpoint for the torque and its influence on the speed and were obtained using a simulation program under the environment Matlab / Simulink