A new equivalent model of the induction motor with turn to turn fault on one phase has been developed. This model has been used to establish two schemes to estimate the severity of the short circuit fault. In the first scheme, the faulty model is considered as an observer, where a correction of an error between the measured and the estimated currents is the kernel of the fault severity estimator. However, to develop the second method, the model was required only in the training process of an artificial neural network (ANN). Since stator faults have a signature on symmetrical components of phase currents, the magnitudes and angles of these components were used with the mean speed value as inputs of the ANN

In this paper, an efficient and fast MPPT power control of photovoltaic systems based on backstepping approach is presented. The proposed control scheme consists of two cascade loops; in the first loop, the auto-scaling variable step-size perturb and observe MPPT technique estimates the reference voltage of all electrical load values. The robust backstepping controller has been adopted to remove steady state oscillations in the second loop. Further, the performance of proposed control system has been analyzed through dSPACE DS-1104 experimental validation with Isofoton photovoltaic module under real climatic conditions at Biskra (Algeria) region. The results obtained by the used controller averred a good improvement.

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.

A model reference adaptive system (MRAS) based speed estimator for sensorless induction motor (IM) drive is proposed in this paper. The MRAS is formed with flux rotor and the estimated stator current vector. The reference model utilizes measured current vector. On the other hand, the adjustable model uses the estimated stator current vector. The current is estimated through the solution of machine state equations. The performance of the estimator under regeneration is an important aspect, which is studied in this paper through the small signal analysis. In this paper, the principle and method of speed estimation and control set-up are described, as well as the results of an experiment that verified the effectiveness of the proposed method.

The objective of this paper is to develop a novel combined MPPT-pitch angle robust control system of a variable-speed wind turbine. The direct driven wind turbine using the permanent magnet synchronous generator (PMSG) is connected to the grid by means of fully controlled frequency converters, which consist of a pulse width-modulation PWM rectifier connected to an inverter via an intermediate DC bus. In order to maximize the exploited wind power and benefit from a wide range of the wind speed, a novel combined maximum power point tracking (MPPT)-Pitch angle control is developed using only one low cost circuit based on Neural Network (ANN), which allows the PMSG to operate at an optimal speed to extract maximum power when this last is lower than nominal power, and limit the extra power. To achieve feeding the grid with high-power and good quality of electrical energy, the inverter is controlled by (PWM) in a way to deliver only the active power into the grid, and thus to obtain a unit power factor. DC-link voltage is also controlled by the inverter. The dynamic and steady-state performances of the wind energy conversion system (WECS) are carried by using Matlab Simulink.

One of the most frequent faults in PMSM stator is the insulation failure due to the degradation of the main isolation in the motor winding. This paper is aimed at suggesting a dynamic model of PMSM with phase-to-phase fault based on an equivalent electric circuit model including the real form of back EMF. The faulty model is used for studying the machine behavior and extracting the fault signatures for diagnosis. Two diagnostic techniques the Spectral Analysis (ESA) and Extend Park's Vectors Approach (EPVA) based on frequency analysis are applied to detect this kind of fault.