This paper presents the design and implementation of a photovoltaic emulator, based on an accurate mathematical model of a photovoltaic panel, instead of the look-up table method. The latter requires more memory for increasing accuracy and considering all the desired environmental situations. Furthermore, the proposed approach takes into account the incidence solar angle, as an input parameter, to offer the possibility of evaluating daily losses for different values of tilt angle. The validation of the proposed emulator is carried out by comparing in real-time, both the studied panel output and the emulator output, under variable load, temperature, and irradiation levels. The emulator is able to operate online with connected solar radiation and temperature sensors or offline with recorded measurement vectors. The practical tests were performed on a prototype designed using a MATLAB C MEX S-function, dSPACE board 1104, and a controlled DC/DC converter. The results showed that the emulator was able to behave accurately as the studied photovoltaic panel.

The goal of this study was to figure out how to regulate an induction motor in a hybrid electric vehicle. Conventional combined vector and direct control induction motors take advantage of the advantages of vector control and direct torque control. It is also a method that avoids some of the difficulties in implementing both of the two control methods. However, for this method of control, the statoric current has a great wealth of harmonic components which, unfortunately, results in a strong undulation of the torque regardless of the region speed. To solve this problem, a five-level neutral point clamped inverter was used. Through multilevel inverter operation, the voltage is closer to the sine wave. The speed and torque are then successfully controlled with a lower level of ripple in the torque response which improves system performance. The analysis of this study was verified with simulation in the MATLAB/Simulink interface. The simulation results demonstrate the high performance of this control strategy.

In this paper, an adaptive fault tolerant control strategy is proposed to deal with the three pitch actuator faults in the large-scale wind turbines. Firstly, a simultaneous state and fault estimation was performed through a suitable LMI (linear matrix inequality) based optimal strategy. Hereafter, the new control law is designed using the previously estimated fault information. The actuator efficiency estimator uses as design parameters, respectively, the performance index γ against the wind and the learning rate Ξ. of the fault estimation algorithm. The study shows that the choice of the previous two parameters impacts the response time of the fault estimation and the correlation of the tracking error with the wind. The aim is to choose a small fault estimation response time while keeping a weak correlation between the tracking error and the wind turbulence noise. Finally, a tuning strategy is elaborated to choose the suitable γ and to match the reconfiguration objective.

In this paper, a robust vector control sensorless based on three Active Disturbance Rejection Controllers (ADRC) for an induction motor fed by a five-level cascaded H-bridge was developed. The estimation of rotor position is achieved using a Luenberger estimator. The proposed model considers the disturbances and the inaccuracies of the system and compensates them using the extended state observer of ADRC. Moreover, a five-level cascaded H-bridge inverter is the best topology to minimize the torque ripples and to improve the current output of IMunder control. The suggested control system was simulated under different conditions using MATLAB-Simulink. The results demonstrate the effectiveness and the robustness of the proposed system against disturbances such as variations of parameters and load torque.

An accurate method is proposed to track the maximum power point of a photovoltaic module. The method is based on the analytical value of the maximum power point voltage, determined from a mathematical model of the photovoltaic panel. The method has the advantage of accuracy without any oscillations, as with certain conventional methods. The algorithm has also the ability to track accurately the maximum power point under variable atmospheric conditions and load changes. Experimental results are presented to show the effectiveness of the method. The implementation of the method needs an online measurement of irradiance, panel temperature, and panel current and voltage.

In this paper, we propose a concept for estimating solar irradiation by measuring the current, the voltage and the temperature of a photovoltaic cell. The estimation of the solar irradiation is obtained by processing these measurements using a mathematical model of a photovoltaic cell, combined with a PI controller. Since the PV cell current is very sensitive to the irradiance level, the principle of the method is to force the photovoltaic model to reproduce the same current as that measured on the cell by applying an appropriate irradiance as input, for measured temperature and voltage. The appropriate irradiance, which is the output of the estimator, is provided by the PI controller in such way that the estimated current by the model follows exactly the measured current. The PI controller also ensures the self-calibration of the photovoltaic reference-cell depending on the temperature changes. The effectiveness of the proposed approach has been validated in simulation and on an experimental platform.