<p>The power supplied by photovoltaic DC–DC converter is affected by two factors, sun irradiance and temperature. Therefore, to improve the performance of the PV system; a mechanism to track the maximum power point (MPP) is required. Conventional maximum power point tracking approaches, such as observation and perturbation technique present some difficulties in identifying the true MPP. Therefore, intelligent systems including fuzzy logic controllers (FLC) are introduced for the maximum power point tracking system (MPPT). In this paper, we present a comparative study of the PV standalone system which is controlled by three techniques. The first one is conventional based on the observation and perturbation technique, the other are intelligent based on fuzzy logic according Mamdani and Takagi-Sugeno models. The investigations show that the fuzzy logic controllers provide the best results and Takagi-Sugeno model presents the lower overshoot value.</p>
This paper proposes RT-LAB platform for realtime implementation of Luenberger observer based on speed sensorless scalar control of induction motor. The observed shaft speed is derived from lyapunov's theory. It is shown by an extensive study that this Luenberger observer with PI anti-windup speed controller is completely satisfactory at (nominal, variable, reverse) speed references and it is also robust to load torque disturbance. The sensorless control algorithm along with the proposed Luenberger observer is modeled, built in the Host PC and successfully implemented in real-time using digital simulator OP5600. The experimental results observed in the GW-Instek digital oscilloscope's screen validate the effectiveness of the proposed Luenberger observer for speed sensorless scheme.
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