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Документ New application of artificial neural network-based direct power control for permanent magnet synchronous generator(Національний технічний університет "Харківський політехнічний інститут", 2021) Akkouchi, Kamel; Rahmani, Lazhar; Lebied, RymaThis article proposes a new strategy for Direct Power Control (DPC) based on the use of Artificial Neural Networks (ANN-DPC). The proposed ANN-DPC scheme is based on the replacement of PI and hysteresis regulators by neural regulators. Simulation results for a 1 kW system are provided to demonstrate the efficiency and robustness of the proposed control strategy during variations in active and reactive power and in DC bus voltage. Methodology. Our strategy is based on direct control of instant active and reactive powers. The voltage regulator and hysteresis are replaced by more efficient and robust artificial neuron networks. The proposed control technique strategy is validated using MATLAB / Simulink software to analysis the working performances. Results. The results obtained clearly show that neuronal regulators have good dynamic performances compared to conventional regulators (minimum response time, without overshoots). Originality. Regulation of continuous bus voltage and sinusoidal currents on the network side by using artificial neuron networks. Practical value. The work concerns the comparative study and the application of DPC based on ANN techniques to achieve a good performance control system of the permanent magnet synchronous generator. This article presents a comparative study between the conventional DPC control and the ANNDPC control. The first strategy based on the use of a PI controller for the control of the continuous bus voltage and hysteresis regulators for the instantaneous powers control. In the second technique, the PI and hysteresis regulators are replaced by more efficient neuronal controllers more robust for the system parameters variation. The study is validated by the simulation results based on MATLAB / Simulink software.Документ Fuzzy maximum power point tracking compared to sliding mode technique for photovoltaic systems based on DC-DC boost converter(Національний технічний університет "Харківський політехнічний інститут", 2021) Nebti, Khalil; Lebied, RymaThis paper presents the amelioration of maximum power point tracking using fuzzy logic methods for photovoltaic system supplying a standalone system. Method. The main role of the maximum power tracking is to force the system for working at the maximum point for each change of meteorological conditions. The classic technique Perturb and Observe is more attractive due to its simple and high efficiency. Sliding mode is a non-linear control technique; characterised by robustness against the parameters change or disturbances, it gives a good maximum power operation under different conditions such as changing solar radiation and photovoltaic cell temperature. Novelty. Fuzzy logic tracking technique is treated. Fuzzy rules construction is based on Perturb and Observe behaviour when the appropriate disturbance step is produced in order to obtain a fast system with an acceptable precision. We use in our study 60 W photovoltaic panel associated to boost chopper converter in order to supply a standalone system. Results. As show in results figures using fuzzy maximum power point tracking the ameliorate performances especially the very low oscillation rate (nearly 0.6 W), and very acceptable response time 0.1 s.