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This paper designs a fractional order PID direct torque control strategy for permanent magnet synchronous machine (PSMS) based on on fractional calculus. The fractional order controller to control the speed of the machine was synthesized, referring to Bode's ideal transfer function. In the controller, the fractional order integrator was approximated by Charef's method. The fractional PID order control was compared with classical PID control, showing that the former has the better accuracy and robustness. Finally, MATLAB/ SIMULINK simulation proved the advantages of our control strategy under oscillating torque load or magnetic field.

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In order to better adapt to the variation in solar irradiation and to improve the efficiency of the photovoltaic generator, i.e. to maximize the power delivered to the grid. Several criteria's for optimizing the efficiency of the photovoltaic system have been applied. Among them, the algorithms for tracking the optimal operating point of the photovoltaic panels that called Maximum Power Point Tracking (MPPT). In this article, a PV generator (GPV) has been connected to the power grid, as a result, direct consequence is in the deterioration of the voltage wave and thus the quality level of the energy supplied to the consumers. To overcome these problems of harmonic pollution, active power filtering is proposed as an efficient solution to improve grid power quality. This paper therefore proposes to examine the characteristics of an association between a photovoltaic generator (PVG) that aims at injecting active power into the electrical grid and a parallel active filter that has the task of eliminating disturbances present in this grid. The theory of the twophase method with Adaline harmonic extraction is applied for the extraction of the reference currents according to the DQ reference frame. Finite set mode predictive current control (FS-MPCC) applied on PAF has been proposed in order to compensate undesirable harmonic, and reactive power resulting from a non-linear load. A Global Maximum Power Point Tracking (GMPPT) algorithm based Adaline method has been suggested for extracting power from PVG. A simulation under Matlab/Simulink of the global system proves the robust performance capability of the suggested Adaline Neuro-Predictive (ANP) control to simultaneously provide harmonic current compensation, power factor correction and solar power energy injection into the grid.

This research article proposes the optimization of a grid-connected photovoltaic system based on the PV emulator (PVE), the Boost converter, and a single-phase full-bridge inverter. The main objective is to track and extract the highest amount of power from the PV system working under variable solar irradiation while reducing losses and time response in each stage of the converter. As none, the main flaw of the classical maximum power point tracking algorithm (MPPT) is its performance. The control law design is based on a PI controller in the PVE, a meta heuristic whale optimization algorithm (WOA) in the MPPT, and a reduced switching finite set model predictive control (RS-FS-MPC) for the single-phase full-bridge inverter. The proposed control techniques inherit the property of robustness and successfully deal with the nonlinear behavior of the system. The performance validation and effectiveness of the proposed control techniques is supported by MATLAB/SIMULINK simulations and is also verified experimentally on various systems carried out under varying solar irradiation.