Proportional Integral Derivative (PID) is the most popular controller used in automatic systems, because of its robustness, ability to adapt the behaviors of the system, making them converge toward its optimum. These advantages are valid only in the case of the linear systems, as they present poor robustness in nonlinear systems. For that reason, many solutions are adopted to improve the PID robustness of the nonlinear systems. The optimization algorithm presents an efficient solution to generate the optimums PID gains adapting to the system’s nonlinearity. The regulation speed in the Direct Torque Control (DTC) is carried out by the PID controller, which caused many inconveniences in terms of speed (overshoot and rejection time), fluxes, and torque ripples. For that, this work describes a new approach for DTC of the Doubly Fed Induction Motor (DFIM) powered by two voltage inverters, using a PID controller for the regulation speed, based on a Genetic Algorithm (GA), which has been proposed for adjustment and optimizing the parameters of the PID controller, using a weighted combination of objective functions. To overcome the disadvantages cited at the beginning, the new hybrid approach GA-DTC has the efficiency to adapt to the system’s nonlinearity. This proposed strategy has been validated and implemented on Matlab/Simulink, which is attributed to many improvements in DFIM performances, such as limiting speed overshoot, reducing response time and the rate of Total Harmonic Distortion (THD) of the stator and rotor currents, and minimizing the rejection time of speed and amplitude of the torque and flux ripples.
In recent years, regulating a wind energy conversion system (WECS) under fluctuating wind speed and enhancing the quality of the electricity provided to the grid has become a hard challenge for many academics. The current research provides a better control strategy to decrease the occurrence of chattering phenomena. Combined with the Maximum Power Point Tracking (MPPT) strategy and a pitch angle control, the control is possible to increase the performance and the efficiency of the Permanent Magnet Synchronous Generator (PMSG) based Wind Energy Conversion System. This study attempts initially to regulate the generator and the grid side converter to track the wind speed reference established by the MPPT algorithm. And secondly, to relieve the chattering problem associated with the conventional sliding mode control (CSMC), the proposed sliding mode control (PSMC) is based on a novel smooth continuous switching control. Besides, the suggested sliding mode control stability is confirmed using Lyapunov’s stability function. The complete system was evaluated in the MATLAB/Simulink (MathWorks, Natick, MA, USA) environment using a 2 MW PMSG’s power, under random fluctuations in the wind speed to show the suggested approach’s efficiency and robustness, which was then compared to the CSMC and other common approaches available in the literature. The simulation results reveal that the recommended sliding mode control approach delivers good speed, accuracy, stability, and output current’s ripple.
In This paper we present a new contribution of fuzzy logic for electrical machine control. We are interested to the control direction of the rotor flux applied to Doubly-Fed Induction Generators (DFIG)At first, the principle of operation and modeling are applied to the DFIG is developed and introduced. Thereafter, the Fuzzy approach is applied to the FOC control, to improve the performance of the machines.Finally, the simulation results of the two commands are validates on the environment Matlab / Simulink followed by a detailed analysis.
This paper presents a new contribution of the nonlinear control technique of electrical energy in a wind energy system. The nonlinear sliding mode technique used to control the powers of the DFIG-Generator is connected to the power grid by two converters (grid side and machine side). The proposed model is validated using tracking and robustness tests with a real wind speed. The control was developed under Matlab/Simulink, and the FPGA in the Loop technique was used to design the DFIG model. By employing a co-simulation, the purpose is to test the controller for the FPGA simulated model or system in its entirety. The results obtained by the cο-simulation show the efficiency of the proposed model in terms of speed and robustness with a rate THD = 0.95, and the proposed model of the sliding mode controller shows a significant improvement in the quality of energy produced by the wind system.
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