Direct torque control based multi-level inverter and artificial neural networks of wind energy conversion system

Moualdia, Abdelhafidh; Boudana, Dj.; Bouchhida, Ouahid; Wira, Patrice

doi:10.1109/icmic.2016.7804199

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Every node uses constant weights to multiply its input signals, summarizes the result and maps the summition to a nonlinear function; then the result is transferred to its output and integrated an activation function is as illustrated in Figure 6. The ANN is illustrated in Figure 7, it may be trained to perform a particular role by changing the values of the interconnections (weights) between elements [23]. Usually, neural networks are modified or educated so that a given input contributes to a desired output [24].…”

Section: Fuzzy Control Rulesmentioning

confidence: 99%

Artificial intelligent techniques based on direct torque control of induction machines

Magdy

Abu-Zaid

Elwany

2021

IJPEDS

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The direct torque control (DTC) system, which is based on induction machine drive is a developed and simple control method. It allows high dynamic performance with very simple hysteresis control scheme; However, its disadvantages are high current, torque, and flux ripple. In this paper, DTC of induction machine drive has been improved by using the applications of artificial intelligence (AI) approaches to reduce the current, torque, and flux ripples and also get better performance of the machines. At the conclusion of this study, the outcomes of traditional DTC and artificial intelligent methods are compared. By the program MATLAB/SIMULINK, the modeling and simulation results of the DTC system for induction machine (IM) have been proposed.

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Section: Fuzzy Control Rulesmentioning

confidence: 99%

Artificial intelligent techniques based on direct torque control of induction machines

Magdy

Abu-Zaid

Elwany

2021

IJPEDS

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“…Besides the modifications of conventional control strategies and the combination with different techniques, some authors have used a strategy based on the multi-level converter instead of the classical ones [21,22]. This method is characterized by the delivered power maximization with the C-DTC drawback mitigation.…”

Section: Introductionmentioning

confidence: 99%

Advanced Fuzzy 12 DTC Control of Doubly Fed Induction Generator for Optimal Power Extraction in Wind Turbine System under Random Wind Conditions

et al. 2021

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A wind turbine (WT)-based doubly fed induction generator (DFIG) is the most often used generator in the wind conversion system market due to its advantages such as the ability of operating under variable wind speed and its high performance. However, nonlinear dynamical and parameter uncertainties of the DFIG make the controller design of this kind of system a challenging work. Thus, in this study, a novel control strategy was proposed to design the desired system dynamics, to highlight the efficacy of the proposed system, and to improve the performance of the closed-loop system. The proposed controller combines the twelve-sector direct torque control (12-DTC) and the fuzzy controller with modified rules to solve the limitations and shortcomings of the usual methods for the WT-DFIG system. All operation modes, successively and continually, were considered to reflect the true operation of WT-DFIG system subject to random wind speeds. The aims of this work was to ensure an optimal operation of the wind generator, extracting maximum power in the zone II of the WT characteristic, and limiting this power in its maximum value in the case (zone III), to transmit the power generated by the DFIG to the grid-side with minimum losses in the disturbances related to DFIG. Extensive numerical simulations were performed under MATALB/Simulink, where the proposed fuzzy twelve direct torque control (F12-DTC) was compared with conventional nonlinear controls: conventional DTC (C-DTC) and 12-DTC. The simulation results demonstrated clearly that the proposed one had the highest performance and robustness, with a significant reduction in rotor flux and electromagnetic torque ripples and better-generated power quality with low currents’ THD over the conventional strategies (C-DTC and 12-DTC).

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BLDC of Robotic Manipulators with Neural Torque Compensator based Optimal Robust Control

Belov

Khoa

Truong

2019

2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)

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Direct torque control based multi-level inverter and artificial neural networks of wind energy conversion system

Cited by 4 publications

References 12 publications

Artificial intelligent techniques based on direct torque control of induction machines

Artificial intelligent techniques based on direct torque control of induction machines

Advanced Fuzzy 12 DTC Control of Doubly Fed Induction Generator for Optimal Power Extraction in Wind Turbine System under Random Wind Conditions

BLDC of Robotic Manipulators with Neural Torque Compensator based Optimal Robust Control

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