Simulation of Variable Frequency Controlled AC Induction Motor Operating On Non-Linear Load

Avdeev, Boris A.; Vyngra, Aleksei V.

doi:10.1109/eiconrus49466.2020.9038963

Cited by 8 publications

(1 citation statement)

References 11 publications

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“…Other evolutionary biology-inspired techniques used by the GA include natural selection, reproduction, mutation, and crossover. The method is applied using the uniform selection strategy, which has an extremely low spread and no bias [31].…”

Section: Genetic Algorithmmentioning

confidence: 99%

African vulture optimizer algorithm based vector control induction motor drive system

Mohammed

Ismaiel

Elnaghi

et al. 2023

IJECE

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<span lang="EN-US">This study describes a new optimization approach for three-phase induction motor speed drive to minimize the integral square error for speed controller and improve the dynamic speed performance. The new proposed algorithm, African vulture optimizer algorithm (AVOA) optimizes internal controller parameters of a fuzzy like proportional differential (PD) speed controller. The AVOA is notable for its ease of implementation, minimal number of design parameters, high convergence speed, and low computing burden. This study compares fuzzy-like PD speed controllers optimized with AVOA to adaptive fuzzy logic speed regulators, fuzzy-like PD optimized with genetic algorithm (GA), and proportional integral (PI) speed regulators optimized with AVOA to provide speed control for an induction motor drive system. The drive system is simulated using MATLAB/Simulink and laboratory prototype is implemented using DSP-DS1104 board. The results demonstrate that the suggested fuzzy-like PD speed controller optimized with AVOA, with a speed steady state error performance of 0.5% compared to the adaptive fuzzy logic speed regulator’s 0.7%, is the optimum alternative for speed controller. The results clarify the effectiveness of the controllers based on fuzzy like PD speed controller optimized with AVOA for each performance index as it provides lower overshoot, lowers rising time, and high dynamic response.</span>

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Section: Genetic Algorithmmentioning

confidence: 99%

African vulture optimizer algorithm based vector control induction motor drive system

Mohammed

Ismaiel

Elnaghi

et al. 2023

IJECE

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Simulation and experimental validation of chaotic-billiards optimization algorithm for advanced variable speed drive

Elnaghi,

Ismaiel,

Mohammed

2023

Electr Eng

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To appropriately construct the proportional–integral control strategy for stability enhancement of the speed performance of induction motors and current waveform, this study describes a novel optimization approach for three-phase induction motor pumps speed drive. This work provides a novel chaotic-billiards optimizer (C-BO) method. These strategies were implemented in the same hardware with modifications in the control algorithm. Both simulation and experimental investigation are carried out, and a comparative analysis of the optimized parameters is presented. The system setup is prepared and simulated in the environment of MATLAB/Simulink. The same system has been presented experimentally. The laboratory experiment is carried out in the Smart Systems Co laboratory using simulators of induction motors designed and manufactured by the Lucas-Nuelle company. The asynchronous motor is controlled by 3 phase variable speed drive A1000 of Yaskawa Co. The "ActiveServo" software included ensures user-friendly operation and visualization of the measurement values. Experiment has validated the speed the effectiveness of C-BO. The speed control and flux control using C-BO have a fast response even under pump load and improvement in rising time by 41.65% as compared to GA. The novel optimization model C-BO has improvement in integral square error (ISE) of the three controllers by 38.91% as compared to genetic algorithm systems. Furthermore, the difficulty of developing both systems is the same. The C-BO algorithm stands out for its uncomplicated design, low requirement for design specifications, high rate of convergence, and minimal computational strain.

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Investigation of SEPS Electric Power Quality Indicators Based on Mathematical Simulation Models Control

Vyngra,

Chernyi,

Avdeev

et al. 2023

2023 Seminar on Electrical Engineering, Automation &Amp; Control Systems, Theory and Practical Applications (EEACS)

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Simulation of Variable Frequency Controlled AC Induction Motor Operating On Non-Linear Load

Cited by 8 publications

References 11 publications

African vulture optimizer algorithm based vector control induction motor drive system

African vulture optimizer algorithm based vector control induction motor drive system

Simulation and experimental validation of chaotic-billiards optimization algorithm for advanced variable speed drive

Investigation of SEPS Electric Power Quality Indicators Based on Mathematical Simulation Models Control

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