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Performance analysis of Genetic Algorithm and Ant Colony Optimization dependent on PID Controller for Matrix Converter
Oral Presentation , Page 77-82 (6)
Volume Title: 2nd IEEE International Conference on Electronic Eng., Faculty of Electronic Eng., Menouf, Egypt, 3-4 July. 2021
Authors
ELECTRICAL DEPARTMENT, FACULTY OF ENGINEERING, ASSIUT UNIVERSITY, ASSIUT, EGYPT
Abstract
This study proposes a simulation of modeling and
implementation of a comparative study of two popular
Optimization techniques, i.e., Ant Colony Optimization (ACO)
and genetic algorithm (GA) for optimal control approach for
PID controller is developed for Direct Matrix Converter. It
converts power from three phases to three phases by a closed-loop control system. The PID controller gives real-time Control
in the closed-loop. The mathematical model establishes the
proper matrix converter circuits and MATLAB/SIMULINK for
RL Load aims to test the performance of the PID controllers.
The duty cycles are evaluated utilizing the modified Venturini
algorithm for the greatest voltage transfer ratio of the matrix
converter bidirectional switches.
implementation of a comparative study of two popular
Optimization techniques, i.e., Ant Colony Optimization (ACO)
and genetic algorithm (GA) for optimal control approach for
PID controller is developed for Direct Matrix Converter. It
converts power from three phases to three phases by a closed-loop control system. The PID controller gives real-time Control
in the closed-loop. The mathematical model establishes the
proper matrix converter circuits and MATLAB/SIMULINK for
RL Load aims to test the performance of the PID controllers.
The duty cycles are evaluated utilizing the modified Venturini
algorithm for the greatest voltage transfer ratio of the matrix
converter bidirectional switches.
Keywords
Matrix Converter; switch modulation strategy; PID Controller; Ant Colony Optimization (ACO); and genetic algorithm (GA)