Open AccessSpeed control of brushless de motor using Ant Colony Optimization
Author(s) -
Bonzou A. Kouassi,
Yiming Zhang,
Mesmin J. Mbyamm Kiki,
Sié Ouattara
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/431/1/012022
Subject(s) - ant colony optimization algorithms , dc motor , pid controller , computer science , control theory (sociology) , metaheuristic , key (lock) , control engineering , control (management) , engineering , artificial intelligence , temperature control , computer security , electrical engineering
DC motor has as a key aspect of industrial applications. Thus, due to their high performance, BLDC motors are preferred as a small horsepower motor. However, it is hard to acquire the good controlling performance with traditional tuning approaches in order to solve the speed control. This paper provides an approach of determining the optimum control parameters of PID for the BLDC speed control using the Ant Colony Optimization (ACO), which is an intelligent algorithm based on feeding behavior of the swarm. The efficiency and validity of the design method based on ACO are shown in the Simulation outcomes.