Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor
| Autor: | Said Benaggoune, Abdesselem Chikhi, Sebti Belkacem, Ghoulemallah Boukhalfa |
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| Rok vydání: | 2019 |
| Předmět: |
Computer science
Heuristic (computer science) 020208 electrical & electronic engineering MathematicsofComputing_NUMERICALANALYSIS Metals and Alloys General Engineering Particle swarm optimization 02 engineering and technology Star (graph theory) ComputingMethodologies_ARTIFICIALINTELLIGENCE ComputingMethodologies_PATTERNRECOGNITION Direct torque control Control theory Rise time Genetic algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing MATLAB computer Induction motor computer.programming_language |
| Zdroj: | Journal of Central South University. 26:1886-1896 |
| ISSN: | 2227-5223 2095-2899 |
| Popis: | This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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