Grey wolf optimizer algorithm based real time implementation of PIDDTC and FDTC of PMSM

Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance pe...

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Vydáno v:International Journal of Power Electronics and Drive Systems Ročník 11; číslo 3; s. 1640
Hlavní autoři: Arafa, Osama M., Wahsh, Said A., Badr, Mohamed, Yassin, Amir
Médium: Journal Article
Jazyk:angličtina
Vydáno: Yogyakarta IAES Institute of Advanced Engineering and Science 01.09.2020
Témata:
Algorithms
Artificial intelligence
Computer simulation
Fuzzy control
Fuzzy logic
Heuristic methods
Optimization
Optimization techniques
Permanent magnets
Real time
ISSN:2088-8694, 2722-256X, 2088-8694
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Shrnutí:Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance permanent-magnet synchronous-motor (PMSM) drive. Grey wolf (GW) algorithms are used with the standard PID-based DTC (PIDDTC) and with the DTC with fuzzy logic (FDTC) based speed controllers. DSPACE DS1202 is utilized in the real-time implementation. MATLAB SIMULINK is used to simulate the steady-state (S.S.) and dynamic responses. The overall system is tested at different operating conditions for both simulation and practical work and all results are presented. A comparison between experimental and simulation results is performed and also a comparison between different applied intelligent techniques is introduced.
Bibliografie:ObjectType-Article-1
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ISSN:2088-8694
2722-256X
2088-8694
DOI:10.11591/ijpeds.v11.i3.pp1640-1652