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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Bibliographic Details
Published in:International Journal of Power Electronics and Drive Systems Vol. 11; no. 3; p. 1640
Main Authors: Arafa, Osama M., Wahsh, Said A., Badr, Mohamed, Yassin, Amir
Format: Journal Article
Language:English
Published: Yogyakarta IAES Institute of Advanced Engineering and Science 01.09.2020
Subjects:
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
Online Access:Get full text
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Summary: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.
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ISSN:2088-8694
2722-256X
2088-8694
DOI:10.11591/ijpeds.v11.i3.pp1640-1652