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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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2020-09-01.
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| Subjects: | |
| Online Access: | Get Fulltext |
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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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| Item Description: | https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/14018 |