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

Osama M. Arafa (Electronics Research Institute)
Said A. Wahsh (Electronics Research Institute)
Mohamed Badr (Ain-Shams university)
Amir Yassin (Electronics Research Institute)

International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol 11, No 3: September 2020

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.