Grey wolf optimizer algorithm based real time implementation of PIDDTC and FDTC of PMSM
Abstract
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.
Full Text:
PDFDOI: http://doi.org/10.11591/ijpeds.v11.i3.pp1640-1652
Refbacks
- There are currently no refbacks.
Copyright (c) 2020 Osama M. Arafa, Said A. Wahsh, Mohamed Badr, Amir Yassin

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.