Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Permanent Magnet Synchronous Motor


Direct Torque Control for Permanent Magnet Synchronous Motor Based on NARMA-L2 controller

Huda B. Ahmed; Ali H. Almukhtar; Abdulrahim T. Humod

Engineering and Technology Journal, 2016, Volume 34, Issue 3, Pages 464-482

This paper investigates the improvement of the speed and torque dynamic responses of three phase Permanent Magnet Synchronous Motor (PMSM) using Direct Torque Control (DTC) technique. Different torques are applied to PMSM at different speeds during operation to ensure the robustness of the controller for wide torque variations. Optimal PI controller is used to modify the response of DTC. The optimal gains of PI controller are tuned by Particle Swarm Optimization (PSO) technique. Neural Network controller is called the Nonlinear Autoregressive-Moving Average (NARMA-L2) which is trained based on optimal PI controller (PI-PSO) data. The results show the superiority performance of using NARMA-L2 controller on PI-PSO controller for different speeds and load change. The overall simulation and design of the scheme are implemented Using MATLAB/Simulink program.

Study and Comparison The Performance of Sensorless Control of PMSM Drive System

Majid K. Al-Khatat; Ghphran Taha Ahmed Abd

Engineering and Technology Journal, 2014, Volume 32, Issue 10, Pages 2528-2547

Field oriented control space vector pulse width modulation (FOC- SVPWM) is one of the effective and modern methods for speed control of Permanent magnet synchronous motor (PMSM). A mathematical model and theoretical analysis of (FOC-SVPWM) driven a PMSM are presented .In this work, a control methods for PMSM using Model reference adaptive system (MRAS) are utilized to compare the performance behavior under conventional PI, Fuzzy PI, and Particle swarm optimization (PSO) control methods.
Extensive simulation results are presented using MATLAB/SIMULINK program which including (SVPWM generation, inverter, PMSM, the reference frame transformation and different PI controllers) as well as the estimation method using MRAS.
This work presents a comparative study to investigate the performance of PMSM based on MRAS when different load conditions are applied to PMSM and under three different controllers: the first controller is the Proportional-Integral (PI) based on classical trial and error method, the second controller is PI controller based on PSO technique for optimal gains tuning and thus improve the performance of the system. The obtained results show that an improvement in motor performance when using PI-PSO compared to classical PI controller. The third controller is Fuzzy-PI with scaling factor (gains) tuned by PSO technique. This method can improve the performance of the system compared with PI-PSO in terms of reducing steady state error, rising time, overshoot and smoother response to make this controller more robust to variation in load other than the rest motor controllers.