Mustafa Naozad Taifor
Northern Technical University

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Active Disturbance Rejection and Model Predictive Control for Mitigating Non-Torque-Producing Currents and Harmonic Distortion in Six-Phase Permanent Magnet Synchronous Motor Rjwan Ahmed Al-Hamdany; Jameel Kadhim Abed; Mustafa Naozad Taifor; Sarah A. Mohammed; Ali Falih Challoob; Naseer T. Alwan; Salam J. Yaqoob
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16847

Abstract

The six-phase permanent magnet synchronous motor drives have high power density, fault tolerance, and reliability; however, conventional model predictive control is sensitive to load disturbances, unmodeled dynamics, and parameter uncertainties, which can lead to high non-torque-producing currents and harmonic distortion. To overcome these drawbacks, this work introduces an active disturbance rejection control approach with model predictive control (MPC). The research contribution is the combination of active disturbance estimation and compensation in the outer speed loop with the predictive current regulation in the inner current loop to improve disturbance rejection, reduce non-torque-producing currents, and improve the dynamic performance of the six-phase motor drives. The proposed scheme is modeled and validated through the MATLAB/Simulink simulation and compared to the standard MPC at the speed reference of 1000 rpm, load-torque steps of 10N·m applied in 0.05 s and 15N·m applied in 0.1 s, and motor inertia of 0.0048 kg·m². The simulation results show the current THD is reduced to 2.3% with the proposed strategy, and the average switching frequency is diminished to 10.8 kHz. The peak transient torque error is reduced from 0.65 N · m to 0.10 N · m, and steady-state torque ripple is lessened from 0.15 N·m to 0.02 N·m. Furthermore, the maximum speed deviation is lowered from about 150 rpm to 35 rpm, and the recovery time after a load disturbance is lowered from 40ms to 10ms. The obtained outcomes demonstrate the dominance of harmonic suppression, disturbance rejection, and dynamic efficacy of the proposed approach, indicating its prospective use in high-performance multiphase electric-drive systems.
A Load-following Particle Swarm Optimization-based Energy Management Technique for Integrating Electric Vehicles into a Renewable Microgrid System Zaid KH. Sadane; Mustafa Naozad Taifor; Arwa Amer Abdulkareem; Naseer T. Alwan
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16850

Abstract

The growing incorporation of Electric Vehicles (EVs) and Renewable Energy Sources (RES) into power systems presents new challenges and opportunities for the operation of microgrid (MG). To solve these limitations, this article presents a novel load-following particle swarm optimization (LF-PSO)-based energy management strategy (EMS) for on-grid renewable microgrids with electric vehicle (EV) integration. The proposed EMS optimally coordinates bidirectional power flow between the photovoltaic (PV) system, EV and MG thereby ensuring stable DC-link voltage regulation, improved power quality, efficient battery management, and enhanced overall system energy efficiency. The studied microgrid in this paper is composed of a 21 kW photovoltaic array, a 355 V lithium-ion battery (60 Ah), a 750 V DC bus, a 400 V utility grid, and an electric vehicle load. The assessment of the suggested EMS has been conducted in MATLAB/Simulink across diverse irradiation and load scenarios. The findings demonstrate that the suggested EMS shows improved efficacy, thus guaranteeing the management of the EV and PV system during all atypical circumstances. The obtained results are compared with the results obtained by the classical EMS methods such as proportional-integral (PI) and artificial intelligence (AI) techniques. The proposed LF-PSO strategy reduces the DC-link voltage overshoot from about 30% to less than 5%, which is a reduction of 83.3%, and improves the transient response, power quality, and renewable energy utilization compared with the conventional PI controller.