Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections

Permanent URI for this collectionhttps://hdl.handle.net/20.500.13091/3

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Citation - Scopus: 20
Analysis and Investigation of Different Advanced Control Strategies for High-Performance Induction Motor Drives
(Universitas Ahmad Dahlan, 2020) Farah, Nabil; Talib, Hairul Nizam; Ibrahim, Z.B.; Abdullah, Q.; Aydoğdu, Ömer; Rasin, Z.; Lazi, J.M.
Induction motor (IM) drives have received a strong interest from researchers and industry particularly for high-performance AC drives through vector control method. With the advancement in power electronics and digital signal processing (DSP), high capability processors allow the implementation of advanced control techniques for motor drives such as model predictive control (MPC). In this paper, design, analysis and investigation of two different MPC techniques applied to IM drives; the model predictive torque control (MPTC) and model predictive current control (MPCC) are presented. The two techniques are designed in Matlab/Simulink environment and compared in term of operation in different operating conditions. Moreover, a comparison of these techniques with field-oriented control (FOC) and direct torque control (DTC) is conducted based on simulation studies with PI speed controller for all control techniques. Based on the analysis, the MPC techniques demonstrates a better result compared with the FOC and DTC in terms of speed, torque and current responses in transient and steady-state conditions. © (2020). All rights reserved.
Citation - Scopus: 5
Fuzzy Membership Functions Tuning for Speed Controller of Induction Motor Drive: Performance Improvement
(Institute of Advanced Engineering and Science, 2021) Farah, Nabil; Talib, Hairul Nizam; Ibrahim, Z.B.; Abdullah, Q.; Aydoğdu, Ömer; Lazi, J.M.; Isa, Z.
Fuzzy logic controller (FLC) has gained high interest in the field of speed control of machine drives in both academic and industrial communities. This is due to the features of FLC of handling non-linearity and variations. FLC system consists of three main elements: Scaling factors (SFs), membership functions (MFs), and rule-base. Fuzzy MFs can be designed with different types and sizes. For induction motor (IM) speed control, (3x3), (5x5) and (7x7) MFs are the most used MFs sizes, and normally designed based on symmetrical distribution. However, changing the width and peak position of MFs design enhance the performance. In this paper, tuning of MFs of FLC speed control of IM drives is considered. Considering (3x3), (5x5) and (7x7) MFs sizes, the widths and peak positions of these MFs are asymmetrically distributed to improve the performance of IM drive. Based on these MFs sizes, the widths and peak positions are moved toward the origin (zero), negative and positive side that produces a controller less sensitive to the small error variations. Based on simulation and performance evaluations, improvement of 5% in settling time (Ts), 0.5% in rise time and 20% of steady-state improvement achieved with the tuned MFs compared to original MFs. © 2021 Institute of Advanced Engineering and Science. All rights reserved.
Citation - Scopus: 6
Optimizing Battery Energy Storage and Solar Photovoltaic Systems for Commercial Buildings in Malaysia: a Case Study
(Institute of Electrical and Electronics Engineers Inc., 2023) Hossain, J.; Shareef, H.; Hossain, M.A.; Manojkumar, R.; Abdullah, Q.; Al-Masoodi, A.H.H.
In this study, a combination of a battery energy storage (BES) and a solar photovoltaic (PV) system is proposed to reduce peak demand and energy costs in a commercial building in Malaysia. The sizing of the BES and PV systems is found optimally by considering the net present cost of both systems and energy cost over a 20-year lifespan. Data on solar irradiance, ambient temperature, load patterns, Malaysian power rates, and grid export limitations are used to determine the optimal sizes of the BES and PV systems. The case study indicates that optimal BES and PV systems reduce the energy cost by 17.81% and decrease annual energy consumption by 19.57% and peak demand by 11.72%. 11,449 kWh of energy is exported to the grid. The study provides a general method for commercial building owners in Malaysia to find the BES and PV system sizes optimally. The results are validated and tested using MATLAB. © 2023 IEEE.
Citation - WoS: 4
Citation - Scopus: 6
Sensorless Speed Control of Induction Motor Drives Using Reinforcement Learning and Self-Tuning Simplified Fuzzy Logic Controller
(Institute of Electrical and Electronics Engineers Inc., 2024) Abdullah, Q.; Farah, N.; Ahmed, M.S.; Shah, N.S.M.; Aydogdu, O.; Talib, M.H.N.; Al-Moliki, Y.M.
Fuzzy logic controls (FLCs) have emerged as a promising solution for speed regulation in induction motor (IM) drives, offering adaptability to non-linearities, parameter variations, and external disturbances. However, conventional FLCs with fixed parameters and a huge number of rules can limit adaptiveness and increase system complexity, leading to deteriorated performance and high computational requirements. Moreover, reliance on costly encoders in traditional sensor-based IM drives introduces measurement errors and contributes toward the overall cost. To tackle these challenges, this paper proposes an integrated sensorless IM drive with a simplified self-tuning FLC (ST-FLC) and data-driven reinforcement learning (RL) for speed estimation. By employing a simplified 9-rule FLC instead of an intensive 49-rule counterpart and integrating a simple self-tuning mechanism based on mathematical equations, adaptiveness is maintained while computational overhead is reduced. Furthermore, the adoption of RL-based sensorless speed estimation eliminates reliance on encoder data, offering a cost-effective and computationally efficient alternative. Unlike conventional sensorless methods, the proposed sensorless-RL approach is data-driven and does not rely on motor parameters, leveraging a pre-trained policy for efficient speed estimation. Validation through simulation and experimentation on the dSPACE DS1104 platform demonstrates the efficacy of the proposed ST-FLC Sim 9-rule with sensorless RL. The method showcases accurate speed estimation, with simulation results comparable to standard 49-rule FLC and superior experimental performance. Significant computational time reduction is achieved with the proposed approach, resulting in a notable improvement in experimental performance metrics. Specifically, reductions of 50.5%, 20.4%, 15%, and 14.9% in settling time, current ripples, torque ripples, and current harmonics, respectively, underscore the practical benefits of the proposed integrated ST-FLC Sim 9-rule with sensorless-RL IM drive system. Authors

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Browsing Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections by Author "Abdullah, Q."