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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC)
Shuraiji, Ahlam Luaibi
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Fuzzy Logic Control and PID Controller for Brushless Permanent Magnetic Direct Current Motor: A Comparative Study Shuraiji, Ahlam Luaibi; Shneen, Salam Waley
Journal of Robotics and Control (JRC) Vol 3, No 6 (2022): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i6.15974

Abstract

Electrical machines based on permanent magnet material excitations have been applied in many sectors since they are distinguished by their high torque-to-size ratio and offer high efficiency. Brushless permanent magnetic direct current (BLPMDC) motors are one type of these machines. They are preferable over conventional DC motors. one of the main challengings of the BLPMDC motor drives is the inherited feature of nonlinearity. Therefore, a conventional PID controller would not be an efficient choice for the speed control of such motors. The object of this paper is to design an efficient speed control for the BLPMDC motor. The proposed controller is based on the Fuzzy logic technique. MATLAB/ Simulink has been employed to design and test the drive system. Simulations were carried out for three cases, the first without a controller, the other using conventional control, and the third using expert systems. The results proved the possibility of improving the engine's working performance using the control systems. They also proved that the adoption of expert systems is better than the traditional nonlinear systems. The simulation response shows that the Rise Time(tr) at PID equals 66.306ms, while it equals 19.530ms for the Fuzzy logic controller. Moreover, Overshoot for PID and Fuzzy logic controller are 6.989% and 1.531%, respectively. On the other hand, undershoot is equal to 1.788% and 11.924% for PID and Fuzzy logic controller, respectively.
Evaluation of Voltage/Frequency and Voltage Source Inverter Control Strategies for Single-Phase Induction Motors Using MATLAB Simulation Dakheel, Hashmia S.; Shneen, Salam Waley; Abdullah, Zainab B.; Shuraiji, Ahlam Luaibi
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23760

Abstract

There is a growing interest in studying the single-phase induction motor due to its wide use in many applications, the most important of which are domestic and industrial. A simulation model is built by implementing and running the model using MATLAB to identify the system behavior of the induction motor. To study and analyze the system behavior in different cases, it is proposed to implement and run the model in two ways: the first without control techniques and the second using control techniques. Tests are conducted according to a methodology based on scenarios that include all expected cases that can be assumed to suit real-time operation. To evaluate control strategies, the clear effect between their use and non-use must be demonstrated through clear measurement criteria to include response speed and performance improvement. In induction motor tests, the focus is on electrical and mechanical quantities and the transient and steady state of the system, including a 220-volt supply voltage and a 50 Hz frequency. The initial test case refers to using the model to simulate three cases: the first without load, the second with a constant load of one newton meter, and the third operating the motor as a pump by changing the load according to the pumping quantity and linked to the motor output. After conducting these tests, the different simulation results can be indicated in terms of the change in electrical and mechanical quantities over time during the proposed operating period. The results showed the high starting current that may affect the motor, and the response time for the motor to operate at the rated speed can be considered. Therefore, this requires the use of techniques to improve performance and provide response speed with a gradual increase in the starting current to protect the motor from high starting current. Voltage and frequency control techniques, as well as voltage-to-frequency ratio and another technique representing the voltage source inverter, were used. The results indicate a clear improvement through the stability of the motor by operating with a short response time compared to other cases and the specified rotational speed and specified torque, which shows a relatively high-efficiency performance.
Design and optimization of HTS flux-switching permanent magnet machine Shuraiji, Ahlam Luaibi; Al-ani, M.M.J.
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (393.251 KB) | DOI: 10.11591/ijpeds.v10.i4.pp1751-1757

Abstract

Flux-switching permanent magnet (FSPM) machine with high temperature superconductors (HTS) bulks located between the rotor poles to eliminate the flux leakage in the rotor, termed as (HTS-FSPM) machine has been proposed in this paper. Using genetic algorithm, the HTS and the conventional FSPM machines having the same size constraints and load conditions have been globally optimized for max. aveage torque. To highlight the advantages of the HTS-FSPM machine, a performance comparison between the conventional and HTS-FSPM machines has been presented. It is found that the HTS-FSPM machine can increase the torque by 27%, however, this comes with the expense of higher torque ripple and power losses.  
Analysis of Improve Performance and Dynamics of an Induction Motor using an Artificial Neural Network Controller and a Conventional Proportional Integral Derivative Controller Shuraiji, Ahlam Luaibi; Shneen, Salam Waley
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13820

Abstract

Systems vary depending on the changing operating conditions. Some include linear systems, which previous studies have proven can be controlled using conventional systems, while non-linear systems require expert and intelligent controllers. To verify this, the current study compares expert artificial neural networks (ANNs) with traditional PID controllers for controlling the rotational speed of an induction motor. Traditional PID controllers are simple and easy to implement, but they lack the ability to handle changing operating conditions and do not have the capacity to adapt to load fluctuations as expert systems such as neural networks do. They also have the ability to handle load disturbances and are considered more effective, efficient, and robust compared to traditional PID controllers. PID controllers are easy to adjust and simple in structure, and are widely used with linear industrial systems. PID controllers have degraded performance when the load changes, i.e., when the system is non-linear, their performance deteriorates. ANN, on the other hand, are characterized by their ability to adapt to varying conditions and changing loads. In non-linear systems, they have the ability to adapt and handle system disturbances. ANNs are expensive and require precise design, data for network architecture, and training. The feasibility of tracking induction motor speed is investigated using motor simulation models, conventional PID controllers, and expert neural networks, and the simulation results are analyzed and compared. The simulation results demonstrate that ANNs outperform PIDs in response speed and lower overshoot and undershoot limits under various operating conditions. From the above, it can be concluded that expert neural networks can effectively control and improve dynamic response of induction motors due to their adaptive and learning capabilities, and they can handle nonlinear systems such as changing load conditions. It is proposed to conduct simulation tests of an electric motor using MATLAB engineering software, by mathematically representing it using a transfer function according to characteristics suitable for applications similar to the proposed characteristics. Simulation tests are conducted for an open circuit system, a closed circuit system without control, and a closed circuit system with control. The second method involves self-tuning the conventional controller to achieve the best design by optimizing performance, response speed, overshoot rate, and rise time, according to the proposed operating algorithm. The results demonstrate the superiority of the neural network over conventional controllers.
Co-Authors Abdullah, Zainab B. Al-ani, M.M.J. Dakheel, Hashmia S. Salam Waley Shneen