Malek Omar - Academia.edu (original) (raw)

Papers by Malek Omar

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)

2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)

This paper presents the design and simulation of a single-phase inverter for Uninterruptible Powe... more This paper presents the design and simulation of a single-phase inverter for Uninterruptible Power Supply (UPS) using the Verilog Hardware Description Language (HDL) co-simulation by interfacing MATLAB/Simulink and ModelSim. The PWM signal was produced by comparing Sine Wave and Triangular Wave digitally generated by Verilog HDL. The analog and digital of the UPS circuit were simulated in MATLAB/SIMULINK and ModelSim Altera software, respectively. The digital controller was simulated using cosimulation tools in MATLAB/SIMULINK. As system developers and researchers work on the same platform, it reduces the required time required in translating the technical specifications into functional specifications. ModelSim works as HDL (Hardware Description Language) simulator. The designed circuit and obtained simulation results are presented in the paper to confirm the performance of digital implementation for this single-phase UPS system.

2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 2021

This project is a development of apps software that can design and analyzing the grounding of the... more This project is a development of apps software that can design and analyzing the grounding of the AC substation based on several conditions by using Android Studio software according to the IEEE Std. 80–2000. Six types of grids that has been developed are square, rectangular and L-shaped where all types with and without ground rod. The percentage difference obtained for all cases are less than 10 %. The application is compatible to be used for education and industry purposed. To make sure the design is safe, the comparable values such as Em and Es must be less than Etouch and Estep value. This app can be used with shortened time to design and verify the grounding system of the AC substation. It is fast, robust, and accurate. The design app is very important for every consultant as it is easy to use compared to manually calculation.

This paper proposes a speed control design of Permanent Magnet Synchronous Motor (PMSM) using Fie... more This paper proposes a speed control design of Permanent Magnet Synchronous Motor (PMSM) using Field Oriented Control (FOC). The focus is to design a speed control using Takagi — Sugeno Fuzzy Logic Control (T-S FLS). These systems will replace the conventional method which is proportional-integral (PI). The objective of this paper is to study the T—S Fuzzy Inference System (FIS) speed regulator and acceleration observer for PMSM. The scope of study basically is to design and analyse the Takagi Sugeno FLC and the PMSM. This paper also will describe the methodology and process of modelling the PMSM including data analysis. The simulation work is implemented in Matlab-Simulink to verify the control method. The effectiveness of this proposed control method was confirmed through various range of speed and torque variation.

Indonesian Journal of Electrical Engineering and Computer Science, 2020

Deep Learning has ignited great international attention in modern artificial intelligence techniq... more Deep Learning has ignited great international attention in modern artificial intelligence techniques. The method has been widely applied in many power system applications and produced promising results. A few attempts have been made to classify fault on transmission lines using various deep learning methods. However, a type of deep learning called Long Short-Term Memory (LSTM) has not been reported in literature. Therefore, this paper presents fault classification on transmission line using LSTM network as a tool to classify different types of faults. In this study, a transmission line model with 400 kV and 100 km distance was modelled. Fault free and 10 types of fault signals are generated from the transmission line model. Fault signals are pre-processed by extracting post-fault current signals. Then, these signals are fed as input to the LSTM network and trained to classify 10 types of faults. The white Gaussian noise of level 20 dB and 30 dB signal to noise ratio (SNR) is also ad...

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 2021

As technology advanced, electrical interruption or disturbance still becomes a significant proble... more As technology advanced, electrical interruption or disturbance still becomes a significant problem in power systems. A fault is one example of electrical disturbance or power failure in a power system. In order to recover the system, the fault must be detected, classify and locate to eliminate as fast as possible. Four types of fault occur in the transmission line. Those four types are Line-to-Ground Fault (L-G), Line-to-Line Fault (L-L), Double Line-to-Ground Fault (L-L-G), and Three Line Fault (L-L-L). These Days, fault has been one of the significant problems in the transmission line system. Fault can lead to power losses in transmission lines as well as power failure. Electrical service in the transmission line system needs to be recovered immediately after fault appears to avoid more energy losses. Thus, it is crucial to create a system that will detect and eliminate fault faster, more accurately, and effectively. Typically, transmission line fault classification required complex signal processing, required expert knowledge, and complex mathematical modeling to process the output signal. This paper proposed a deep learning technique to classify ten types of fault through simulation. The objective of this study is to propose automated signal processing and features extraction. This technique can model a system that generates the automated signal processing and extract features learning with a deep learning framework and classify all the ten fault types in transmission lines accurately and effectively.

AIP Conference Proceedings, 2017

This paper presents a power electronic devices application focus on modeling, analysis, and contr... more This paper presents a power electronic devices application focus on modeling, analysis, and control of switching power converter in the inverting DC substation with regenerative braking system which is used to recycle the surplus regenerative power by feed it back to the main AC grid. The main objective of this research is to improve the switching power electronic converter of the railway inverting substation and optimize the maximum kinetic energy recovery together with minimum power losses from the railway braking system. Assess performance including efficiency and robustness will be evaluated in order to get the best solution for the design configuration. Research methodology included mathematical calculation, simulation, and detail analysis on modeling of switching power converter on inverting substation. The design stage separates to four main areas include rectification mode, regenerative mode, control inverter mode and filtering mode. The simulation result has shown that the regenerative inverter has a capability to accept a maximum recovery power on the regeneration mode. Total energy recovery has increase and power losses have decreases because inverter abilities to transfer the surplus energy back to the main AC supply. An Inverter controller with PWM Generator and PI Voltage Regulator has been designed to control voltage magnitude and frequency of the DC traction system.

2014 International Symposium on Biometrics and Security Technologies (ISBAST), 2014

2014 International Symposium on Biometrics and Security Technologies (ISBAST), 2014

Virtualization technology is the base technology used in Cloud computing. Therefore, virtualizati... more Virtualization technology is the base technology used in Cloud computing. Therefore, virtualization enables Cloud computing to provide hardware and software services to the users on demand. Actually, many companies migrates to the Cloud computing for many reasons such as capabilities of processor, bus speed, size of storage, memory and managed to reduce the cost of dedicated servers. However, virtualization and Cloud computing contain many security weaknesses that affects the biometric data confidentiality in the Cloud computing. Those security issues are VM ware escape, hopping, mobility, diversity monitoring and etc. Furthermore, the privacy of a particular user is an issue in biometric data i.e. the face reorganization data for a famous and important people. Therefore, this paper proposed biometric encryption to improve the confidentiality in Cloud computing for biometric data. Also, this paper discussed virtualization for Cloud computing, as well as biometrics encryption. Indeed, this paper overviewed the security weaknesses of Cloud computing and how biometric encryption can improve the confidentiality in Cloud computing environment. Apart from this, confidentiality is enhanced in Cloud computing by using biometric encryption for biometric data. The novel approach of biometric encryption is to enhance the biometric data confidentiality in Cloud computing.

2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)

Due to the growth of urbanization, streetlight systems are one of the most crucial devices relate... more Due to the growth of urbanization, streetlight systems are one of the most crucial devices related to city life. Most of the existing streetlight systems in Malaysia are conventional in terms of energy efficiency and cost reduction. This project focuses on using streetlight system information modeling to create correlations between consumed energy and actual utilization of the streetlight system with real-time data collection in Universiti Teknologi MARA Cawangan Pulau Pinang (UiTMCPP). The proposed technique used the most advanced method known as Artificial Neural Network to predict the total maximum demand for the streetlight system. The data analysis compares the High-Pressure Sodium (HPS) and Light Emitting Diode (LED) streetlight systems. A few comparisons, a total of maximum demand, cost analysis, and luminous flux, have been made. The data comparison between two different streetlight systems makes the proposed replacing the HPS streetlight systems with LED streetlight systems are reasonable.

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)

2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)

This paper presents the design and simulation of a single-phase inverter for Uninterruptible Powe... more This paper presents the design and simulation of a single-phase inverter for Uninterruptible Power Supply (UPS) using the Verilog Hardware Description Language (HDL) co-simulation by interfacing MATLAB/Simulink and ModelSim. The PWM signal was produced by comparing Sine Wave and Triangular Wave digitally generated by Verilog HDL. The analog and digital of the UPS circuit were simulated in MATLAB/SIMULINK and ModelSim Altera software, respectively. The digital controller was simulated using cosimulation tools in MATLAB/SIMULINK. As system developers and researchers work on the same platform, it reduces the required time required in translating the technical specifications into functional specifications. ModelSim works as HDL (Hardware Description Language) simulator. The designed circuit and obtained simulation results are presented in the paper to confirm the performance of digital implementation for this single-phase UPS system.

2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 2021

This project is a development of apps software that can design and analyzing the grounding of the... more This project is a development of apps software that can design and analyzing the grounding of the AC substation based on several conditions by using Android Studio software according to the IEEE Std. 80–2000. Six types of grids that has been developed are square, rectangular and L-shaped where all types with and without ground rod. The percentage difference obtained for all cases are less than 10 %. The application is compatible to be used for education and industry purposed. To make sure the design is safe, the comparable values such as Em and Es must be less than Etouch and Estep value. This app can be used with shortened time to design and verify the grounding system of the AC substation. It is fast, robust, and accurate. The design app is very important for every consultant as it is easy to use compared to manually calculation.

This paper proposes a speed control design of Permanent Magnet Synchronous Motor (PMSM) using Fie... more This paper proposes a speed control design of Permanent Magnet Synchronous Motor (PMSM) using Field Oriented Control (FOC). The focus is to design a speed control using Takagi — Sugeno Fuzzy Logic Control (T-S FLS). These systems will replace the conventional method which is proportional-integral (PI). The objective of this paper is to study the T—S Fuzzy Inference System (FIS) speed regulator and acceleration observer for PMSM. The scope of study basically is to design and analyse the Takagi Sugeno FLC and the PMSM. This paper also will describe the methodology and process of modelling the PMSM including data analysis. The simulation work is implemented in Matlab-Simulink to verify the control method. The effectiveness of this proposed control method was confirmed through various range of speed and torque variation.

Indonesian Journal of Electrical Engineering and Computer Science, 2020

Deep Learning has ignited great international attention in modern artificial intelligence techniq... more Deep Learning has ignited great international attention in modern artificial intelligence techniques. The method has been widely applied in many power system applications and produced promising results. A few attempts have been made to classify fault on transmission lines using various deep learning methods. However, a type of deep learning called Long Short-Term Memory (LSTM) has not been reported in literature. Therefore, this paper presents fault classification on transmission line using LSTM network as a tool to classify different types of faults. In this study, a transmission line model with 400 kV and 100 km distance was modelled. Fault free and 10 types of fault signals are generated from the transmission line model. Fault signals are pre-processed by extracting post-fault current signals. Then, these signals are fed as input to the LSTM network and trained to classify 10 types of faults. The white Gaussian noise of level 20 dB and 30 dB signal to noise ratio (SNR) is also ad...

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 2021

As technology advanced, electrical interruption or disturbance still becomes a significant proble... more As technology advanced, electrical interruption or disturbance still becomes a significant problem in power systems. A fault is one example of electrical disturbance or power failure in a power system. In order to recover the system, the fault must be detected, classify and locate to eliminate as fast as possible. Four types of fault occur in the transmission line. Those four types are Line-to-Ground Fault (L-G), Line-to-Line Fault (L-L), Double Line-to-Ground Fault (L-L-G), and Three Line Fault (L-L-L). These Days, fault has been one of the significant problems in the transmission line system. Fault can lead to power losses in transmission lines as well as power failure. Electrical service in the transmission line system needs to be recovered immediately after fault appears to avoid more energy losses. Thus, it is crucial to create a system that will detect and eliminate fault faster, more accurately, and effectively. Typically, transmission line fault classification required complex signal processing, required expert knowledge, and complex mathematical modeling to process the output signal. This paper proposed a deep learning technique to classify ten types of fault through simulation. The objective of this study is to propose automated signal processing and features extraction. This technique can model a system that generates the automated signal processing and extract features learning with a deep learning framework and classify all the ten fault types in transmission lines accurately and effectively.

AIP Conference Proceedings, 2017

This paper presents a power electronic devices application focus on modeling, analysis, and contr... more This paper presents a power electronic devices application focus on modeling, analysis, and control of switching power converter in the inverting DC substation with regenerative braking system which is used to recycle the surplus regenerative power by feed it back to the main AC grid. The main objective of this research is to improve the switching power electronic converter of the railway inverting substation and optimize the maximum kinetic energy recovery together with minimum power losses from the railway braking system. Assess performance including efficiency and robustness will be evaluated in order to get the best solution for the design configuration. Research methodology included mathematical calculation, simulation, and detail analysis on modeling of switching power converter on inverting substation. The design stage separates to four main areas include rectification mode, regenerative mode, control inverter mode and filtering mode. The simulation result has shown that the regenerative inverter has a capability to accept a maximum recovery power on the regeneration mode. Total energy recovery has increase and power losses have decreases because inverter abilities to transfer the surplus energy back to the main AC supply. An Inverter controller with PWM Generator and PI Voltage Regulator has been designed to control voltage magnitude and frequency of the DC traction system.

2014 International Symposium on Biometrics and Security Technologies (ISBAST), 2014

2014 International Symposium on Biometrics and Security Technologies (ISBAST), 2014

Virtualization technology is the base technology used in Cloud computing. Therefore, virtualizati... more Virtualization technology is the base technology used in Cloud computing. Therefore, virtualization enables Cloud computing to provide hardware and software services to the users on demand. Actually, many companies migrates to the Cloud computing for many reasons such as capabilities of processor, bus speed, size of storage, memory and managed to reduce the cost of dedicated servers. However, virtualization and Cloud computing contain many security weaknesses that affects the biometric data confidentiality in the Cloud computing. Those security issues are VM ware escape, hopping, mobility, diversity monitoring and etc. Furthermore, the privacy of a particular user is an issue in biometric data i.e. the face reorganization data for a famous and important people. Therefore, this paper proposed biometric encryption to improve the confidentiality in Cloud computing for biometric data. Also, this paper discussed virtualization for Cloud computing, as well as biometrics encryption. Indeed, this paper overviewed the security weaknesses of Cloud computing and how biometric encryption can improve the confidentiality in Cloud computing environment. Apart from this, confidentiality is enhanced in Cloud computing by using biometric encryption for biometric data. The novel approach of biometric encryption is to enhance the biometric data confidentiality in Cloud computing.

2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)

Due to the growth of urbanization, streetlight systems are one of the most crucial devices relate... more Due to the growth of urbanization, streetlight systems are one of the most crucial devices related to city life. Most of the existing streetlight systems in Malaysia are conventional in terms of energy efficiency and cost reduction. This project focuses on using streetlight system information modeling to create correlations between consumed energy and actual utilization of the streetlight system with real-time data collection in Universiti Teknologi MARA Cawangan Pulau Pinang (UiTMCPP). The proposed technique used the most advanced method known as Artificial Neural Network to predict the total maximum demand for the streetlight system. The data analysis compares the High-Pressure Sodium (HPS) and Light Emitting Diode (LED) streetlight systems. A few comparisons, a total of maximum demand, cost analysis, and luminous flux, have been made. The data comparison between two different streetlight systems makes the proposed replacing the HPS streetlight systems with LED streetlight systems are reasonable.