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Dr. Mostafa Abdelgeliel
Head of Department of Electrical and Control Engineering

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Research Keywords & Expertise

0 Model Predictive Control
0 Process Automation
0 Renewable and Sustainable Energy
0 Autonomation
0 Control and Automation

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Project

Project Goal: Reduce the lack of engineers skilled in Wind Engineering in Egypt and Tunisia

Starting Date:01 October 2017

Current Stage: Implement the courses and TOT

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Journal article
Published: 05 February 2021 in Energies
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Because of the unpredictable activity of solar energy sources, photovoltaic (PV) maximum power point tracking (MPPT) is essential to guarantee the continuous operation of electrical energy generation at optimal power levels. Several works have extensively examined the generation of the maximum power from the PV systems under normal and shading conditions. The fuzzy logic control (FLC) method is one of the effective MPPT techniques, but it needs to be adapted to work in partial shading conditions. The current paper presents the FLC-based on dynamic safety margin (DSM) as an MPPT technique for a PV system to overcome the limitations of FLC in shading conditions. The DSM is a performance index that measures the system state deviation from the normal situation. As a performance index, DSM is used to adapt the FLC controller output to rapidly reach the global maxima of the PV system. The ability of the proposed algorithm and its performance are evaluated using simulation and practical implementation results for single phase grid-connected PV system under normal and partial shading operating conditions.

ACS Style

Mostafa Bakkar; Ahmed Aboelhassan; Mostafa Abdelgeliel; Michael Galea. PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions. Energies 2021, 14, 841 .

AMA Style

Mostafa Bakkar, Ahmed Aboelhassan, Mostafa Abdelgeliel, Michael Galea. PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions. Energies. 2021; 14 (4):841.

Chicago/Turabian Style

Mostafa Bakkar; Ahmed Aboelhassan; Mostafa Abdelgeliel; Michael Galea. 2021. "PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions." Energies 14, no. 4: 841.

Journal article
Published: 14 December 2020 in Energies
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Advanced control approaches are essential for industrial processes to enhance system performance and increase the production rate. Model Predictive Control (MPC) is considered as one of the promising advanced control algorithms. It is suitable for several industrial applications for its ability to handle system constraints. However, it is not widely implemented in the industrial field as most field engineers are not familiar with the advanced techniques conceptual structure, the relation between the parameter settings and control system actions. Conversely, the Proportional Integral Derivative (PID) controller is a common industrial controller known for its simplicity and robustness. Adapting the parameters of the PID considering system constraints is a challenging task. Both controllers, MPC and PID, merged in a hierarchical structure in this work to improve the industrial processes performance considering the operational constraints. The proposed control system is simulated and implemented on a three-tank benchmark system as a Multi-Input Multi-Output (MIMO) system. Since the main industrial goal of the proposed configuration is to be easily implemented using the available automation technology, PID controller is implemented in a PLC (Programable Logic Controller) controller as a lower controller level, while MPC controller and the adaptation mechanism are implemented within a SCADA (Supervisory Control And Data Acquisition) system as a higher controller level.

ACS Style

Ahmed Aboelhassan; M. Abdelgeliel; Ezz Eldin Zakzouk; Michael Galea. Design and Implementation of Model Predictive Control Based PID Controller for Industrial Applications. Energies 2020, 13, 6594 .

AMA Style

Ahmed Aboelhassan, M. Abdelgeliel, Ezz Eldin Zakzouk, Michael Galea. Design and Implementation of Model Predictive Control Based PID Controller for Industrial Applications. Energies. 2020; 13 (24):6594.

Chicago/Turabian Style

Ahmed Aboelhassan; M. Abdelgeliel; Ezz Eldin Zakzouk; Michael Galea. 2020. "Design and Implementation of Model Predictive Control Based PID Controller for Industrial Applications." Energies 13, no. 24: 6594.

Conference paper
Published: 11 October 2020 in 2020 4th International Conference on Automation, Control and Robots (ICACR)
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Polymer extrusion is a widely used industrial process that exists in almost all petrochemical industries as well as various other industrial applications. In order to achieve a high quality of end-product, it is crucial to precisely control the process conditions of the polymer throughout the extrusion process. In this paper, a brief description of the extrusion process and its main control loop are described. System identification of the gear melt pump is also illustrated which is considered as the most important equipment to be controlled within the extruder unit. In order to overcome the parameters and operating condition variations of the process a robust and adapted controller is required. Since the operators of the polymer extrusion process is familiar with classical PID controller. Therefore, the application of a Supervisory Model Predictive Controller (SMPC) is suggested and implemented to overcome the limitation of PID controller alone. SMPC is implemented under two cases; first when the traditional PID controller optimum gains are used to control the inner loop of the melt pump, and second when random PID controller gains are representing the change of process conditions. Finally, the results of both cases were illustrated, compared and discussed proving that the implementation of an SMPC indeed enhances the reliability of the process control algorithm.

ACS Style

M.Y. Elmahdawy; Mostafa Abdelgeliel; Alaa Eldin Khalil. Application of Supervisory Model Predictive Controller in Polymer Extrusion Process. 2020 4th International Conference on Automation, Control and Robots (ICACR) 2020, 107 -111.

AMA Style

M.Y. Elmahdawy, Mostafa Abdelgeliel, Alaa Eldin Khalil. Application of Supervisory Model Predictive Controller in Polymer Extrusion Process. 2020 4th International Conference on Automation, Control and Robots (ICACR). 2020; ():107-111.

Chicago/Turabian Style

M.Y. Elmahdawy; Mostafa Abdelgeliel; Alaa Eldin Khalil. 2020. "Application of Supervisory Model Predictive Controller in Polymer Extrusion Process." 2020 4th International Conference on Automation, Control and Robots (ICACR) , no. : 107-111.

Journal article
Published: 09 June 2020 in Energies
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Since the permeant magnet synchronous generator (PMSG) has many applications in particular safety-critical applications, enhancing PMSG availability has become essential. An effective tool for enhancing PMSG availability and reliability is continuous monitoring and diagnosis of the machine. Therefore, designing a robust fault diagnosis (FD) and fault tolerant system (FTS) of PMSG is essential for such applications. This paper describes an FD method that monitors online stator winding partial inter-turn faults in PMSGs. The fault appears in the direct and quadrature (dq)-frame equations of the machine. The extended Kalman filter (EKF) and unscented Kalman filter (UKF) were used to detect the percentage and the place of the fault. The proposed techniques have been simulated for different fault scenarios using Matlab®/Simulink®. The results of the EKF estimation responses simulation were validated with the practical implementation results of tests that were performed with a prototype PMSG used in the Arab Academy For Science and Technology (AAST) machine lab. The results showed impressive responses with different operating conditions when exposed to different fault states to prevent the development of complete failure.

ACS Style

Waseem El Sayed; Mostafa Abd El Geliel; Ahmed Lotfy. Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter. Energies 2020, 13, 2972 .

AMA Style

Waseem El Sayed, Mostafa Abd El Geliel, Ahmed Lotfy. Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter. Energies. 2020; 13 (11):2972.

Chicago/Turabian Style

Waseem El Sayed; Mostafa Abd El Geliel; Ahmed Lotfy. 2020. "Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter." Energies 13, no. 11: 2972.

Article
Published: 20 February 2020 in International Journal of Fuzzy Systems
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Air quality control is necessary to improve the environmental condition in particular Indoor Air Quality (IAQ), which has a direct impact on a living organism. In marine application, the International Maritime Organization (IMO) made standards to determine the gas emission limits and specify the air circulation in IAQ in addition to employing in energy-efficient and energy management system which leads to reduce emission and enhance the environmental condition by efficient and economical way. Applying advanced energy management policies and control could be achieved by energy consumption. In this paper, an intelligent neuro-fuzzy controller has been designed to model and control carbon monoxide (CO) concentration for a real case study of a high-speed craft passenger ship with a vehicle garage onboard for a liner between Egypt and Saudi Arabia ports. The relation between emitted CO and the number of cars and their positions has been modelled using artificial neural network (ANN). The ANN model has been built and validated based on real measurements of CO at different ventilation conditions of the case study. Different fuzzy controllers, fixed and adaptive, are designed to control CO during loading and unloading states. Scaling factors of fuzzy controller are adapted using two different ways namely Supervisor Fuzzy Controller (SFC) and Particle Swamp Optimization (PSO). Simulation results have analysed the proposed control system at different conditions. The obtained outcomes manifest the fact that the controller tends to work robustly and efficiently to maintain CO at the permissible allowed range.

ACS Style

Hossam Agamy; Mostafa Abdelgeliel; Mosaad Mosleh; Kamel Elserafy; Nasr Abdelrahman Nasr Mohamed. Neural Fuzzy Control of the Indoor Air Quality Onboard a RO–RO Ship Garage. International Journal of Fuzzy Systems 2020, 22, 1020 -1035.

AMA Style

Hossam Agamy, Mostafa Abdelgeliel, Mosaad Mosleh, Kamel Elserafy, Nasr Abdelrahman Nasr Mohamed. Neural Fuzzy Control of the Indoor Air Quality Onboard a RO–RO Ship Garage. International Journal of Fuzzy Systems. 2020; 22 (3):1020-1035.

Chicago/Turabian Style

Hossam Agamy; Mostafa Abdelgeliel; Mosaad Mosleh; Kamel Elserafy; Nasr Abdelrahman Nasr Mohamed. 2020. "Neural Fuzzy Control of the Indoor Air Quality Onboard a RO–RO Ship Garage." International Journal of Fuzzy Systems 22, no. 3: 1020-1035.

Original article
Published: 25 September 2019 in Port-Said Engineering Research Journal
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ACS Style

Kamel Ahmed Elserafi; Hossam Eldine Agamy; Mosaad Mosleh; Mostafa Abdelgeliel; Nasr Abdalrahman. Neural Network Model of carbon monoxide distribution in onboard a RO-RO Ship Garage. Port-Said Engineering Research Journal 2019, 1 .

AMA Style

Kamel Ahmed Elserafi, Hossam Eldine Agamy, Mosaad Mosleh, Mostafa Abdelgeliel, Nasr Abdalrahman. Neural Network Model of carbon monoxide distribution in onboard a RO-RO Ship Garage. Port-Said Engineering Research Journal. 2019; ():1.

Chicago/Turabian Style

Kamel Ahmed Elserafi; Hossam Eldine Agamy; Mosaad Mosleh; Mostafa Abdelgeliel; Nasr Abdalrahman. 2019. "Neural Network Model of carbon monoxide distribution in onboard a RO-RO Ship Garage." Port-Said Engineering Research Journal , no. : 1.

Conference paper
Published: 01 November 2017 in 2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems & 2017 Intl Conf on New Paradigms in Electronics & Information Technology (PEIT)
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The induction motor is widely used in industrial applications, respectively, the fault detection and isolation is very important for the continuity of industrial process. The stator turns faults are one of the common faults that may lead to a massive failure which confirms the early detection of the fault to take the best action. This paper presents the fault diagnosis of stator turns faults using extended Kalman filter technique to estimate the percentage of short circuit turns ratio in each phase. The simulation is implemented using MATLAB/Simulink, the technique is tested in various load conditions. The simulation results show that the proposed technique is effective and robust, it shows an accurate estimation in the presence of noises to take action prevent the propagation of fault.

ACS Style

Waseem. W. Saad; M. Abd El-Geliel; Ahmed Lotfy. IM stator winding faults diagnosis using EKF. 2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems & 2017 Intl Conf on New Paradigms in Electronics & Information Technology (PEIT) 2017, 34 -39.

AMA Style

Waseem. W. Saad, M. Abd El-Geliel, Ahmed Lotfy. IM stator winding faults diagnosis using EKF. 2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems & 2017 Intl Conf on New Paradigms in Electronics & Information Technology (PEIT). 2017; ():34-39.

Chicago/Turabian Style

Waseem. W. Saad; M. Abd El-Geliel; Ahmed Lotfy. 2017. "IM stator winding faults diagnosis using EKF." 2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems & 2017 Intl Conf on New Paradigms in Electronics & Information Technology (PEIT) , no. : 34-39.

Conference paper
Published: 01 November 2017 in 2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems & 2017 Intl Conf on New Paradigms in Electronics & Information Technology (PEIT)
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In industrial processes, all available resources, are selected to improve the process performance. However, in critical processes, any kind of faults may lead to serious consequences. One of the main techniques to enhance process reliability is to early detect and isolate faults. Artificial Neural Networks (ANN) technique is a good tool to detect and isolate several types of faults in industrial systems. Fault detection and isolation based on ANN is proposed in this paper. This technique is implemented and tested on Three-Tank system as a bench mark. Moreover different fault scenarios are tested.

ACS Style

Youssef A. Ghobashy; Mostafa Abdelgeliel; M. El Sengaby. Industrial application of fault detection and fault isolation using artificial neural networks. 2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems & 2017 Intl Conf on New Paradigms in Electronics & Information Technology (PEIT) 2017, 48 -59.

AMA Style

Youssef A. Ghobashy, Mostafa Abdelgeliel, M. El Sengaby. Industrial application of fault detection and fault isolation using artificial neural networks. 2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems & 2017 Intl Conf on New Paradigms in Electronics & Information Technology (PEIT). 2017; ():48-59.

Chicago/Turabian Style

Youssef A. Ghobashy; Mostafa Abdelgeliel; M. El Sengaby. 2017. "Industrial application of fault detection and fault isolation using artificial neural networks." 2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems & 2017 Intl Conf on New Paradigms in Electronics & Information Technology (PEIT) , no. : 48-59.