Mohamed Misbah Elkhatib
@mtc.edu.eg
Electronic Engineering Department
Military Technical College
RESEARCH INTERESTS
Intelligent systems, Mixed-mode VLSI design, Low power circuit design, ASICs for control applications, Intelligent control circuits & systems, Unman Vehicles, Embedded systems, Fuzzy systems, LDO voltage regulator design, Power management and Energy harvesting circuits, and wireless sensor network.
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Mohamed Etewa, Ehab Safwat, Mohammed Abozied Hassan Abozied, and Mohamed Misbah El-Khatib
IEEE
Unmanned Aerial Vehicles (UAVs) have emerged as vital tools in various industries, including surveillance, environmental monitoring, and aerial mapping. The success of UAV missions is contingent upon their precise and robust flight control systems. This research presents a thorough investigation into the design and implementation of a fixed-wing UAV flight controller utilizing the Nonlinear Dynamic Inversion (NDI) technique. The study delves into the theoretical foundations of NDI and its application in UAV control, aiming to address the challenges posed by nonlinear dynamics and uncertainties in UAV systems. Extensive simulations are conducted to validate the proposed controller's performance, highlighting its superior precision and adaptability. The findings demonstrate the potential of NDI as an advanced control approach for improving the efficiency and reliability of fixed-wing UAV operations in various real-world scenarios
Mohamed S. Elkerdany, Ibrahim M. Safwat, Ahmed Medhat M. Youssef, and Mohamed M. Elkhatib
IEEE
Hybrid electric UAVs rely heavily on energy manage-ment strategy (EMS). For a small UAV fuel-cell (FC) hybrid system, a comparison of four EMSs is presented in this paper. The FC, lithium-ion battery, and dc/dc converters comprise the hybrid system. The management of hybrid electric power flow based on changes in load power and battery state of charge (SOC) is an important part of these strategies. The energy management schemes considered in this paper are the most commonly used energy management schemes in fuel-cell based UAVs, and they include the following: the classical proportional-integral (PI) control (CPIC) strategy, the state machine control (SMC) strategy, the rule-based fuzzy logic (RBFL) strategy, and an intelligent technique based on adaptive neuro-fuzzy control strategy (ANFIS). There are two primary metrics for comparing performance, hydrogen consumption and battery SOC (BSOC), which impacts their life cycle. Such an EMS should be designed to maximise fuel efficiency while also making sure each energy source is used responsibly. MATLAB/Simulink software is used to conduct an in-depth study of a simulated model. For better usage of hybrid system's energy, EMS identifies variations in transient load current, as well as fuel-cell power. These investi-gations give insight on EMS work and the power flow in hybrid power systems. The trade-off choice between EMS is ensuring optimal performance in accordance with selected criterion.
Ahmed Elbatal, Ahmed Medhat Youssef, and Mohamed M. Elkhatib
Institute of Advanced Engineering and Science
Synthesis of a flight control system for such an aircraft that achieves stable and acceptable performance across a specified flying envelope in the presence of uncertainties represents an attractive and challenging design problem. This study uses the genetic self-tuning PID algorithm to develop an intelligent flight control system for the aerosonde UAV model. To improve the system's transient responses, the gains of the PID controller are improved using a genetic algorithm (GA). Simulink/MATLAB software is used to model and simulate the proposed system. The proposed PID controller integrated with the GA is compared with the classical one. Three simulation scenarios are carried out. In the first scenario, and at normal conditions, the proposed controller performance is better than the classical one. While in the second scenario, identical results are achieved from both controllers. Finally, in the third scenario, the PID controller with GA shows the robustness and durability of the system compared with the classical PID in presence of external wind disturbance. The simulation results prove the system parameters optimization.
Mohamed Sameh Elkerdany, Ibrahim Mohamed Safwat, Ahmed Medhat Mohamed Yossef, and Mohamed M. Elkhatib
IEEE
Energy management strategy (EMS) for fuel cell and battery hybrid system is a fundamental property of controlling the flow of power between power sources. A key aspect of intelligent control strategy is controlling the flow of hybrid system power according to the change of load power and the variation of state of charge (SOC) of the battery. A case-study design, with in-depth analysis using ANFIS/Simulink toolbox is introduced. This paper provides an intelligent method based on adaptive neuro-fuzzy algorithm to be used for the UAV hybrid Energy Management Strategies. The major objective of this study is to investigate the effectiveness of the proposed method in maintaining a constant DC bus voltage. These studies provide important insights into the flow of power decisions based on the EMS in hybrid power systems.
M. K. Gad, M. S. Mohamed, and M. M. Elkhatib
IEEE
Technological growth had changed the conduction way of the warfare. This work is paying attention with developing the performance of a SSM (surface-to-surface missile) aerodynamically controlled system via both predictive and Neuro-Fuzzy controllers. The analysis and design demand somehow precise system model with different uncertainties via 6-DOF simulation. The executive differential equations of the missile motion are obtained from the model of missile’s aerodynamic that built by means of the Missile Datcom software. Hence getting the required aerodynamics stability derivatives by the resulted aerodynamics data, the required transfer functions are calculated based on the equations of motion for the missile. Then the yaw autopilot is designed using the calculated transfer functions and to recognize the command signal produced by the guidance laws. The form of guidance commands are in the lateral acceleration components. By using the whole system model, the computer simulators are made by using the Matlab-Simulink software, where predictive and hybrid AI (Artificial Intelligence) Neuro-Fuzzy Yaw autopilots are compared proving that the more stability and less processing time.
Mohamed Sameh Elkerdany, Ibrahim Mohamed Safwat, Ahmed Medhat Mohamed Yossef, and Mohamed M. Elkhatib
IEEE
Electrical propulsion system using Brushless DC(BLDC) motors is widely used nowadays in mini Unmanned Aerial Vehicle (UAV), as it guarantees an efficient performance and long flight endurance enhancement. The driver of BLDC has a pivotal role in this electrical propulsion system. Three-phase inverter with six switches design is the most common in the driver model of a conventional BLDC motor. In this paper, a comparative study between the BLDC motor drive system using a non-ideal six-switch three-phase inverter (SSTPI), and a non-ideal four-switch three phase inverter (FSTPI) is investigated. The study point-of-view is the enhancement of the propulsion system efficiency, cost, and controllability. Mathematical models for the two proposed systems including BLDC motor are introduced. Simulation using MATLAB Simulink is performed at different flight modes with variable motor speeds. A comparative study declares the tradeoff choice between the two drive systems to enhance the system performance based on the preferred selection criterion. This study provides a good guide for designing such BLDC motor driver systems.
Ahmed Elbatal, Mohamed M. Elkhatib, and Ahmed Medhat Youssef
IEEE
In the last decade, the Unmanned Aerial Vehicles (UAVs) industry has a rapid progress in the development and optimization of UAV’s autopilot systems. This paper proposes two flight control methods using the Aerosonde simulation model, which was modeled and simulated using Simulink/MATLAB software. The two methods are a self-tuning PID controller using genetic algorithm and Adaptive Neuro-fuzzy Inference System controller (ANFIS). In a self-tuning PID controller, a PID is genetically controlled and utilized as an autopilot to optimize the controller parameters for the proposed UAV model. However, the second method is based on fuzzy logic controller tuned using neural network. For the main navigation system Three fuzzy logic modules are designed to monitor the altitude, speed and heading angle. Simulation results for the two methods reveal high robustness and durability of ANFIS controller response especially under windy conditions.
Tamer Farouk, Mohamed Dessouky, and Mohamed Elkhatib
Elsevier BV
Mohamed M. Elkhatib
IOP Publishing
Abstract Recently, stability of nonlinear multi-input, multi-output (MIMO) system has attracted a significant number of researchers specially, due to the large development in practical implementation of nonlinear system with uncertainty. In this paper, using additively decomposable property based on the structure of a LUR’E problem, an intelligent Takagi-Sugeno fuzzy block is added in the system feedback. The new proposed system includes all the system nonlinearities as result it grantees system absolute stability. A simulation result of the new algorithm for MIMO system is introduced.
Mohamed Sherif Nabil, Mohamed Misbah ElKhatib, and Ashraf Tammam
IEEE
Internet of Things (IoT) is increasingly gaining impact from day to day in our lives. Wireless sensor networks (WSNs) are integrated into the “Internet of Things” and one of the challenges is energy saving. This paper focuses on a self-sustainable Wireless Sensor Node (WSN) for various Internet of Things applications with low power consumption. It is devoted to implement energy harvesting solutions to provide constant output voltage; therefore, a power management system (PMS) is needed to control and manage this output. That is, a DC-DC Buck-Boost converter had been proposed to control Energy Harvester output voltage via PID-like fuzzy controller.
Mohamed Sherif Nabil, Mohamed Misbah ElKhatib, and Ashraf Tammam
IEEE
These days, on account of the immense advances in energy technology, sustainable power source has developed and turned into an essential part of the power system. However, the output energy that is collected from the natural surrounding elements is unstable, therefore this paper presents a DC-DC Buck-Boost Converter to control and manage the Energy Harvester output voltage via Neuro-fuzzy controller to provide constant output voltage for various power system applications among them are: self-sustainable Wireless Sensor Node. Based on adaptive Neuro-Fuzzy inference systems (ANFIS), this methodology combines the training talents of artificial neural networks and also the ability of fuzzy logic to handle imprecise knowledge. The execution of the proposed strategy is contrasted with that of a PID-like Fuzzy controller to exhibit its adequacy and it has proven that there is an effective changes regarding settling time almost being zero, overshoot being negligible and steady state voltage. The simulation results are determined by means that of MATLAB/Simulink toolbox.
Islam W. Mahdy, Mohamed M. Elkhatib, and Mohamed A. Refky
IEEE
M. K. Elbaioumy, M. M. Elkhatib, and A. E. Khalifa
University of Defence
In this paper, a general platform of a surface-to-surface missile model is presented. An accurate missile system model was made with consideration of the rigid body dynamics in space with six degrees of freedom and equation of motion starting from Newton second law to the non-linear state space model of the missile. Computer simulations have been executed using the MATLAB / Simulink software. Verification of the system model has been made.
Azza Esam, Mohamed Elkhatib, and Sameh Ibrahim
Springer International Publishing
Hossam O. Ahmed, Mohamed M. Elkhatib, Ihab Adly, and Hani Fikry Ragai
Springer Science and Business Media LLC
Mohamed M. Elkhatib
IEEE
Low-dropout Linear Regulators (LDOs) play an important role in the power delivery process within portable electronic devices, such as cellular phones and laptop computers. This paper introduces an LDO control technique based on a neuromorphic spiking compensation inspired by the human brain's data-driven communication. The presented voltage-spike detection method is based on capacitive coupling and a spike to current modulator, where the rapid transients at the LDO output are used to increase the quiescent current temporarily to enhance the dynamic response. Moreover, the presented technique reduces the size of the output capacitor in a typical LDO to enable its full integration within System-on-Chip (SoCs) while ensuring stability. Simulations in a 0.13 μm CMOS technology show over 85% reduction in overshoots and undershoots.
Tamer Farouk, Mohamed Elkhatib, and Mohamed Dessouky
IEEE
This paper presents a low-voltage low-power low-noise amplifier suitable for neural recording applications. Based on the flipped voltage follower (FVF) topology, the amplifier is able to operate under a 1 V supply by alleviating the tradeoff between the noise and the voltage headroom. A gm-cell was built using FVF, its effective transconductance is not a function of the bias current, so the noise contribution of the output transistors can be decreased without increasing the bias current. This amplifier is designed and simulated in a 130 nm CMOS process. The amplifier consumes 2.2 μW from 1 V supply voltage. The input referred noise is 3.7 μVrms. The amplifier has a BW from 25 Hz to 9.9 kHz.
A. N. Mohamed, H. N. Ahmed, M. Elkhatib, and K. A. Shehata
IEEE
A low-power, low-noise chopper stabilized CMOS differential difference instrumentation amplifier (CHDDA) for portable biopotential acquisition applications is presented. The proposed 130 nm CMOS chopper stabilized amplifier has 3.2μW power dissipation, thermal noise floor of 10 nV/rtHz and corner frequency in the vicinity of 10 Hz with 1 V supply voltage which performs adequately well in measuring biopotential signals.
M. M. El-khatib and W. M. Hussein
SPIE
A Hovercraft is an amphibious vehicle that hovers just above the ground or water by air cushion. The concept of air cushion vehicle can be traced back to 1719. However, the practical form of hovercraft nowadays is traced back to 1955. The objective of the paper is to design, simulate and implement an autonomous model of a small hovercraft equipped with a mine detector that can travel over any terrains. A real time layered fuzzy navigator for a hovercraft in a dynamic environment is proposed. The system consists of a Takagi-Sugenotype fuzzy motion planner and a modified proportional navigation based fuzzy controller. The system philosophy is inspired by human routing when moving between obstacles based on visual information including the right and left views from which he makes his next step towards the goal in the free space. It intelligently combines two behaviours to cope with obstacle avoidance as well as approaching a goal using a proportional navigation path accounting for hovercraft kinematics. MATLAB/Simulink software tool is used to design and verify the proposed algorithm.
Mohamed El-khatib and David Hamilton
IEEE
A system for real time navigation of a nonholonomic car-like robot in a dynamic environment consists of two layers is described: a Sugeno-type fuzzy motion planner; and a modified proportional navigation based fuzzy controller. The system philosophy is inspired by human routing when moving between obstacles based on visual information including right and left views to identify the next step to the goal. A Sugeno-type fuzzy motion planner of four inputs one output is introduced to give a clear direction to the robot controller. The second stage is a modified proportional navigation based fuzzy controller based on the proportional navigation guidance law and able to optimize the robot's behavior in real time, i.e. to avoid stationary and moving obstacles in its local environment obeying kinematics constraints. The system has an intelligent combination of two behaviors to cope with obstacle avoidance as well as approaching a target using a proportional navigation path. The system was simulated and tested on different environments with various obstacle distributions. The simulation reveals that the system gives good results for various simple environments
A.K. Taha, M.M. El-Khatib, and A.S. Badawi
Minufiya Univ
The design of an analog programmable membership function circuit for fuzzy logic controllers implementation is introduced. The presented circuit has been simulated on PSpice. A VLSI implementation of the circuit has also been performed using the L-EDIT/sup TM/ program.