Prof. Ahmed El-Garhy - Academia.edu (original) (raw)

Papers by Prof. Ahmed El-Garhy

2018 13th International Conference on Computer Engineering and Systems (ICCES), 2018

This paper introduces a sensor-based approach for finding an optimized solution for online covera... more This paper introduces a sensor-based approach for finding an optimized solution for online coverage path planning problem. Compared to traditional approaches we can augment. Multi-objective optimization genetic algorithm (GA) with Dynamic Programming (DP) for finding a short path with complete coverage; while using on-board sensors data only. Simulation results prove the effectiveness of the proposed approach compared to current adapted approaches.

2021 16th International Conference on Computer Engineering and Systems (ICCES), 2021

This paper proposes a novel approach for finding an optimized solution for the online coverage pa... more This paper proposes a novel approach for finding an optimized solution for the online coverage path planning in unknown environments problem employing cooperative multi robotic agents. The suggested approach lessens the time required for solving the coverage problem by using cooperative multiple robotic agents working together to achieve enhanced complete coverage while sustaining minimum time, and the minimum number of repeated cells and respecting the service time. The distributed multi-agent planning with coordination process is optimized using dynamic programming with a rolling horizon limited look-ahead policy for online capability. In addition to expanding the usual single-agent action tree to hold a multi-agent scheme for possible collision-free sub-trajectories generation con-cerning quality, repetitions count, length per single agent to plan and execute cooperatively for covering a given unknown sur-roundings. Regarding coverage optimization, we utilize a multi-objective optimization genetic based algorithm with uniform cost search for the single-agent coverage sub-trajectory planning. In multi-agent-based systems, communication introduces overhead and have a direct influence on the system's robustness. Hence, we proposed a voting and coalition formation based on the K-means clustering algorithm for minimizing the communication henceforth improving the system's robustness. Simulation results highlight an enhancement regarding speeding up the complete coverage process compared to optimum single-agent approaches while advancing near-optimal utilization and efficiency minimizing repetitions in different unknown environments.

Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017, 2017

A novel Multi-Input Multi-Output Brain Emotional Learning Based Intelligent Controller (MIMO-BELB... more A novel Multi-Input Multi-Output Brain Emotional Learning Based Intelligent Controller (MIMO-BELBIC) is introduced and applied as a controller of PUMA 560 robotic arm. PUMA 560 model is strongly coupled highly nonlinear model, which necessitate effective controller capable of dealing with high degree of coupling and nonlinearity. Furthermore, the robot is subjected to many sources of disturbances, which can affect the performance significantly. Mathematical model of MIMO-BELBIC is introduced and tailored to work as a controller of PUMA 560. Moreover, new optimization algorithm, designed especially for this problem, is used to optimize the 51 parameters of the controller. The results show remarkable success of the proposed controller in decreasing the tracking error (with/without) disturbances in comparison to the traditional PID controllers that were optimized by two different algorithms. Moreover, the proposed controller has minimal control effort with respect to the PID controllers.

In this study, a nonlinear time-varying lumped parameter mathematical model of left sided heart f... more In this study, a nonlinear time-varying lumped parameter mathematical model of left sided heart failure had been proposed. One of the causes of systolic heart failure is Dilated Cardiomyopathy, was studied. Many tries were done to know the appropriate parameters in the model to express Dilated Cardiomyopathy as a case of heart failure. Ventricular elastance was found to be the most suitable parameter to present Dilated Cardiomyopathy. Mathematical equations for the change of heart rate and left ventricular pressure with time with decreasing ventricular elastance were concluded. The effects of Dilated Cardiomyopathy on heart rate, left ventricular pressure-volume loop (P-V loop), left ventricular pressure, stroke volume and ejection fraction were modeled.

2021 38th National Radio Science Conference (NRSC), 2021

The respiratory system is one of the complicated systems in the human body. In this paper, the ma... more The respiratory system is one of the complicated systems in the human body. In this paper, the mathematical model for the respiratory system was proposed based on the electro-acoustic bio-impedance analysis with huge number of equations. Further, the behavior of each generation from 24 generations of the respiratory system can be analyzed separately. Furthermore, the pressure with ventilated frequency from 1-1200 min-1 at any generation can be predicted and calculated. The proposed mathematical model was validated by comparison the results with the published results. The simulated results for ARDS disease are presented. Also, the comparison between normal case (healthy) and ARDS diseased case is presented. The proposed mathematical model with huge number of equations is implemented by Matlab program package. This proposed mathematical model can be used as a reversed problem solution to detect and diagnose the medical situation of the respiratory system for patients especially patients associated with COVID-19.

JES. Journal of Engineering Sciences, 2010

This Paper presents a hybrid genetic and Nelder-Mead algorithm (HGNMA) to determine the optimal p... more This Paper presents a hybrid genetic and Nelder-Mead algorithm (HGNMA) to determine the optimal proportional-integral-derivative (PID) controller parameters. PID controller exhibits good features, including easy implementation, stable convergence characteristic and good computational efficiency. The HGNMA algorithm is implemented in MATLAB, the results obtained from this hybrid technique is compared with that obtained from Genetic Algorithm (GA) and the conventional PID which is tuned via the Ziegler-Nichols frequency response method. The proposed method is more efficient in improving the step response characteristics such as, reducing rise time, settling time and maximum overshoot.

JES. Journal of Engineering Sciences, 2012

To control the actuation of the spring-roll dielectric elastomer actuator, the required actuation... more To control the actuation of the spring-roll dielectric elastomer actuator, the required actuation and dimensionless axial force (load) should be prescribed. Required actuation can be considered as a set point of the control system. In this paper different conventional and evolutionary controllers have been proposed, PID, Fuzzy, PID-Fuzzy average, particle swarm optimizing algorithm based PID. The performance of all these controllers have been addressed in terms of steady state error, maximum overshoot, and time consumed for the sake of qualitative comparison. To control the actuation of the spring-roll dielectric elastomer actuator, the charges pumped by the voltage supply should be controlled. A unity feed back control system is used. The response of each control system is derived and the choice of the more suitable controller is an application dependent, where some applications need zero steady state error while others need fast response. Spring-roll dielectric elastomer voltage supply and control system are based upon optimal design parameters derived in [1, 2]. The results of the conducted simulation experiments proved that all developed control systems are robust and help the usage of the spring-roll dielectric elastomer as a structural unit of an active artificial muscle.

International Journal of Electronics, 2018

In this study, converting acoustic to electric energy was achieved via the Disk Jockey (DJ) model... more In this study, converting acoustic to electric energy was achieved via the Disk Jockey (DJ) model TG5000, which worked as a noise source, and the piezoelectric model 7BB-41-2, which worked as a transducer. We proposed different states of piezoelectric transducer's mounting on DJ and examined the results to determine the optimum state for maximization of the converted power. We proposed a technique which comprises four stages, and each stage is composed of a piezoelectric transducer followed by a voltage multiplier. The outputs of the four stages were connected in parallel, and these transducers were mounted via their bodies on the slim diaphragm of the acoustic focusing tube. The results indicated that the maximum converted power values were 1.225 mW with a load resistor of 10 kΩ for one stage, 1.089 mW with a load resistor of 10 kΩ for two stages, 1.682 mW with a load resistor of 5 kΩ for three stages, and 5.891mW with a load resistor of 2.2 kΩ for four stages at a sound intensity level of 85 dB and sound wave frequency of 2.1 kHz.

Mathematical Problems in Engineering, 2017

The distillation process is vital in many fields of chemical industries, such as the two-coupled ... more The distillation process is vital in many fields of chemical industries, such as the two-coupled distillation columns that are usually highly nonlinear Multi-Input Multi-Output (MIMO) coupled processes. The control of MIMO process is usually implemented via a decentralized approach using a set of Single-Input Single-Output (SISO) loop controllers. Decoupling the MIMO process into group of single loops requires proper input-output pairing and development of decoupling compensator unit. This paper proposes a novel intelligent decoupling approach for MIMO processes based on new MIMO brain emotional learning architecture. A MIMO architecture of Brain Emotional Learning Based Intelligent Controller (BELBIC) is developed and applied as a decoupler for 4 input/4 output highly nonlinear coupled distillation columns process. Moreover, the performance of the proposed Brain Emotional Learning Based Intelligent Decoupler (BELBID) is enhanced using Particle Swarm Optimization (PSO) technique. Th...

2016 Eighteenth International Middle East Power Systems Conference (MEPCON), 2016

In this study a new noise source is proposed as a one of renewable energy sources in energy harve... more In this study a new noise source is proposed as a one of renewable energy sources in energy harvesting. Disk Jokey (DJ) is a common device in celebrations and other events. Converting the produced noise from DJ to electric energy by using a suitable piezoelectric transducer is the main aim of this study. Piezoelectric sensors are used to convert the sound waves to electric charges. Piezoelectric sensor of the model 7BB-41-2 is used in this study. The piezoelectric sensors are connected in series, parallel, and hybrid combination connections. The disk jockey is used as an acoustic noise source. The sound intensity levels of the output sound are 81, 84, 87 dB. The output of the three connection modes are measured at 0, 1,2,3,4, and 5cm distance. The results showed that the parallel connection gave the highest power at the various distances. The maximum generated power is 4.96m watts without using an external power supply for the signal condition device. The power decreases by increasing the distance from the source of the noise.

Computational Intelligence and Neuroscience, 2016

The two-coupled distillation column process is a physically complicated system in many aspects. S... more The two-coupled distillation column process is a physically complicated system in many aspects. Specifically, the nested interrelationship between system inputs and outputs constitutes one of the significant challenges in system control design. Mostly, such a process is to be decoupled into several input/output pairings (loops), so that a single controller can be assigned for each loop. In the frame of this research, the Brain Emotional Learning Based Intelligent Controller (BELBIC) forms the control structure for each decoupled loop. The paper’s main objective is to develop a parameterization technique for decoupling and control schemes, which ensures robust control behavior. In this regard, the novel optimization technique Bacterial Swarm Optimization (BSO) is utilized for the minimization of summation of the integral time-weighted squared errors (ITSEs) for all control loops. This optimization technique constitutes a hybrid between two techniques, which are the Particle Swarm and...

AEJ - Alexandria Engineering Journal

Journal of Clinical Engineering, 2015

Overactive bladder is a sudden bladder contraction without the patient_s control despite the blad... more Overactive bladder is a sudden bladder contraction without the patient_s control despite the bladder may contain only a small amount of urine. The overactive bladder is a chronic dysfunction caused primarily by a problem in the nerves that causes an increasing discomfort and burden on the patient. Therefore, the management of overactive bladder is crucial for the health. This study investigated a new controller approach based on Adaptive Neuro-Fuzzy Inference System to damp the parasympathetic nervous signal and furthermore to stimulate the stimulation locations such as the tibial nerve and dorsal penile nerve to enhance the bladder stability of the control continence. The complete simulations are performed in the MATLAB Simulink to provide comprehensive understanding of the issue. Simulation results demonstrated that the developed Adaptive Neuro-Fuzzy Inference SystemYbased controller would be more effective in damping signal oscillations.

Journal of Engineering and Applied Science

ABSTRACT The main aim of this work is to propose a two-stage neuro-fuzzy approach as a Failure De... more ABSTRACT The main aim of this work is to propose a two-stage neuro-fuzzy approach as a Failure Detection and Identification (FDI) scheme in dynamic processes. The first stage of the scheme is responsible for failure detection and is implemented using a Neuro-Fuzzy (N-F) model. The second stage of the scheme is responsible for failure identification and classification. The second stage is built using a Hierarchical Structure of Multilayer Feedforward Neural Networks (HSMFNN). The proposed scheme is applied on highly nonlinear boiler-turbine process for detecting, identifying, and classifying failures of different sensors in the process. Simulation results of the proposed scheme prove validity and high accuracy.