Ayman A. Aly

Work place: Mechatronics Section, Department of Mechanical Engineering, Faculty of Engineering, Assiut University, 71516, Assiut, Egypt

E-mail: draymanelnaggar@yahoo.com

Website: https://www.researchgate.net/profile/Ayman-Aly-2

Research Interests: Mobile Learning, Wireless Sensor Networks, World Wide Web, Network Security, Mobile Computing, Computer Networks, Neural Networks, Wireless Networks, Telecommunication


Ayman A. Aly has been a Professor in mechatronics engineering and the Director of the E-Learning and Distance Education Unit, College of Engineering, Taif University, Saudi Arabia, since 2008. Prior to joining Taif University, he is one of the team, who established the Mechatronics and Robotics Engineering Educational Program at Assiut University. in 2006. He was nominated and selected for inclusion in Marquis Who’s Who in the World, 30th Pearl Anniversary Edition, in 2013. He is the author of more than 160 scientific papers and seven textbooks in refereed journals and international conferences. He has supervised and examined some of a M.Sc. and Ph.D. degree students. His research interests include intelligent control of mechatronics systems, robotics design, renewable energy systems, and modelling and simulation.

Author Articles
PD Controller Structures: Comparison and Selection for an Electromechanical System

By Farhan A. Salem Ayman A. Aly

DOI: https://doi.org/10.5815/ijisa.2015.02.01, Pub. Date: 8 Jan. 2015

Many different PD controller modeling, configurations and control algorithms have been developed. These methods differ in their theoretical basis and performance under the changes of system conditions. In the present paper we review the methods used in the design of PD control systems. We highlight the main difficulties and summarize the more recent developments in their control techniques. Intelligent control systems like PD fuzzy control can be used to emulate the qualitative aspects of human knowledge with several advantages such as universal approximation theorem and rule-based algorithms.

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Artificial Neural Network Turbulent Modeling for Predicting the Pressure Drop of Nanofluid

By M. S. Youssef Ayman A. Aly

DOI: https://doi.org/10.5815/ijitcs.2013.11.02, Pub. Date: 8 Oct. 2013

An Artificial Neural Network (ANN) model was developed to predict the pressure drop of titanium dioxide-water (TiO2-water). The model was developed based on experimentally measured data. Experimental measurements of fully developed turbulent flow in pipe at different particle volumetric concentrations, nanoparticle diameters, nanofluid temperature and Reynolds number were used to construct the proposed model. The ANN model was validated by comparing the predicted results with the experimental measured data at different experimental conditions. It was shown that, the present ANN model performed well in predicting the pressure drop of TiO2-water nanofluid under different flow conditions with a high degree of accuracy.

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Robust Sliding Mode Fuzzy Control of a Car Suspension System

By Ayman A. Aly

DOI: https://doi.org/10.5815/ijitcs.2013.08.05, Pub. Date: 9 Jul. 2013

Different characteristics can be considered in a suspension system design like: ride comfort, body travel, road handling and suspension travel. No suspension system can optimize all these parameters together but a better tradeoff among these parameters can be achieved in active suspension system.
Objective of this paper is to establish a robust control technique of the active suspension system for a quarter-car model. The paper describes also the model and controller used in the study and discusses the vehicle response results obtained from a range of road input simulations. A comparison of robust suspension sliding fuzzy control and passive control is shown using MATLAB simulations.

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Velocity Feedback Control of a Mechatronics System

By Ayman A. Aly

DOI: https://doi.org/10.5815/ijisa.2013.08.05, Pub. Date: 8 Jul. 2013

Increasing demands in performance and quality make drive systems fundamental parts in the progressive automation of industrial process. The analysis and design of Mechatronics systems are often based on linear or linearized models which may not accurately represent the servo system characteristics when the system is subject to inputs of large amplitude. The impact of the nonlinearities of the dynamic system and its stability needs to be clarified.
The objective of this paper is to present a nonlinear mathematical model which allows studying and analysis of the dynamic characteristic of an electro hydraulic position control servo. The angular displacement response of motor shaft due to large amplitude step input is obtained by applying velocity feedback control strategy. The simulation results are found to be in agreement with the experimental data that were generated under similar conditions.

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Intelligent Vision Methodology for Detection of the Cutting Tool Breakage

By Abdallah A. Alshennawy Ayman A. Aly

DOI: https://doi.org/10.5815/ijitcs.2013.06.06, Pub. Date: 8 May 2013

In this paper, a new Intelligent system based on neurofuzzy for detecting and diagnostics the wear and damage of the milling cutter is presented. The compatibility between the computer vision and neurofuzzy techniques is introduced. The proposed approaches consists of capturing the milling cutter image, Fuzzy edge detection, Chain code technique for feature extraction and finally, apply the neural network on the feature. The results of the study are three different diagnostics models, The first is diagnostic model for the original profile of the perfect cutter, the second is model for the wearied profile and the third is model for the damage profile. Experimental test results show that the proposed system is reliable, practical and can be used for the easy distinguish between the wear and damage automatically.

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Mechatronics Design of a Mobile Robot System

By Ahmad A. Mahfouz Ayman A. Aly Farhan A. Salem

DOI: https://doi.org/10.5815/ijisa.2013.03.03, Pub. Date: 8 Feb. 2013

Mobile robot motion control is simplified to a DC motor motion control that may include gear system. The simplest and widespread approach to control the mobile robot motion is the differential drive style, it consists of two in-lines with each a DC motor. Both DC motors are independently powered so the desired movements will rely on how these two DC motors are commanded. Thedevelop design, model and control of Mechatronics mobile robotic system is presented in this paper. The developed robotic system is intended for research purposes as well as for educational process. The model of proposed mobile robot was created and verified using MATLAB-Simulink software.

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A Novel Circuit forThermocouple Signals Linearization Using AD Converter

By Ayman A. Aly Aly S. Abo El-Lail

DOI: https://doi.org/10.5815/ijitcs.2013.03.07, Pub. Date: 8 Feb. 2013

A novel circuit for linearization of thermocouple signals using Analog – to – Digital converter (ADC) is proposed. The present method utilizes the ratio metric property of ADCs and the converter performs analog to digital conversion as well as linearization. The resulting circuit also has provision for scaling the linearized digital output to obtain a desired full-scale value. Computational studies carried out on the proposed method gives satisfactory results for thermocouples with monotonic concave upward and downward characteristics.

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Hardware-in-the-loop of Simulation for a Hydraulic Antilock Brake System

By Ayman A. Aly

DOI: https://doi.org/10.5815/ijisa.2013.02.11, Pub. Date: 8 Jan. 2013

Hardware-In-the-Loop (HIL) of simulation policy is used as a rapid and economical tool for developing automotive systems effectively and for dangerous situations tests such as extreme road conditions or high travelling speeds. A method for building a HIL of simulation a hydraulic Antilock Braking System (ABS) based on MATLAB/Simulink is presented in this paper. The system is implemented for research purposes as well as for the application in educational process. It can help the user heightening the efficiency when developing the electronic device. Also, the system can be used as teaching demo software. Experiment tests of HIL scheme were carried to ensure the feasibility and effectiveness of the system.

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Model Reference PID Control of an Electro hydraulic Drive

By Ayman A. Aly

DOI: https://doi.org/10.5815/ijisa.2012.11.03, Pub. Date: 8 Oct. 2012

Hydraulic cranes are inherently nonlinear and contain components exhibiting strong friction, saturation, variable inertia mechanical loads, etc. The characteristics of these non-linear components are usually not known exactly as structure or parameters. For these reasons, tuning of the traditional PID controller parameters to control this system for the required performance faces a strong challenge. 
In this paper a new approach to design an adaptive PID control has the ability to solve the control problem of highly nonlinear systems such as the hydraulic crane was proposed. The core of the design method depends on comparing the performance of the Model Reference (MR) response with the nonlinear model response and feeding an adaptation signal to the PID control system to eliminate the error in between. It is found that the proposed MR-PID control policy provided the most consistent performance in terms of rise time and settling time regardless of the nonlinearities.

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Intelligent PI Fuzzy Control of An Electro Hydraulic Manipulator

By Ayman A. Aly Aly S. Abo El-Lail Kamel A. Shoush Farhan A. Salem

DOI: https://doi.org/10.5815/ijisa.2012.07.06, Pub. Date: 8 Jun. 2012

The development of a fuzzy-logic controller for a class of industrial hydraulic manipulator is described. The main element of the controller is a PI-type fuzzy control technique which utilizes a simple set of membership functions and rules to meet the basic control requirements of such robots. Using the triangle shaped membership function, the position of the servocylinder was successfully controlled. When the system parameter is altered, the control algorithm is shown to be robust and more faster compared to the traditional PID controller. The robustness and tracking ability of the controller were demonstrated through simulations.

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Parameter Tuning via Genetic Algorithm of Fuzzy Controller for Fire Tube Boiler

By Osama I. Hassanein Ayman A. Aly Ahmed A. Abo-Ismail

DOI: https://doi.org/10.5815/ijisa.2012.04.02, Pub. Date: 8 Apr. 2012

The optimal use of fuel energy and water in a fire tube boiler is important in achieving economical system operation, precise control system design required to achieve high speed of response with no overshot. Two artificial intelligence techniques, fuzzy control (FLC) and genetic-fuzzy control (GFLC) applied to control both of the water/steam temperature and water level control loops of boiler. The parameters of the FLC are optimized to locating the optimal solutions to meet the required performance objectives using a genetic algorithm. The parameters subject to optimization are the width of the membership functions and scaling factors. The performance of the fire tube boiler that fitted with GFLC has reliable dynamic performance as compared with the system fitted with FLC.

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