Research Title: Multi-robot system for real-time sensing and monitoring

Author: Mohammed Mahdi Ali, Published Year: 2014

15th International Workshop on Research and Education in Mechatronics (REM), Egypt

Faculty: Engineering and Technology

Abstract: The main objective of this research is to design and realize a multi-robot system for real-time sensing and monitoring suitable for hazardous and/or unreachable environment. The proposed system has three mobile robots; main, rover and eye. Each mobile robot has its own embedded microcontroller and set of sensors. Wireless communications between local site and these mobile robots are achieved by WiFi, ZigBee and Bluetooth techniques, and can be accessed through the internet. Wireless teleoperation of these mobile robots is a challenging task that requires an efficient interface and a reliable real-time control algorithm to avoid obstacles. The proposed system enables the authorized operator to send commands to the mobile robots, and receive scanned data and images from the environment through the internet. The mechanical part of the remote station has been built after careful selection of the design parameters using CAD/CAM tools. While, the system hardware and software parts of the embedded controllers were implemented using PROTEUS development tool to obtain the suitable design parameters. Then, real experiments have been achieved to demonstrate the system performance including the wireless teleoperation of the three mobile robots, their navigation to avoid obstacles, and real-time sensing and monitoring.

Keywords: Mobile robot, Multi-robot system, Remote sensing and monitoring, Wireless sensor networks, Obstacles avoidance

Research Title: Real-time monitoring and intelligent control for greenhouses based on wireless sensor network

Author: Mohammed Mahdi Ali, Published Year: 2014

11th International Multi-Conference on Systems, Signals & Devices (SSD14), Barcelona, Spain

Faculty: Engineering and Technology

Abstract: The main objective of this research is to design and implement a real-time monitoring and control of several environmental parameters for group of greenhouses. Each greenhouse is considered as a node in a wireless sensor network. A single-board microcontroller-based system has been designed and implemented to monitor and control several variables and maintain desired condition in each greenhouse. A rule-based fuzzy controller has been designed to control the microclimate of each greenhouse. The proposed system enables the farmer to monitor both the internal environment of the greenhouse. Also, the farmer can send commands to turn ON or OFF certain devices in a selected greenhouse through wireless communications. Simulated and real results have been achieved to demonstrate the system performance and real-time remote monitoring and control activities

Keywords: Greenhouse automation, Remote monitoring and control, Fuzzy control, Intelligent control, Wireless sensor network.

Research Title: Maximum power point neuro-fuzzy tracker for photovoltaic arrays

Author: Mohammed Mahdi Ali, Published Year: 2011

Eighth International Multi-Conference on Systems, Signals & Devices, Tunisia

Faculty: Engineering and Technology

Abstract: Every photovoltaic (PV) array has unique point at which maximum power can be generated and extracted for different atmospheric conditions and output load. The maximum power point tracking is therefore critical for the success of PV arrays. All methods proposed earlier suffer from slow response; they oscillate around the maximum power point and ignoring the atmospheric conditions changing. This paper presents an intelligent method of maximum power point tracking for photovoltaic systems. It is based on tracking the maximum power point by monitoring the voltage and current of the solar array and adjusting the duty cycle of the PWM switching signal of a buck-boost DC/DC converter. Both conventional fuzzy logic controller and neuro-fuzzy controller are implemented to evaluate PV system performance. Functional neuro-fuzzy controller has advantages over that of fuzzy logic both in speed and generalization features. Obtained results show that the neuro-fuzzy controller can deal with different load and weather conditions and deliver more power from the photovoltaic systems.

Keywords: Photovoltaic System, Solar cells, Fuzzy logic, Neuro-fuzzy, Maximum power point tracking

Research Title: THE EFFECTS OF MOS LAYERS ON SENSING PROPERTIES OF MOS PHOTOSENSOR

Author: Mohammed Mahdi Ali, Published Year: 2013

INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS, 6, 3

Faculty: Engineering and Technology

Abstract: In this research work, many samples of metal –oxide –silicon photo sensors were laboratory prepared by thermal evaporation techniques. Some silicon samples were left in the air for a predefined time for SiO2 to grow naturally, while others were thermally coated with measured thickness of SiO. A number of the samples were coated with nickel while others with aluminum and one sample was coated with indium. Various tests and measurements were conducted; these include transmittance tests with a range of wavelength and for different thicknesses. The ideality factors of the samples and the potential barrier height were calculated from I-V and C-V characteristics. The photo generated current of the samples were also measured at photoconductive mode under reverse voltage. Quantum efficiency measurement indicated that native oxide samples provided higher quantum efficiency than those thermal

Keywords: Schottky Barrier Diode, Photo sensor, MOS Photo sensor, Silicon Photo sensor:

Research Title: Wheelchair Neuro Fuzzy Control and Tracking System Based on Voice Recognition

Author: Mohammed Mahdi Ali, Published Year: 2020

Sensors, 20, 10

Faculty: Engineering and Technology

Abstract: Autonomous wheelchairs are important tools to enhance the mobility of people with disabilities. Advances in computer and wireless communication technologies have contributed to the provision of smart wheelchairs to suit the needs of the disabled person. This research paper presents the design and implementation of a voice controlled electric wheelchair. This design is based on voice recognition algorithms to classify the required commands to drive the wheelchair. An adaptive neuro-fuzzy controller has been used to generate the required real-time control signals for actuating motors of the wheelchair. This controller depends on real data received from obstacle avoidance sensors and a voice recognition classifier. The wheelchair is considered as a node in a wireless sensor network in order to track the position of the wheelchair and for supervisory control. The simulated and running experiments demonstrate that, by combining the concepts of soft-computing and mechatronics, the implemented wheelchair has become more sophisticated and gives people more mobility.

Keywords: wheelchair control; voice recognition; autonomous wheelchair; ANFIS; V-REP; mechatronics

Research Title: Power Peaks Allocation Based on Averaging-Adaptive Wavelet Transform

Author: Mohammed Mahdi Ali, Published Year: 2016

International Journal of Circuits, Systems and Signal Processing, 10

Faculty: Engineering and Technology

Abstract: One of Orthogonal Frequency Division Multiplexing deficiency has been taken into consideration in this work. A proposition has been made to tackle the Peak to Average Power Ratio (PAPR) problem. The proposed work will be based on a special averaging adaptive wavelet transformation (SAAWT) process. It will be compared with two main works that has been published previously; a neural network (NN)-based and a special averaging technique (SAT)-based. In the NN work, the learning process makes use of a previously published work that is based on three linear coding techniques. The proposed work (SAAWT) consists of three main stages; extracting the needed features, de-noising and the optimization criterion. SAAWT has an enhancement over the SAT that will take the noise clearance enhancement into its consideration. It uses 136880 different combinations of de-noising parameters that are experimentally computed to get the most efficient result with respect to the MSE, SNR and PSNR values. A MATLAB simulation-based of such works has been made in order to check the proposition performance. In this simulation, both of the BER and CCDF curves have been taken into consideration. Furthermore, the bandwidth and channel behaviors have been remaining constant. Moreover, two kinds of data have been imposing to this simulation; a random data that is generated randomly by making use of the MATLAB features and a practical data that have been extracted from a funded project entitled by ECEM. From the previously published work the SAT shows promising results in reducing the PAPR effect reached up to 75% over the work in the literature and over the NN-based work. Under the cost of increasing complexity, SAAWT gives further reduction over the SAT reaches up to 6%. This drawback will be examined in the future work.

Keywords: Orthogonal Frequency Division Multiplexing, Neural Network, Linear Codes, De-noising Parameters, Wavelet, Moving Average Filter

Research Title: Efficiency enhancement based on allocating bizarre peaks

Author: Mohammed Mahdi Ali, Published Year: 2016

International Journal of Wireless & Mobile Networks (IJWMN), 8, 4

Faculty: Engineering and Technology

Abstract: A new work has been proposed in this paper in order to overcome one of the main drawbacks that found in the Orthogonal Frequency Division Multiplex (OFDM) systems, namely Peak to Average Power Ratio (PAPR). Furthermore, this work will be compared with a previously published work that uses the neural network (NN) as a solution to remedy this deficiency. The proposed work could be considered as a special averaging technique (SAT), which consists of wavelet transformation in its first stage, a globally statistical adaptive detecting algorithm as a second stage; and in the third stage it replaces the affected peaks by making use of moving average filter process. In the NN work, the learning process makes use of a previously published work that is based on three linear coding techniques. In order to check the proposed work validity, a MATLAB simulation has been run and has two main variables to compare with; namely BER and CCDF curves. This is true under the same bandwidth occupancy and channel characteristics. Two types of tested data have been used; randomly generated data and a practical data that have been extracted from a funded project entitled by ECEM. From the achieved simulation results, the work that is based on SAT shows promising results in reducing the PAPR effect reached up to 80% over the work in the literature and our previously published work. This means that this work gives an extra reduction up to 15% of our previously published work. However, this achievement will be under the cost of complexity. This penalty could be optimized by imposing the NN to the SAT work in order to enhance the wireless systems performance.

Keywords: Orthogonal Frequency Division Multiplexing, Neural Network, Linear Codes, Wavelet, Moving Average Filter.

Research Title: Wireless Cellular Systems Performance Improvement Based on Neural Network

Author: Mohammed Mahdi Ali, Published Year: 2012

INTERNATIONAL JOURNAL OF COMMUNICATIONS, 6, 4

Faculty: Engineering and Technology

Abstract: In this paper, a neural network (NN) part has been imposed to overcome a previously mitigated drawback that is found in Orthogonal Frequency Division Multiplex technology (OFDM) systems. In the learning process we make use of the results obtained from the previously published work to reduce the Peak to Average Power Ratio (PAPR) problem based on different linear coding techniques. The proposed technique shows that an improvement in the OFDM technology performance has been achieved based on reducing the system’s complexity. Moreover, the reduction percentage of the PAPR compared to the previously published one; which combats the PAPR based on Low Density Parity Check (LDPC), turbo coding and convolutional coding has been attained exactly. Our simulation results show that 15% reduction in PAPR over current values in the literature can be achieved depending on the system’s type. This is in addition to that the use of NN reduces the overall OFDM system's complexity. This is because that in the proposed technique the system does not need to send extra data to recombine the processed OFDM symbols at the receiver side. Thus, the performance improvement could be attained. Keywords—Multiple Input Multiple Output, Orthogonal Frequency Division Multiplexing, Neural Network, Linear codes.

Keywords: Multiple Input Multiple Output, Orthogonal Frequency Division Multiplexing, Neural Network, Linear codes.

Research Title: Design with Simulation of an Iterative Fuzzy Logic Controller (IFLC)

Author: Mohammed Mahdi Ali, Published Year: 2006

Asian Journal of Information Technology, 5, 1

Faculty: Engineering and Technology

Abstract: As the need for control is extended to systems of increasing complexity which is also often highly non-linear, rule-based fuzzy logic control was one of the successful solutions. An Iterative Fuzzy Logic Controller (IFLC) is designed based on finding the best input-output scale factors settings that are found during iterations to give an acceptable controlled behavior. To verify the ability of the proposed IFLC, a promising simulation study on different kinds of control systems has been pointed out

Keywords: Iterative Fuzzy Logic Controller (IFLC), Fuzzy Production Rules (FPRs), Input-Output scale factors (Ge, Gce, and Gu)

Research Title: A Hierarchical Neuro-Fuzzy MRAC of a Robot in Flexible Manufacturing Environment

Author: Mohammed Mahdi Ali, Published Year: 2004

The International Arab Journal of Information Technology, Vol. 1, No. 2,

Faculty: Engineering and Technology

Abstract: In one hand, the Model Reference Adaptive Control (MRAC) architecture has been widely used in linear adaptive control field. The control objective is to adjust the control signal in a stable manner so that the plant’s output asymptotically tracks the reference model’s output. The performance will depend on the choice of a suitable reference model and the derivation of an appropriate learning scheme. While in the other hand, clusters analysis has been employed for many years in the field of pattern recognition and image processing. To be used in control the aim is being to find natural groupings among a set of collected data. The mean-tracking clustering algorithm is going to be used in order to extract the input-output pattern of rules from applying the suggested control scheme. These rules will be learnt later using the widely used Multi-layer perceptron neural network to gain all the benefits offered by those nets. A hierarchical neuro-fuzzy MRAC is suggested to control robots in a flexible manufacturing system. This proposed controller will be judged for different simulated cases of study to demonstrate its capability in dealing with such a system.

Keywords: : MRAC, mean-tracking clustering algorithm, MLP neural nets, computer control, real-time systems, robots, FMS