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Research Areas
The faculty of the AUS Mechatronics Engineering Graduate Program is drawn from disparate and outstanding talents in the fields of electrical engineering, computer engineering and mechanical engineering. They have established themselves at the pinnacle of their respective fields during their tenure at AUS, and have distinguished achievements as their legacy. The following is a comprehensive list of the area of expertise of the combined AUS mechatronics faculty:
- autonomous systems such as unmanned vehicles, field robotics
- mechanical and electromechanical design/analysis and synthesis
- computer software/hardware systems and applications
- advance simulation modeling and control
- intelligent industrial automation and PLC controllers
- online monitoring and diagnosis
- measurements systems, data acquisition, signal processing and networking
- electro-pneumatic and electro-hydraulics
- microprocessors/microcontrollers and embedded systems
- control: PLC, DCS and SCADA
- artificial intelligence: fuzzy logic and neural networks
- data acquisition and networking
- image processing and digital signal processing
- biomedical instrumentation and imaging
- microwave systems, antennas, wave propagation, microwave imaging, radars and electromagnetics
- speech recognition/pattern classification and speech enhancement
Mechatronics research areas can be divided into the broad categories shown below.
Description of Research Areas
Autonomous Systems: Field Robotics, Artificial Intelligence and Multi-Agent Systems
Autonomous systems can be defined as the field of technical devices that have some onboard intelligence as well as standalone and communication capabilities. An autonomous system can be seen as a combination of a computational core, sensors and motors, a finite store for energy and a suited control allowing for flexible stand-alone operation. This type of devices has grown in shortest time into a significant market and will be one of the leading technologies of the 21st century.
Artificial intelligence is the study of ideas to bring into being machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention. Each such machine should engage in critical appraisal and selection of differing opinions within itself. Produced by human skill and labor, these machines should conduct themselves in agreement with life, spirit and sensitivity, though in reality, they are imitations.
Faculty involved in related research
Dr. Mohammed Ameen Al-Jarrah
Dr. Joachim Diederich
Dr. Rached Dhaouadi
Dr. Yousef Al-Assaf
Dr. Khaled Assaleh
Dr. Mamoun Abdel-Hafez
Mobile Ad-Hoc Wireless Sensors Networks
Wireless ad hoc networks are formed by a set of hosts that communicate with each other over a wireless channel. Each node has the ability to communicate directly with another node (or several of them) in its physical neighborhood. They operate in a self-organized and decentralized manner and message communication takes place via multi-hop spreading. Any packet sent from one node to another may pass through a number of intermediate nodes acting as routers.
Recently, wireless ad hoc technology has been utilized for the development and deployment of wireless sensor networks: wireless ad hoc networks consisting of individual sensor nodes distributed over a given area and used to monitor some physical phenomenon in the environment. Typical sensed phenomena include temperature, humidity, position, speed, motion and others, used in applications ranging from health care and logistics to agriculture, forestry, civil and construction engineering, to surveillance and military applications. The importance of such networks is increasing rapidly with advances in technology that result in smaller, cheaper and power-efficient devices.
Faculty involved in related research
Dr. Abdul-Rahman Al-Ali
Dr. Mohammed Ameen Al-Jarrah
Dr. Taha Landolsi
Embedded Systems and Real-Time Systems
Mechatronical applications mostly include microcontrollers/microprocessors and software. Many of these applications are time critical and safety critical and must therefore be predictable and robust. Models and methods are used for design of hard real-time control software for mechanical applications. Modern computer-based "control engineering" tools are used for modeling, simulation, and rapid prototyping of control applications and then the control algorithms are implemented on microprocessors/microcontrollers with real time operating systems.
Real-time applications have evolved considerably over the past decades from closed and well-studied systems to environments that are unpredictable, and with considerable uncertainty in workload and resource requirements. The great challenge posed by these new applications to the research community is how to achieve predictable system performance and temporal behavior in the presence of such uncertainty and without precise knowledge of worst-case load patterns. Areas of growing interest include feedback architectures for adaptive real-time computing, theory for performance guarantees under uncertainty, integrated resource scheduling and feedback control, control-theoretical models of dynamic real-time systems, application of control theory for controlling timing behavior, and optimal, robust or adaptive feedback control in real-time systems.
Faculty involved in related research
Dr. Abdul-Rahman Al-Ali
Dr. Tarik Ozkul
Dr. Rached Dhaouadi
Dr. Mohammed Ameen Al-Jarrah
Industrial and Process Control System and Machine Condition Monitoring
Process control, factory automation and plant information systems are major concerns in determining the cost of construction or modernization for industrial manufacturing facilities. Projects utilizing distributed control systems, programmable logic controllers, coordinated drives, motion controllers, intelligent valves, process variable transmitters and computers require innovation and experience to fully integrate the hardware and software. The ever-increasing demands for higher quality and reductions in cost must be met in order to gain the competitive edge in a global market. Automation is frequently the answer to improve production efficiencies. Examples of industries where process control applications are utilized include aerospace and automotive industries, power systems, and manufacturing industries to name a few.
Faculty involved in related research
Dr. Nabeel Abdel-Jabbar
Dr. Rached Dhaouadi
Dr. Yousef Al-Assaf
Dr. Ibrahim Deiab
Dr. Ameen El-Sinawi
Sensor and Data Fusion and Machine Vision
Digital signal processing is the changing or analyzing of information that is measured as discrete sequences of numbers. A more exact definition of DSP would be the computer manipulation of analog signals that have been sampled and converted to digital form.
The Internet has grown tremendously since it has been commercialized. Growth in speed and quality of the Internet has opened up new applications and services and has made possible large volumes of data to be transferred between locations with relative ease and security. This paved the way for bandwidth consuming applications including video conferencing, voice over IP and real-time monitoring of devices over the Internet. New generations of sensors called smart sensors are now being implemented with wireless capability, enabling them to access the net through various access points, and thus be monitored online.
Faculty involved in related research
Dr. Khaled Assaleh
Dr. Mourad Barkat
Dr. Hasan Al Nashash
Dr. Yousef Al-Assaf
Dr. Abdul-Rahman Al-Ali
Dr. Tarik Ozkul
Smart Materials, Nano- and Microelectromechanical Systems (MEMS)
The miniaturization of components, particularly in computer electronics, telecommunication and transportation industries, has been at the forefront of economic growth for the last three decades. MEMS devices are now produced in large volumes due to the new demands on warranty periods, reliability of components, emissions and safety standards, performance, comfort and costs. Microsensors and actuators alone represent a more than $30 billion market.
Nanotechnology lies at the intersection of chemistry, physics, biology, electrical engineering, computer science and material science. Of direct significance is the deeper understanding and control of structures at atomic, molecular and supramolecular levels where materials and systems can exhibit novel and significantly improved physical, chemical and biological properties. Nanotechnology is important for modeling the properties of materials as well as designing of new materials that are economical with superior performance. Nonotechnologies are important in designing new systems with super sensing abilities and with a distributed intelligence.
Mechanical engineering and material sciences form the core of mechatronics. New and smart materials make it possible to create self-monitoring and “healing” devices. Nanotechnology will play an important role, allowing the creation of complete and robust systems on a minute scale.
Faculty involved in related research
Dr. Hany El-Kadi
Dr. Ameen El-Sinawi
Dr. Mohamed Gadalla
Dr. Nasser Qaddoumi
Biomechatronics
Biomechatronics is the interdisciplinary study of biology, mechanics and electronics. Biomechatronics focuses on the interactivity of biological organs (including the brain) with electromechanical devices and systems. Universities and research centers worldwide have taken notice of biomechatronics in light of its potential for development of advanced medical devices and life-support systems. Primitive biomechatronic devices have existed for some time; the heart pacemaker and the defibrillator are examples. More exciting biometchatronic possibilities that scientists foresee in the near future include pancreas pacemakers for diabetics, mentally controlled electronic muscle stimulators for stroke and accident survivors, cameras that can be wired into the brain allowing blind people to see, and microphones that can be wired into the brain allowing deaf people to hear.
Faculty involved in related research
Dr. Saad Ahmed
Dr. Hasan Al Nashash
Dr. Khaled Assaleh
Dr. Ghaleb A. Husseini
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