Bachelor of Science in Mechatronics and Robotics Engineering

402207

Applied Electronic Circuit

2–3–3

Basic DC Circuits, General DC circuit analysis, Transient Circuits Basic AC Circuits, Diodes, and their applications, Transistors, Operational Amplifiers, Basic Combinational Circuits, Decoders, Adders and Multiplexers, Transformers.

Prerequisite:

1430117 – Physics II

Pre/Co-requisite:

None

402210

Industrial Power Electronics

3–0–3

This course covers the fundamentals of semiconductor devices used in power electronics (power diodes, Power bipolar junction transistors, SCR, IGBT, field effect transistors FET and MOSFET). It deals also with the application of electronic circuits in industrial processing and power conversion. It covers the topics of, DC–DC power conversion (Choppers), AC–DC power conversion (Rectifiers), DC–AC power conversion (inverters), AC voltage controllers, and Industrial applications.

Prerequisite:

0402207 –Applied Electronic Circuit

Pre/Co-requisite:

None

402211

Electrical Drives and Actuators

2–0–2

Fundamentals of magnetic circuits and Faraday’s Law, basics of electromagnetics and electromechanical energy conversions. Transformers, Basics of DC and AC machines and drives, steady–state analysis of AC and DC motor drives, BLDC motors, Stepper motors, Reluctance motors, AC and DC servo motors, Electrical actuators, and electric Valves.

Prerequisite:

0402207 –Applied Electronic Circuit

Pre/Co-requisite:

None

402349

Analog and Digital Signal Processing

3–0–3

The course deals with the representation and analysis of analog and discrete–time signals and systems. It covers continuous and discrete convolution, Fourier series and Fourier transform, discrete–time, and discrete–time Fourier transform. Topics also include Z–transform, and analog and digital filters.

Prerequisite:

0405221 – Engineering Statistics and Stochastic Processes

Pre/Co-requisite:

0408318 – Instrumentation and Measurement

408151

Introduction to MRE

2–3–3

This course aims to expose students to the mechatronics and robotics engineering profession. Mechatronics discipline synergistically combines Mechanical, electrical and computer engineering, as well as robotic systems. In this course, mechatronics and robotics systems are presented by emphasizing their components and the fundamentals behind their functionality. Moreover, principles of ethics, problem–solving, and teamwork are covered. A laboratory is introduced to gain the knowledge in conducting an experiment, running data analytics, and using a software package, to solve mechatronics and robotics engineering problems.

Prerequisite:

None

Pre/Co-requisite:

None

408200

Dynamics for Mechanical Engineering

3–0–3

Kinematics of a rigid body, absolute and relative motion analysis; Kinetics of a rigid body, force and acceleration, work and energy, impulse and momentum; Vibrations, undamped and damped free and forced one–degree–of–freedom vibration of a rigid body, base excitation, vibration isolation.

Prerequisite:

0408251 – Statics and Strength of Materials

Pre/Co-requisite:

None

408251

Statics and Strength of Materials

2–3–3

Knowledge and understanding of vector resultant of forces in two and three dimensions; type of structural supports; equilibrium of particles and rigid bodies; analysis of internal forces in beams; static and kinetic friction; centroids of lines, areas, and volumes; second moments of area. Simple states of stress and strain; Hook’s law; stress and strain under different types of loading, axial, torsion, and bending loads; shear force and bending moment diagrams; stress transformation; beam deflection. An embedded lab that emphasizes the practical side is included.

Prerequisite:

None

Pre/Co-requisite:

0408151 – Introduction to MRE

408252

Fluid & Thermal Sciences

2–3–3

Basic principles of thermodynamics, fluid mechanics and heat transfer. Thermodynamics concepts and definitions. Properties of pure substances, First law of thermodynamics. System and control volume analyses. The second law of thermodynamics. Basic principles of fluid mechanics. Fluid statics. Conservation laws. Energy equations. Flow in pipes. Heat transfer modes. Conduction, convection, and radiation. The experimental topics include Hydrostatic Forces and Centre of Pressure, Pascal's Law, Verification of Bernoulli’s Theorem, Frictional Losses in Piping Systems, Pelton Turbine, Linear Heat Conduction, Law of Radiation, Free or natural convection heat transfer, Free or natural convection heat transfer, forced convection heat transfer, Shell & Tube Heat Exchanger, and Cross flow heat exchanger.

Prerequisite:

None

Pre/Co-requisite:

1440261 – Differential Equations for Engineers

0408200 – Dynamics for ME

408253

Mechanical Components Design

2–3–3

This course covers static failure theories; fatigue failure theories; design of machine elements to include the design of columns, shafts, and fasteners and bolted connections, different types of gears (spur, helical, bevel, and worm gears), lubrication and journal bearings, springs, flexible mechanical elements, welding. The course also includes team project(s). An internal lab that emphases on the practical side/Software is included.

Prerequisite:

0408251 – Statics and Strength of Materials

Pre/Co-requisite:

None

408300

Analytical Methods in Engineering

3–0–3

Discrete–time systems and the Z–transform. Sampling and reconstruction. Open–loop and closed–loop discrete–time systems. System time–response characteristics. Stability analysis techniques. Digital controller design. State–space representations of discrete–time systems. Pole–assignment design and stat estimation. Linear quadratic optimal Control.

Prerequisite:

1440261 – Differential Equations for Engineers

Pre/Co-requisite:

None

408318

Instrumentation and Measurements

3–0–3

Introduction to measurement system components, measurement process, errors and sources of errors, signal and noise in instrumentation, filtering, elements of signal processing in instrumentation, sensors, transducers, analog and digital devices, measurement system behavior, sampling and data acquisition, applications of measurement systems.

Prerequisite:

0408232 – Fluid and Thermal Sciences

0402207 – Applied Electronic Circuit

Pre/Co-requisite:

None

408320

Modelling and Control of Dynamic Systems

2–3–3

This course teaches the students the modelling of simple and multi–physics systems including the mechanical, electrical, fluid and thermal system. This include a review of such system and the use of linear graph and state space representation. The course teaches different controller techniques including the PI, PD, PID, Lead/Lag compensator, and lag/lead compensator. Different approaches of designing the controller will be considered including the root locus, and bode plot designs. The stability analysis is included. The course is extended to cover the observer design and an Introduction to digital control. Simulation tools using Matlab/Simulink will be used to illustrate the different types of systems and controllers and a lab is designed to cover the practical side of such systems.

Prerequisite:

0408318 – Instrumentation and Measurements

Pre/Co-requisite:

None

408351

Classic and Modern Manufacturing Processes

2–3–3

This course covers both classical and modern–computerized manufacturing process. The first part includes the traditional manufacturing processes of materials such as metal casting, joining, metal cutting, rolling, forging, extrusion and drawing. Later, the course introduces the computer–aided design (CAD) and computer–aided manufacturing (CAM) theory and their applications. These include CAD/CAM systems, Geometric modeling, mechanical assembly, process planning and Tool path generation, and Computer control of machines and processes in manufacturing systems. It also includes a project that emphasis on CNC applications. An internal lab that emphases on the practical side is included.

Prerequisite:

0408253 – Mechanical Design Components

Pre/Co-requisite:

None

408352

Engineering Analysis for MRE

3–0–3

This course covers matrix theory and linear algebra, and their applications in Mechatronics and Robotics. The course emphasis on forming the matrices, matrices’ operations, inverse, solving system of linear equations analytically and numerically, Echelon form, Norms, Orthogonality, determinates, Cramer’s rule, space and subspaces, rank, basis, Eigenvalues and eigenvectors. Moreover, it covers solving ODE using matrix format both analytically and numerically. MATLAB is used to solve complex mechatronics and robotics engineering problems utilizing the previous topics.

Prerequisite:

1501113 – Programming for Engineers

1440261 – Differential Equations for Engineers

Pre/Co-requisite:

None

408457

Mechatronics Systems Design and Integration

2–3–3

This course provides a practical step–by–step approach to design mechatronics systems by integrating mechanical, electrical and computer engineering disciplines within a unified framework. These steps include specifications, conceptual design, analysis, modeling, simulation bread–boarding, prototyping, integration, verification, installation, testing and project management and economics. The course links different pre–requisite courses, from programming to real–time computation tasks; mechanical components, digital logic, signal processing, measurement and sensing, and control of mechatronic systems. An internal lab that emphases on the practical side/Software is included.

Prerequisite:

01502344 – Microcontroller Systems

0402211 – Electrical Drives and actuators

Pre/Co-requisite:

0402318 – Instrumentation and Measurement

408455

Robotics & Automation 1

2–3–3

This course provides an introduction to robotics and automation. The first part covers the fundamentals of the industrial robot such as manipulator, including rigid motions, homogeneous transformations, forward and inverse kinematics, velocity kinematics, and trajectory generation. The second part of the course covers the pneumatic systems, as part of automation system, used to derive the robot manipulator. Moreover, this part includes the choice of the suitable components as well as the design and simulation of pneumatic circuits. An internal lab that emphases on the practical side/Software is included.

Prerequisite:

0408300 – Analytical Methods in Eng.

0408352 – Engineering Analysis for MRE

Pre/Co-requisite:

0408320 – Modelling and Cont. of Dynamic Systems

408456

Robotics & Automation 2

2–3–3

This course introduces the state–of–the–art technologies in mobile robotics, such as locomotion, sensing, communication, localization and mapping, navigation, etc . The first part covers the kinematics, locomotion and navigation of mobile robot as well as the sensors and actuators beside the noise. The second part of the course covers the hydraulic systems and programmable logic controller (PLC) used for controlling the circuit. An internal lab that emphases on the practical side and Software packages (i.e. Automation Studio, ladder diagram and Mindstorm EV3 software) is included.

Prerequisite:

0408455 – Robotics & Automation 1

Pre/Co-requisite:

None

408451

Senior Design Project I

1–0–1

Students work on a major design project, applying and integrating the knowledge gained in previous course work to develop solutions to an open–ended problem. Students apply the basic elements of the modern engineering design methodology to learn how to plan a project, work on teams, and incorporate standards and constraints. Another alternative, student teams could investigate a research topic in some area of Mechatronics and Robotics Engineering from the current literature under the supervision of the faculty advisor. Instructor deliver a series of lectures/seminars devoted to discussing design–related issues, such as systematic methods of idea or concepts generation of multiple design alternatives (TRIZ and brainstorming), and methods to select the optimal design subject to various constraints (House of Quality). In addition to seminars devoted to project–related issues and student presentations. A project proposal, oral presentations, and a comprehensive final report are required.

Prerequisite:

90 Credit Hours,

01502344 – Microcontroller Systems

Pre/Co-requisite:

None

408452

Senior Design Project II

3–0–3

Students work on a major design project, applying and integrating the knowledge gained in previous course work to develop solutions to an open–ended problem. Students apply the modern engineering design methodology to choose from alternative design subject to realistic constraints, and incorporate standards and constraints. Student teams work together to design, build, refine and test complete hardware or/and software systems to meet specifications. Another alternative, student teams work together to design and run experiments, analyze data, and conclude on research findings. A project final product (prototype, software code, research/experiments findings, etc.…), oral presentations, poster presentation, and a comprehensive final report are required.

Prerequisite:

0408451 – Senior Design Project I

Pre/Co-requisite:

None

408453

Practical Training I in MRE

1–3–1

This is the first of two required Practical Training courses. The course consists of seminars and workshops, some of which conducted by speakers from the industry, and field trips that cover five major topics. These are: multistep work processes; professional organizations, development, licensure, and ethics; national and local regulations and laws; entrepreneurships, business models, leadership; new technologies in the field.

Prerequisite:

90 Credit Hours

Pre/Co-requisite:

None

408454

Practical Training II in MRE

2–0–2

This is the second of two required Practical Training courses. The course consists of a supervised professional practice of engineering in a workplace for a minimum of 20 hours per week over a period of 16 weeks. The practice should cover different tasks and multistep work processes in the career of engineers in the field. It should prepare the trainee for future employment by engaging him/her in solving practical engineering problems, making informed decisions, upholding standards of ethics in the industry, using latest technologies, and working in a team.

Prerequisite:

0408453 – Practical Training I in MRE

Pre/Co-requisite:

None

1430118

Physics II Laboratory

0–3–1

Various experiments covering the topics mentioned in Physics (II) course.

Prerequisite:

1430116 – Physics 1 Lab

Pre/Co-requisite:

1430117 – Physics II

1501113

Programming for Engineers

3–0–3

This course covers introductory concepts in computer programming using C++. We assume that students have no programming experience. There is an emphasis on both the concepts and practice of computer programming. This course covers principles of problem solving and requires a number labs and programming assignments. You should expect to spend at least 8 hours on average per week on this course.

Prerequisite:

None

Pre/Co-requisite:

None

1502244

Digital Systems

2–3–3

This course covers topics related to number systems and conversion between systems based on different radices. The course introduces Boolean algebra and its application in the analysis and design of logic circuits. Then, common logic gates and their operation is introduced. The course then goes through different techniques for analysis and synthesis of combinational and sequential logic systems.

The design and implementation of the logic circuits will be accomplished practically by using Hardware Description Language (HDL).

Prerequisite:

31 Credit Hours

Pre/Co-requisite:

None

1502344

Microcontroller Systems

2–3–3

This course covers the basic applications of a microcontroller in a complex engineering system. The course discusses the general structure of a microcontroller and principles of peripheral interfacing and implementation of control systems using a microcontroller. The course involves application of C language programming in a microcontroller environment. Theoretical concepts are applied through laboratory experiments and a practical course project.

Prerequisite:

0402210 – Industrial Power Electronics, and

1502244 – Digital Systems

Pre/Co-requisite:

None

1502410

Artificial Intelligence for Engineers

3–0–3

This course will focus on designing and employing Artificial Intelligence models to solve engineering problems. This includes relevant data analytics concepts and models such as neural networks, decision tree, support vector machine, metaheuristic algorithms and regression analysis. Models will be evaluated using appropriate datasets and evaluation criteria. A range of tools such as Python, Weka, MATLAB and similar tools will be used in this course.

Prerequisite:

0405221 – Engineering Statistics and Stochastic Processes

Pre/Co-requisite:

None

402434

Digital Control Systems

3–0–3

Discrete–time systems and the Z–transform. Sampling and reconstruction. Open–loop and closed–loop discrete–time systems. System time–response characteristics. Stability analysis techniques. Digital controller design. State–space representations of discrete–time systems. Pole–assignment design and stat estimation. Linear quadratic optimal Control.

Prerequisite:

0408320 – Modelling and Control of Dynamic Systems

Pre/Co-requisite:

None

402436

Applied Control Engineering

3–0–3

Introduction to process control. Feedback and feedforward control configurations. Modeling of dynamic systems: Time delays, high order systems, multivariable systems. Process identification. Analysis and controller design performances. PID controller tuning. Intelligent controller tuning. Advanced control techniques. Process interaction and decoupling control. Introduction to distributed computer control systems and digital Control issues.

Prerequisite:

0408320 – Modelling and Control of Dynamic Systems

Pre/Co-requisite:

None

408345

Mechanical Vibrations

3–0–3

This course covers the response of discrete single, two– and multi–degree of freedom systems to vibration. Cases of free and forced vibration, damped and undamped systems will be covered. Base excitation, rotating imbalance, vibration Isolation, introduction to human responses to vibration.

Prerequisite:

0408200 – Dynamics for ME

1440261 – Differential Equations for Engineers

Pre/Co-requisite:

None

408442

Reverse engineering

3–0–3

This course teaches the reverse engineering methodology through projects where students disassemble and re–assemble a device/item/product, while document the testing and analyzing each component is found and examine its functionality. This provide with tools that are used to understand the “solutions” that are already available in the market. It also helps in understanding the market need, and how to customize a product.

Prerequisite:

0408318 – Instrumentation and Measurement

Pre/Co-requisite:

None

408443

MEMS and NEMS

3–0–3

This course will introduce the fundamental basis of MEMS (Microelectromechanical Systems) and NEMS (Nanoelectromechanical Systems) including design, analysis, fabrication, integration, packaging, and testing. The course also covers the analysis of the performance aspects of electromechanical transducers including sensors and actuators. In addition, this course will also introduce the most recent development of micro–/nano–fabrication technologies, and up–to–date applications of MEMS and NEMS as well.

Prerequisite:

0408318 – Instrumentation and Measurement

Pre/Co-requisite:

None

408444

Autotronics

3–0–3

This course will introduce the fundamental basic of engine types and components, automobile sensors, ignition systems, and fuel injection systems. It also covers the safety and comfort principles. Moreover, it covers the foundations of electrical and hybrid vehicles. Advanced technologies that are equipped in intelligent vehicles are discussed and illustrated including robot vision, object detection, collision warning and avoidance, and fault detection and diagnosis.

Prerequisite:

0408318 – Instrumentation and Measurement

Pre/Co-requisite:

None

408445

Smart Materials

3–0–3

Smart materials are a novel class of materials characterized by new and unique properties that can be altered in response to environmental stimuli. They can be used in a wide range of applications since they can exceed the current abilities of traditional materials especially in environments where conditions are constantly changing. This course is designed to provide an integrated and complete knowledge to smart materials and structures, which makes a strong foundation for further studies and research on these materials. Topics include: structure, processing, properties of smart materials; Dependence of properties on structure; Processing and design; Mechanical, thermal, electrical, magnetic and optical smart materials systems; such as piezoelectrics, ferroelectrics, electrostrictive materials, shape memory materials, magnetostrictive materials; chemical and optical activated materials; Design, and optimization of smart materials systems using CAD and FEA software packages.

Prerequisite:

0408351 – Classic and Modern Manufacturing Processes

Pre/Co-requisite:

None

408446

Introduction to Estimation and Kalman Filtering

3–0–3

This course will introduce the students to the fundamental basic of estimation theory. The course covers the model–based systems, Controllability and observability, probability theory including random variables and multiple random variables, and the least square estimation. Parameter and state estimation using weighted and recursive least square estimation and Wiener filter. The course then focuses on the Kalman filtering and its application to discrete and continuous systems. Alternative Kalman Filter formulations and their applications to tracking, navigating, and fault detection are discussed.

Prerequisite:

0402349 – Analog and Digital Signal Processing

Pre/Co-requisite:

None

408449

Special Topics in MRE

3–0–3

This course covers emerging and advanced topics in the field of mechatronics and robotics engineering. It may also cover advance technologies in the field of Mechanical, Electrical, and/or Computer Engineering, especially those involve with cut edge technology, industrial manufacturing, artificial intelligent, unmanned systems, ... The course shall carry a project that is developed by a team of students. The scientific contents will vary depending on the topic.

Prerequisite:

Senior Standing

Pre/Co-requisite:

None

408447

Intelligent Robotics

3–0–3

This course introduces the student to advanced mobile robots and humanoid robots. It covers the applications of unmanned air, ground, and underwater vehicles and their principles. The fundamentals of Autonomous Mobile Robotics, both perception and planning for autonomous operation, are introduced as well. The second part of the course covers the theoretical foundations of kinematic, kineto–static and dynamic. Several applications are covered from legged mechanism to multi–figure hand systems. MATLAB (toolboxes) and LabVIEW are used to illustrate the mechanism and theoretical concepts provided in this course.

Prerequisite:

0408455 – Robotics and Automation 1

1502344 – Microcontroller Systems

Pre/Co-requisite:

None

1502416

Real–Time Systems Design

3–0–3

This course studies 16/32 bit architectures and its features for real–time control. It explains Instruction pre–fetch, instruction set extension, exception processing, bus arbitration and multiprocessor control. It introduces real–time scheduling and real–time operating systems. It explores application of computers to real–time on–line control of systems.

Prerequisite:

1502244 – Digital Systems

Pre/Co-requisite:

None

1502446

Computational Vision

3–0–3

This course aims to give a comprehensive introduction to computational vision including both theoretical and practical components. Topics such as image and video processing, object detection and recognition, motion detection and extracting from video and its analysis will be covered to allow students to learn and appreciate the basic concepts of computational vision with applications to robotics and autonomous systems.

By taking this module, students will learn the theory and practice of computational vision to solve real–life vision problems. Various applications will be covered including robotics, automation, autonomous systems and navigation. In particular, students will learn tools and algorithms to computationally implement and evaluate a practical computational vision system to demonstrate the key principles taught.

Prerequisite:

1502410 – Artificial Intelligence for Engineers

Pre/Co-requisite:

None