The student gains skills in writing scientific documents such as draft proposal, conference paper, journal article, thesis, and technical report. The student should learn, develop, and practice writing, communication, and presentation skills. This course introduces the components, traits and professional ethics of scientific writing to the student.

The student gains the knowledge required to perform a complete CFD analysis. In particular, the student has to identify and choose approximations and models, choose boundary conditions, design and dimension the computational grid, identify and quantify sources of error, and take into account quality and reliability of the computational results.

Topics included like fundamentals of robots: Forward and inverse kinematics, velocity kinematics, and robot ethics. Foundations and principles of robotic dynamics. Topics include system modeling including dynamical modeling of serial arm robots using Newton and Lagrange’s techniques, dynamical modeling of mobile robots, introduction to dynamics based robot control, as well as advanced techniques for serial arm forward kinematics, trajectory planning, singularity and manipulability, and vision-based control. Foundations and principles of parallel manipulators and legged robots and gait and stability/balance analysis of legged robots.

This course is to introduce computer-aided design (CAD) and computer-aided manufacturing (CAM) theories and applications. The course subjects include CAD/CAM systems, geometric modelling data exchange and integration, mechanical assembly, mechanical tolerancing, process planning and tool path generation, integration of CAD/CAM with the production machine, and computer control of machines and processes in manufacturing systems. The course will focus on solid modelling for design and manufacturing applications and the use of commercial CAD/CAM software for automating the production cycle. Applications include NC machining, design of (optimum) cutting tools, and modelling and design of fixtures for dies and molds.

This course provides an introduction to the fundamental concepts and mathematics of digital control systems. The covered topics are discrete models of continuous systems feedback and digital controllers, A/D and D/A conversions, Z-transforms, time and frequency domain representations, stability, digital control design including PID, lead-lag, deadbeat, and model matching controllers.

This course provides an introduction to artificial intelligence (AI). It addresses fundamental conditions, problems, and challenges for AI. It also includes cases and applications of AI, understand AI concepts and terms such as machine learning, deep learning, search, planning, knowledge-based reasoning, probabilistic inference, fuzzy logic, and artificial neural networks.

The course introduces the definition of optimization. The topics include calculus of extrema and parameter optimization by the method of Lagrange multipliers, performance measures, and dynamic programming continuous and discrete time. The student will learn Pontragin’s minimum principle, Hamilton Jacobi-Bellman equation, linear quadratic optimization, and numerical methods for optimal control problem using direct method and indirect method approaches.

"This course provides the theoretical and practical concepts of computer vision concepts including: image formation, color, edge detection, image segmentation, texture, representation and analysis of two-dimensional geometric structures, motion estimation, object recognition, feature detection and structured prediction using deep neural networks, image classification, and object detection.

Thermal effects in an electrical drive , reference standards, advanced electrical drives with dc motor and ac motors, architectures of programmable control systems, microcontrollers for industrial automation, Mathematical model of induction motor for dynamic conditions, vectorial control of induction motor (stator and rotor field orientation, direct and indirect field oriented control, rotor flux estimators and observers and direct torque control), NPC multilevel inverter , single-phase asynchronous motor , universal motor.

Flexible robotics studies the elasticity and the intelligence of integrating devices to comply in their mechanics. Design of soft systems, elastic actuation, modeling and control. New fabrication methodologies of flexible robots.

The student should apply continuum mechanical conservation laws for mass, momentum, and energy. The course covers laminar viscous flow, laminar boundary layers, vorticity dynamics, two-dimensional flow, in addition to an introduction to turbulent flow.

This course introduces students to recently-developed and advanced techniques for solving complex control problems. The course presents theory and methodology for analysis and modelling of systems and signals, and methods for design and synthesis of feedback controllers with relevant case studies. The emphasis of this course will be state space representation of dynamical systems.

In this course, the student is introduced to kinetics of rigid body to derive the relationship between applied loads and resulting motion using newton’s second law, energy method, impulse and momentum, and Lagrange methods. The student has to model the load in mechanism, derive equations of motion, and perform load analysis of the mechanism using numerical method to obtain exact/approximate solution.

This course provides the main concepts and techniques needed to design and implement embedded systems having rea-time response requirements. Topics include: number representations and arithmetic, basic concepts of real time and embedded systems, hardware features, processor input/output implementations and electronic interface, programming languages, real time operating systems, synchronization techniques, serial protocols and implementation, finite state machines, design and implementation for control loop.

Introduce the student to different numerical techniques including algebraic systems, iterative methods, solvers for linear system of equations, optimization, curve fitting, numerical differentiation, and integration.