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Mechatronics Program

Mechatronics Program


 

 

The Mechatronics Program offers a cutting-edge and multidisciplinary curriculum that integrates mechanical and electrical engineering. The program includes fundamental courses on Dynamics, Vibrations, Mechatronics and Control Systems, as well as specialized courses on Artificial Intelligence, Haptics, Robotics, and System Identification. The students have the opportunity to engage in engineering research in these rapidly-growing fields under the supervision of faculty members.  

 

Key facts

 

Program Title:

Mechanical Engineering – Energy Conversion

Credential:

Master of Science (M.Sc.) or Doctor of Philosophy (Ph.D.) degrees

Awarding Institute:

University of Tehran

Language:

English

Duration:

two years

Format:

full time, on campus

Starting date:

September 23, 2021

 
Course structure

 

SEMESTER 1: FALL 2021

Credits

Advanced Dynamics

3

Advanced Vibrations

3

Advanced Mechatronics

3

SEMESTER 2: WINTER 2022

Credits

Measurement Systems

3

Digital Control Systems

3

Modern Control Systems

3

SEMESTER 3: FALL 2022

Credits

Artificial Intelligence 

3

Haptic Systems

3

Robotics

3

System Identification

3

Seminar

2

SEMESTER 4: WINTER 2023

Credits

Dissertation

6

 
 
Course descriptions

 

Advanced Dynamics

The objective of this course is to provide students with theoretical and numerical tools for the analysis of dynamical systems. Advanced Dynamics covers fundamental concepts on the three-dimensional kinematics and kinetics of multi-body systems, Euler's equations, holonomic and non-holonomic constraints, Lagrange's equations of motion, Hamilton's principle and analytical dynamics.

Advanced Vibrations

Advanced Vibrations consists of two distinct parts: Vibrations of multi-degrees-of freedom systems and vibrations of continuous systems. In this course, a large variety of topics in vibrations including modal analysis, transverse vibrations of strings, torsional vibrations of shafts, longitudinal vibrations of rods, and flexural vibrations of beams, plates and shells are studies through various analytical and numerical methods.

Advanced Mechatronics

Mechatronics is the science of unifying the principles of mechanics, electronics, controls, and computing to generate a simpler, more economical and reliable system. Traditional product development starts with mechanical design followed by electrical and control system design. This sequential approach to a design problem could be inefficient and suboptimal. Mechatronic design seeks to work in parallel by exploiting interdisciplinary synergies, and to make intelligent design decisions when synergies are not available.

Measurement Systems

Measurement is what human beings have been doing for centuries to prove theories, validate designs, and more recently to build intelligent systems. We are living in Internet-of-Things (IoT) era where devices can sense their environment through various types of sensors and then communicate with each other via internet. On the other hand, with aging infrastructures, monitoring the performance of engineering systems is of crucial importance to assure reliable and safe operation. This is done by integrating sensors into machinery, civil structures, etc. and collecting and analyzing data to obtain insight into the health of the systems. In this course, we will review design and modeling of various subsystems of a data acquisition system such as sensors, signal conditioning circuits, amplifiers, A/D, etc. and also the characteristics of discrete- time signals.

Digital Control Systems

Digital controllers have sidelined analog controllers in past couple of decades due to ever decreasing cost of microprocessors and flexibility they bring about. They are used in all various parts of our lives from domestic appliances and air conditioning systems to autonomous cars and robots. Analysis and design of discrete-time control systems using z-transform, root locus, frequency-domain techniques, and state space method are studied and their online implementation using computers will be discussed.

Modern Control

Modern control deals with the analysis and design of control systems in time domain using state-space approach. The analysis in this course includes stability, controllability, observability, realization and minimality of the state-space model, while the design methods are divided into pole placement for state feedback and observer design, and optimal methods such as linear quadratic regulator. Students will also learn how to apply the theory to engineering problems with MATLAB.

Artificial Intelligence

Driven by the combination of increased access to data, computational power, and improved sensors and algorithms, artificial intelligence technologies are entering the mainstream of engineering practice and innovation. The main objective of the course is to enable students:  a) to identify problems where artificial intelligence techniques are applicable/justifiable; b) to apply basic AI techniques and evaluate their performance in comparison with classical methods, and  c) to participate in the design of systems that act intelligently and learn from their environments.

Haptic Systems

Design and control of haptic systems, which provide touch feedback to human users interacting with virtual environments and tele-operated robots are studied in this course. Device modeling (kinematics and dynamics), synthesis and analysis of control systems, design and implementation of mechatronic devices, and human-machine interaction are among the topics covered.

Robotics

Robots have dominated the auto industry in past few decades but they are also finding applications in medical surgeries, space exploration, home care, etc. This course provides an overview of robot mechanisms, dynamics, and controls

System Identification

Model-based approach to design of advanced control systems and also development of model-based monitoring systems are common. However, such parameters of such models are not always known. System Identification provides us with tools and algorithms to estimate the parameters of such models taking into account the system uncertainties and noisy sensor measurements.