Courses

Teaching

Fall 2024: MECH3350U: Control Systems

MECE 3390U: Mechatronics

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This course provides students with the tools required to design, model, analyse and control mechatronic systems; i.e. smart systems comprising electronic, mechanical, fluid and thermal components. The techniques for modelling various system components will be studied in a unified approach developing tools for the simulation of the performance of these systems. Analysis will also be made of the various components needed to design and control mechatronic systems including sensing, actuating, and I/O interfacing components.

Students who successfully complete the course should have reliably demonstrated the ability to:

  • Use the basic tools required to design, model, analyze and control mechatronic systems
  • Work with smart systems comprising electronic, mechanical, fluid and thermal components
  • Model a wide variety of system components in a unified way
  • Establish the performance of components in mechatronic systems
  • Analyze various components needed to design and control mechatronic systems
  • Apply the material covered in the program to the design of sensing devices and actuating devices
  • Deal with I/O interfacing components in mechatronic systems

MECE 4320U: Advanced Mechatronics

The focus of this course is to provide the tools required to design, model, analyse and control mechatronic systems. Modelling of various system components into a unified approach and tools for the simulation of the performance of these systems; characteristics of typical mechatronics systems in terms of their impacts on enhancement of performance, speed of operation, and physical size; applications of mechatronics to robotics and automation industry, and other intelligent systems.

Students who successfully complete the course should have reliably demonstrated the ability to:

  • Understand the basic principles involved in the design of mechatronic systems
  • Understand and able to apply machine vision in mechatronics systems
  • Have a thorough knowledge of artificial intelligence and its applications in mechatronics systems
  • Be able to deal with a variety of different types of sensors and actuators
  • Handle analog and digital signals and apply filters in design
  • Able to apply programming concepts to mechatronics devices
  • Able to model multi-domain mechatronics systems
  • Understand and use computer modeling and simulation techniques for mechatronic components

MANE 4280U: Robotics and Automation

Industrial robots; robot kinematics, differential kinematics; statics, dynamics and control of robot arms; non-contact and contact sensors; actuators; real-time joint control; task planning and programming of industrial robots; applications of robots.

Students who successfully complete the course should have reliably demonstrated the ability to:

  • Classify industrial robots and know the uses of industrial robots
  • Analyze the kinematics associated with complex robot motion
  • Establish the dynamics of robot arms and how to control the arms
  • Analyze actuators and real-time joint control systems
  • Establish the methodology for the task planning and programming of industrial robots
  • Work with a wide variety of applications of industrial robots
  • Understand industrial robot safety standards

MECE 3350U: Control Systems

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Analysis and synthesis of linear feedback systems by classical and state space techniques. Nonlinear and optimal control systems. Modelling of dynamic systems; analysis of stability, transient and steady state characteristics of dynamic systems; characteristics of feedback systems; design of PID control laws using frequency response methods and the root locus technique. Introduction to nonlinear and optimal control systems.

Students who successfully complete the course should have reliably demonstrated the ability to:

  • carry out analysis and synthesis of linear feedback systems using classical and state space techniques
  • model control systems in a wide variety of engineering scenarios
  • perform stability and steady–state analyses of dynamic systems
  • understand the characteristics of feedback control systems
  • work with the PID controller laws and be able to design systems using frequency response methods and the root locus technique
  • apply the theory established in the course to some common systems that incorporate active control systems
  • use software and computer tools for the design and simulation of control systems

ENGR 5260G: Advanced Robotics and Automation

This course builds upon the knowledge students have gained in a first robotics course to cover more advanced kinematics topics and their application to more complex robotic systems such as redundant manipulators, parallel mechanisms and mobile robots. Topics will include, but not be limited to: robotic manipulators, mobile robots, modeling and controls, vision in robotics and visual servoing.

ENGR 5263G: Advanced Control

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This course builds upon the knowledge students have gained in a first control course to cover more materials in advanced control systems. Topics covered will include: a. State variables and state space models: Relations between state space models and the transfer-function models (controllable and observable canonical forms, and diagonal form), Jordan form, solutions of linear state equations, transition matrix. b. Controllability and observability: Definition and criteria, state feedback and output feedback, pole assignment via state feedback, design of servo-controlled systems. c. State estimation and observer: Observer state-variable feedback control. d. Multi-input multi-output (MIMO) systems: Pole assignment via state feedback. Introduction to Linear quadratic regulator (LQR), intelligent control and model predictive control.

Other Courses

Mechatronic Modeling and Design with Applications in Robotics

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This course will introduce a unified multi-domain modeling tool, named Linear Graph and its applications. It provides students with the tools required to design, model, analyze and control mechatronic systems; i.e. smart systems comprising electronic, mechanical, fluid and thermal components. The techniques for modelling various system components will be studied in a unified approach developing tools for the simulation of the performance of these systems. A comprehensive example of the modeling and design of a mobile robotic system will be included and discussed.