MCTR - Mechatronics & Robotics Engg

Circuit element definitions. Circuit laws: Ohm's, KVL, KCL. Resistive voltage and current dividers. Basic loop and nodal analysis. Circuit theorems: linearity, Thevenin. Dependent sources. Time domain behavior of inductance and capacitance, energy storage. Sinusoidal signals, complex numbers, phasor and impedance concepts. Diodes: ideal and simple and models. Treatment of RLC circuits in the time domain, frequency domain and s-plane. Prerequisites: MATH 101 and MATH 102.

Number systems, logic gates, Boolean algebra. Karnaugh maps. Combinational networks. State machines. Field programmable gate array (FPGA) implementation. Computer architecture. Assembly language. Addressing modes, subroutines, memory, input-output interfacing, and interrupts.

Introduction to linear systems and signal classification. Convolution. Fourier series expansion and Fourier transform (FT). Sampling and reconstruction. Discrete Fourier transform (DFT) and properties. Spectra analysis. Models of continuous-time systems and discrete-time systems for linear control system Z-transform and inverse Z-transform. Analysis of linear time invariant (LTI) systems. Design of linear time-invariant control systems. Corequisites: MCTR 202 and MATH 201.

Design morphology, analysis and design of components, electro-mechanical system design and risk management concepts, design project aimed at assistive devices or technologies addressing user needs. Corequisite: MCTR 265.

Computer-aided engineering, solid modelling, drafting and design. Introduction to multiphysics simulation. Design project aligned with MCTR 260.

Introduction to object-oriented programming for mechatronic applications. Introduction to data structures and classes with application to mechatronics. Introduction to algorithms. Concepts illustrated on a physical mechatronic system. Prerequisite: ENCMP 100.

Transistors, transistor amplifiers, and op-amp circuits; frequency response and filters; analog signal detection, conditioning, analysis, and conversion; transducers and electronic sensors for measuring common physical properties/phenomena. Understanding properties of signals in time and frequency domain; digitization of analog data; statistics, analysis, and uncertainty of measurement data. Prerequisites: MCTR 202 and MCTR 240.

Linear feedback control systems for command-following, stability, and dynamic response specifications. Frequency response and design techniques, including lead, lag compensators and PID control. An introduction to structural design limitations. Introduction to state space models. Examples emphasizing control of mechatronics systems, using computer-aided design. Prerequisite: MCTR 240. Credit can only be granted for one of MCTR 320, MEC E 420, ECE 360, CH E 446.

Force and torque generation in electric machines. AC and DC machines, permanent magnet synchronous (PMSM) and brushless DC motors (BLDC). Machine characteristics and dynamic models of electric actuators. Linear actuators; power electronics device characteristics; motor drives: H-bridges, inverters; speed control methods; power converters.

Kinematics and dynamics of rigid bodies moving in three dimensions. Spatial kinematics of rigid bodies, Euler angles, tensor of inertia and the Newton-Euler equations of motion for rigid bodies, multi-body dynamics, inverse dynamics for manipulators. Prerequisite: MEC E 250.

Systems engineering definition, relevance, and benefits. The nature of technological systems and the concept of a system life cycle, from need to retirement. Requirements setting, including standards. Modelling system performance, with emphasis on mechatronic systems. System safety, risk, and reliability analysis. Ethical and sustainability considerations in systems design. Design for manufacturability and control. Design de-risking and testing for requirements compliance. Configuration management. Systems thinking and Indigenous perspectives.

Coordinates systems, robot kinematics (forward and inverse), differential kinematics, robot dynamics, path and trajectory planning, position control, force control, impedance control, teleoperation systems.

A project-based course dealing with the design and implementation of a robotic system to accomplish a set of requirements. Integration of sensor technologies, sensor data processing, motion control based on feedback and real-time programming. Design procedures, ethics, safety and risk management, theory of engineering design, role of engineering analysis in design, application of computer-aided design software; component and material selection, codes, and standards; design optimization; system integration and verification through testing; teamwork, and a design project. Corequisite: MCTR 365.

Mechatronic and robotic system design using CAD tools. Concepts of function structure models, material selection, and introduction of load and stress analysis. Integration of sensors and actuators. Simulation of mechanisms, dynamics, kinematics, and heat transfer using commercial software. Emphasis is on numerical model design including testing and verification methods, and the critical interpretation of the computed results. Design project aligned with MCTR 360.

Fundamentals of machine learning methods. Supervised, unsupervised, and reinforcement learning concepts, and fundamentals of fuzzy logic. Review of probability and optimization. Linear regression. Linear classification and logistic regression. Components of modern machine learning approaches, including feature engineering, neural network models, training and evaluation methodology, and deep learning libraries. Object detection and object/human pose regression for robotic applications. Bias in machine learning algorithms. Corequisite: MCTR 399.

Advanced topics in object-oriented programming for mechatronic applications. Advanced data structures, and algorithm analysis and design. Concepts illustrated using a physical mechatronic system and practical mechatronic applications. Introduction to modern robotic and mechatronic operating systems. Prerequisite: MCTR 294.

Analytical and numerical methods with mechatronics applications. Complex numbers, partial differential equations, analytic functions, elementary functions, mappings, integrals, series, residues and poles, integral formulas. Statistical tests. Numerical integration and differentiation, solution methods of boundary value problems. Use of programming languages to implement numerical methods. Critical-thinking applied to problems related to mechatronics systems. Formulation, methodologies, and techniques for numerical solutions of engineering issues, particularly those arising within the field of mechatronics.

System states and state space models. Linearization of nonlinear state-space models. Solving linear time-invariant state-space equations. Controllability and observability, and their algebraic tests. Minimal state-space realizations. State feedback and eigenvalue/pole assignment. Step tracking control design. State estimation and observer design. Observer-based control. Introduction to linear quadratic optimal control. Prerequisite: MCTR 320.

Review of probability, random variables, and stochastic processes. Recursive state estimation: Bayes filter, linear Kalman filter and its extension to nonlinear systems. Practical applications of filtering techniques to mechatronics systems. Prerequisite: MCTR 420.

PART 1: Feasibility study and detailed design of a project which requires students to exercise creative ability, to make assumptions and decisions based on synthesis of technical knowledge, and devise new designs. Advanced design safety review.

PART 2: Feasibility study and detailed design of a project which requires students to exercise creative ability, to make assumptions and decisions based on synthesis of technical knowledge, and devise new designs. Advanced design safety review. Prerequisite: MCTR 460.

Introduction to mobile robots. Means of locomotion and kinematic and dynamic models. Linear and nonlinear motion control theory and filtering applied mobile robots. Map-based and reactive motion planning. Localization and mapping. Visual servoing. Prerequisite: MCTR 394. Corequisite: MCTR 421.