Electrical Engineering

This course deals with the analysis and design of electronic circuits containing diodes and transistors. Topics that are covered include physical operation and modeling of diodes (pn junction diode, zener diode) and transistors (MOSFET, BJT); DC analysis, large-signal and small-signal analysis of basic electronic circuits containing diodes and transistors; and design of basic electronic circuits, including simulation and laboratory exercises.

This course explores aspects of electrical power in the context of a wider energy system. The first aspect is electronic “switch-mode” circuits for conditioning and converting power such as in the grid interface for solar and wind energy systems. Circuits for various types of conversion between DC voltage levels and to/from AC are analyzed in order to support circuit design to meet a performance specification. The second aspect covers the electromagnetic devices such as transformers, motors, generators, and transmission lines of an AC power systems. The performance and efficiency of each type of electromagnetic device will be analyzed. The link between these devices and how frequency and voltage of a power system are controlled will be illustrated. The course concludes with a discussion of the transition needed in power systems to achieve zero carbon dioxide emissions and the roles of power electronic, electromagnetic, and information technologies have in that transition.

This course examines electrical energy conversion techniques and equipment. It covers magnetic circuits, inductance, sinusoidal excitation, hysteresis and eddy current loss, permanent magnets, electromechanical energy conversion, singly-excited and doubly-excited systems, transformers, single-phase, equivalent circuit parameters, three-phase transformers, autotransformers, DC machines, separate excitation, shunt excitation, series excitation, and compound excitation, efficiency, armature reaction, induction machines, revolving field, equivalent circuit, squirrel cage machines, measurements of the parameters, DC resistance test, no-load test, blocked-rotor test, synchronous machines, field relationships, power-angle relationships, and salient pole machines.

This course gives students a thorough grounding in electromagnetic systems in electrical engineering. It teaches students how electromagnetic systems provide the foundation of understanding and designing systems as diverse as electrical motors to wireless communication. The Maxwell equations are the basics of Electromagnetism. Students use vector calculus to solve these equations and apply them in low frequency and high frequency applications. Low frequency applications forms strong links with analogue and power electronics whilst high frequency application covers communications and sensing.

This course takes students through the idea of transmitting information from one point to another in the presence of noise. The course introduces students to both analogue and digital transmission, show how the two are connected, and explain the differences (e.g. signal-to-noise ratio vs. bit error rate). The course also introduces students to information theory, and the fundamental theoretical limits of compression and channel coding it identifies.

This course offers an introduction to electronic instrumentation, metrological characteristics, and measurement errors. Other topics include: signal conditioning for electronic sensors-- circuits, amplifiers, and modulation techniques; electronic sensors for the measurement of different physical magnitudes, their characteristics and conditioning circuits; applications of a/d conversion, d/a conversion and data acquisition in instrumentation systems.

This course provides an overview of robot mechanisms, dynamics, and intelligent controls. Topics include planar and spatial kinematics, and motion planning; mechanism design for manipulators and mobile robots; multi-body dynamics; control design, actuators, and sensors; sensing and perception to enable intelligent behavior; and computer vision. Weekly laboratories provide experience with servo drives, real-time control, task modelling and embedded software. Students will build working robotic systems in a group-based term project.

This course deals with signals, systems, and transforms, from their theoretical mathematical foundations to practical implementation in EE applications. This course covers the mathematics and practical issues of signals in continuous and discrete time, linear time invariant systems, convolution, and signal transforms. 

This course explores how machine learning addresses the problem of how computers can learn and extract information automatically from data. It further explores the methods used in artificial intelligence, data mining, and adaptive system design. Students learn how machine learning is used in most disciplines where data is available, including, e.g., electrical engineering, computer science, or medicine. The course introduces students to the theory and practice of modern machine learning methods.

This course presents students with a comprehensive introduction to advanced topics in Linear Algebra as needed in the more advanced literature on Signals, Signal Processing, Systems and Control. The emphasis is on fundamental notions related to vector spaces, inner product spaces, normed spaces, matrix algebras, and computations with matrices.