Mechatronic and Robotic Engineering BEng

This module introduces the concepts and analytical tools for predicting the behaviour of combinations of passive circuit elements, resistance, capacitance and inductance driven by ideal voltage and/or current sources which may be ac or dc sources. The ideas involved are important not only from the point of view of modelling real electronic circuits but also because many complicated processes in biology, medicine and mechanical engineering are themselves modelled by electric circuits. The passive ideas are extended to active electronic components; diodes, transistors and operational amplifiers and the circuits in which these devices are used. Transformers, magnetics and dc motors are also covered.

Engineering applications are typically complex, so students also need to acquire proficiency in analytical problem solving and the ability to apply a systems engineering approach, as a systematic methodology to design and implementation. A group project will develop an understanding of the type of problem solving and systems engineering needed for the design and build of a computer-controlled system. Students will improve skills in communication, team working and reflective practices as a result of the group project. Engineering applications in manufacturing, aerospace, robotics, energy, finance, healthcare and a host of other areas are predominately computer based or computer controlled. In order to be able to create computer based and computer controlled applications, students need to acquire proficiency in relevant software and programming languages. In this module, labs and several individual assignments will build proficiency in creating C programs as solutions to engineering problems.

This module will introduce principles of modelling of simple continuous dynamical systems. This module also introduces analysis of linear models. It includes a detailed analysis of the dynamical behaviour of 1st and 2nd order systems linking behaviour to physical parameters, e.g. Rise time, settling time, overshoot, steady-state. Damping and damping ratio and resonance. Frequency response is also discussed. We will introduce control and feedback as a topic by providing examples of open-loop and closedloop control, and undertake detailed analysis of linear models with a focus on 1st and 2nd order systems. Students are introduced to simple practical feedback mechanisms, including PID controllers and performance criteria such as offset, stability, poles and zeros. You will learn about the principles of how to use Laplace Transforms to solve linear differential equations, and for system representation, using transfer functions and block diagram algebra. You will also develop an appreciation of frequency-domain implications of system analysis through the use of Fourier series. MATLAB is used to reinforce the simulation and analysis of all module contents and coursework assignments.

This module will introduce students to the modelling and analysis of dynamic systems. Students will learn about the different types of physical systems based on real-world case-studies. This 20-credit year-long module is to be delivered over two semesters. In the autumn semester mechanical and electrical-mechanical systems will be introduced. In the second semester the mechanical theme will continue with rotational systems, and then introduce thermodynamic systems as well as flow systems. Students will gain an appreciation of the physics laws governing a variety of physical systems, the impact and interaction of various system components, as well as systematic methods for modelling and analysing such systems. 

This module contains the core mathematical competencies required by students for a systems engineering programme. This covers basic algebra and functions, elementary calculus (differentiation and integration), solution of low order differential equations, Taylor series and iterative methods, matrix algebra and simultaneous equations, vectors and complex numbers. The content is delivered within a systems engineering context. Student learning is encouraged by regular formative assessment and supportive resources. 

This module is intended to equip students with the core knowledge of 'how hardware works' in digital systems and introduce the concept of embedded systems using examples/case studies. The module covers introduction to embedded systems, number systems, boolean algebra, logic gates, logic expressions, combinational logic, A/D and D/A converters, computer systems and architectures. The content is delivered as a combination of lectures, tutorials and laboratory sessions that provide students with a fundamental understanding of embedded systems and their applications.

This module is intended to bring together core content from various Y1 modules in a substantial group design project. The group project involves controlling a mobile robot to navigate to a destination safely and smoothly. This robot is provided as a take-home kit for students to work on this project in their own time. This module also covers important skills needed in the workplace, such as project management and teamwork, as well as other crucial employability skills.

The Faculty-wide Global Engineering Challenge Week is a compulsory part of the first-year programme. The project has been designed to develop student academic, transferable and employability skills as well as widen their horizons as global citizens. Working in multi-disciplinary groups of 5-6, for a full week, all students in the Faculty choose from a number of projects arranged under a range of themes including Water, Waste Management, Energy and Digital with scenarios set in an overseas location facing economic challenge. Some projects are based on the Engineers Without Borders Engineering for people design challenge*.

*The EWB challenge provides students with the opportunity to learn about design, teamwork and communication through real, inspiring, sustainable and cross-cultural development projects identified by EWB with its community-based partner organisations.

This module gives a solid theoretical foundation for understanding feedback control system analysis, design and application and is suitable for general engineering students. This is supported by hardware laboratories, PC laboratory activities and coursework. Content covers standard analysis tools such as root-loci, Bode diagrams, Nyquist diagrams and z-transforms. The latter part of the course focuses on the design of common feedback strategies using these analysis tools and students will undertake indicative designs and reinforce learning through application to laboratory and hardware systems. 

This unit covers methods to represent, analyse and design mechanical, electrical and computational systems and their integration into mechatronics systems. This module will enable students to design, analyse, develop and integrate mechatronic systems. The unit includes lectures on the principles of mechatronic systems, 2D/3D CAD design, sensors and instrumentation, actuation, digital data acquisition, signal pre-processing, hardware interfaces, microcontroller programming and peripherals; practicals on analysing mechatronic components; and project work on designing, developing and testing a mechatronic system.

Modern communication systems provide the backbone of the technological development that is driving the information age. The increase of data analytics, machine learning, and networked solutions pushes the trend towards an increasing use of digital communication systems as means of enabling reliable and efficient information exchange. The aim of the unit is to provide the fundamentals of signals, systems and communication systems. The mathematical principles of signal theory and systems theory will be applied within a communication theory context. The unit will provide the students with the tools to analyse and solve complex open-ended communication problems and to evaluate the technological constraints of the proposed solutions.

Engineering applications in manufacturing, aerospace, robotics, energy, finance, healthcare and a host of other areas are predominantly computer based or computer controlled. In order to be able to create computer based and computer controlled applications, students need to acquire understanding of and proficiency in working across the systems engineering lifecycle. This module builds on the first year undergraduate learning objectives relevant to systems Engineering, to develop further students' skills in the design and development of computer based and software dominated systems. There will be an emphasis on the systems engineering lifecycle (requirements capture, architecture definition, sub-system design and testing, integration, implementation and validation) and project management. Students will use UML/SysML to model systems. C++ will be introduced for algorithmic problem solving. Quality, risk and reliability associated with engineering systems will be explored.

This module provides an introduction to the use of analytical mathematical techniques and numerical methods and algorithms for subsequent higher level module studies and for solving a wide range of engineering problems as well. Students will develop their skills in the theory and application of core mathematics tools required for systems engineering and the application of these in system simulation and data based modelling. A brief summary of topics covered includes: complex variables and Fourier transforms, analysis of matrices and systems represented by matrices, optimisation of functions of many variables, probability, numerical integration techniques and data modelling and analysis. The module is embedded throughout with engineering examples using the mathematical techniques.

The course provides the fundamental concepts and techniques used in Engineering Statics. Two-dimensional statics are covered including force and moment systems, free body diagrams, equilibrium, friction, and the application to structures (such as beams, frames and trusses) that will be encountered in aerospace engineering applications. No prior knowledge of statics is assumed; the treatment concentrates on physical understanding and applications in engineering, rather than using advanced mathematical treatments.

From the apple that fell on Newton's head to launching rockets into space, every object which moves is due to forces and the fundamental laws of physics. In Dynamics you will learn how objects move in 2 and 3 dimensions, and how to calculate trajectories and forces.

The Faculty-wide Engineering - You're Hired Week is a compulsory part of the second year programme, and the week has been designed to develop student academic, transferable and employability skills. Working in multi-disciplinary groups of about six, students will work in interdisciplinary teams on a real world problem over an intensive week-long project. The projects are based on problems provided by industrial partners, and students will come up with ideas to solve them and proposals for a project to develop these ideas further.

The aims of this modules are: to introduce state-space methods for the analysis and design of controllers for multivariable systems; to teach the use of analytical tools and methods for state-space control design; to demonstrate similarities between continuous and sampled data systems; and to extend the analysis to non-linear systems.

Material to be covered includes: Structural properties (modal decomposition, controllability, observability, stability); design (pole assignment, observer design, separation principle, internal model principle, optimal control, LQG, reference tracking, integral control) of continuous systems and equivalents for sampled-data systems.

The aim is to introduce students to digital processing techniques, including sampling and analysis of digital signals, design of digital filers, and the introduction of digital image processing. Discrete signals and systems are studied, with an emphasis on the frequency-domain theory necessary for the analysis of discrete signals and design of digital filters. The concepts associated with digital images and some basic digital image processing operations are also covered. 

This module provides the opportunity for students to undertake a major piece of project work on an individual basis. The project will enhance knowledge and skills in the following areas: critical evaluation of technical literature, project planning and management, deepening knowledge in one or more technical areas and developing the ability to convey technical information both orally and in written form.

The module aims to explore robotic systems, both historically and as an area of rapid contemporary development. Students will be introduced to the different types and applications of robotic systems. An emphasis is placed on modelling and simulation. Sensing and actuation is also covered, with a focus on control of robot manipulators. Students will be exposed to a wide range of practical applications of robotic systems, and encouraged to discuss and reflect on the implications of using robots (e.g. ethical considerations, safety, social and economic impacts).

Machine learning is a component of artificial intelligence that enables a computer to learn how to perform a task from data or simulations rather than being explicitly programmed for every possible scenario. Machine learning is currently being applied in a number of fields including finance, robotics and autonomous systems and bioinformatics and has experienced a huge growth in industry in recent years. This module introduces the key foundational elements of machine learning, including: regression, classification and reinforcement learning. The module is taught by a combination of lectures and labs, where there is an emphasis on practical implementation of different methods.

The module is designed to introduce engineering students to key areas of accounting and legal risk that engineers should be aware of in their working environment. The module will draw directly on practical issues of budgeting, assessing financial risks and making financial decisions in the context of engineering projects and/or product development. At the same time, the module will develop students' understanding of the legal aspects of entering into contracts for the development and delivery of engineering projects and products, and enhance their awareness of environmental regulation, liability for negligence, intellectual property rights and the importance of data protection. Through a series of parallel running lectures in the two disciplines, the module will provide a working knowledge of the two areas and how they impinge on engineering practice.

Modelling dynamical systems from first principles via Newton's, Kirchoff's or other known physical laws is often challenging and costly, requiring substantial expertise. An alternative is offered through 'system identification' that takes observations of inputs and outputs from physical systems and infers or estimates a dynamical model directly.
This module introduces two main ways of thinking about the identification problem, the theoretical framework that underpins them and the algorithms that compute the model estimates. It uses synthetic and real problems to illustrate the process and shows how models can be validated for future use.

This module will introduce students to the theme of intelligent systems with special applications to modelling, control, and pattern recognition. Although this technological area can be perceived as being broad, the focus will mainly be on Fuzzy Systems and on interesting synergies such as those between Fuzzy Systems and Artificial Neural Networks (ANN), including the Neuro-Fuzzy architecture. This module should appeal to all students from engineering as well as from science backgrounds who wish to learn more about Artificial Intelligence and Machine-Learning related paradigms, and mostly, how may the related architectures be applied effectively to solve real-world problems, i.e. non-linear, noisy, and the ones that are characterised by uncertainties. This unit is also timely indeed, since knowledge transfer from human to machine and from machine to human and knowledge extraction from data (Big Data) are seen particularly, as vital components for a successful economy, healthy well-being, and clean environment. Finally, the module strikes the too-often difficult balance between theoretical foundations and examples of applications via weekly interactive lectures, laboratory experiments, video demonstrations, and problem solving.

The module aims to introduce different mission types including communications, earth observation, weather, navigation, astronomy, scientific, interplanetary missions and space stations. Concepts of orbital motion such as Kepler Laws, Elliptic, Parabolic and Hyperbolic orbits are introduced. Hohmann orbit transfer, ground station visibility, launch windows are explained. The module provides an understanding of spacecraft sub-systems and control including attitude control and thermal control, as well as providing knowledge of propulsion systems for example chemical rockets, electric propulsion, nuclear rockets, and solar sails. Various concepts related to space environment are explored including, sun, solar wind, solar cycles, magnetosphere, magnetic storms, and geomagnetic indices. The module explains space weather phenomena and concepts. The module considers ground induced current and its effect on modern technological systems. Methodology that is used to forecast of space weather parameters are discussed.

This course represents an opportunity for students to gain hands-on experience of designing and implementing advanced controllers upon a challenging, real-world control problem. Uniquely, each student will be issued with their own, portable control hardware for the duration of the course. Students will learn how to interface such a system to industry standard software using a data acquisition device, before developing their own simulation models of the hardware. These models will be used to synthesise a feedback controller, and verified in simulation before being implemented upon the hardware. The resultant controller will then be refined in a cycle of rapid control prototyping.

There are a wide range of important healthcare challenges in the 21st Century, such as the aging population, stroke, paralysis and the loss of limbs, which can be treated using biomechatronic devices such as exoskeletons, active prosthetic limbs and brain computer interfaces.
'Biomechatronics' describes the integration of the human body with engineered devices composed of electronic, mechanical and control components (mechatronics) for the purposes of
(i) emulating and replacing natural human function lost through disease or accident and/or
(ii) augmenting natural human function to generate superhuman abilities.
The biomechatronics module will cover the subject of biomechatronics in theory and practical application, and span the main core topics of: neural control, biomedical signals, sensors and actuators.

The purpose of this module is for students to gain knowledge and experience in designing medical and assistive devices and implants, which underlines the role played by a Biomedical Engineer/Bioengineer. Topics include a survey of world health and clinical problems, the need for solutions in the developed, developing and underdeveloped countries; the principles of medical device and implant design; design parameters and specifications; design for an assistive product, engineering analysis; preclinical testing for safety and efficacy, risk/benefit ratio assessment, evaluation of clinical performance and design of clinical trials. Case studies and topical discussions are used to aid further understanding of specific topics.

This module is about understanding the fundamentals and common applications of antennas and radar systems. The basic characteristics of some of the commonly used antennas, and antenna systems, will be examined in the context of practical design and application. The radar part of the module will introduce the basic concepts of radar and examine various types of commercial and military radar system in common use. The application of radar and other methods in airborne navigation and landing systems will be discussed. Throughout the module emphasis will be placed on 'first-order' analysis techniques in order to reduce the use of advanced mathematics.

The aim of this module is to enable students to understand the concepts and practices used by modern manufacturing organisations. The module starts with content on current trends in manufacturing processes (in particular high-speed machining and additive manufacturing). Students are then introduced to ways of designing and evaluating a manufacturing system as well as the relevant theories, concepts and methodologies of controlling and managing a manufacturing shop floor.

The module provides an introduction to some alternative energy technologies with emphasis on solar and wind energy. It aims to provide students with a fundamental appreciation of the potential and usable energy obtainable from the sun and wind; a general knowledge of wind turbine aerodynamics, wind turbine systems, photovoltaics and domestic photovoltaic systems.