Mechatronic and Robotic Engineering MEng

Core modules:

Digital and Embedded Systems

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.

10 credits

Group Control Project and Professional Skills

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.

10 credits

Introduction to Systems Engineering & Software

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.

20 credits

Systems Engineering Mathematics I

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. 

20 credits

Modelling, Analysis and Control

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.

20 credits

Physical Systems

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. 

20 credits

Introduction to Electric and Electronic Circuits

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.

20 credits

Global Engineering Challenge Week

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.

Core modules:

Control Systems Design and Analysis

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. 

20 credits

Mechatronics

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.

20 credits

Signals, Systems, and Communications

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.

20 credits

Systems Engineering and Object Oriented Programming

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.

20 credits

Systems Engineering Mathematics II

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.

20 credits

Engineering Statics

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.

10 credits

Dynamics I

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.

10 credits

Engineering - You're Hired

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.

Core modules:

State-Space Control Design

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.

10 credits

Digital Signal Processing

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. 

10 credits

Robotics

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).

10 credits

Group Project

This module provides students with the opportunity to work as a group on a substantial project of relevance to systems and control engineering. Students will gain practical experience of all aspects of the systems lifecycle, from problem formulation and requirements capture, through design and build activities, and subsequent verification and validation. Each project will have a synthetic customer and students must deliver within time and budget constraints. Students will have the opportunity to develop their communication skills in written and oral forms, including a practical demonstration of the system they have built. Students will also be encouraged to reflect on the individual and group contributions they are making.

30 credits

Machine Learning

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.

10 credits

Accounting and Law for Engineers

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.

10 credits

Optional modules:

System Identification

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.

10 credits

Intelligent Systems

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.

10 credits

Space Systems Engineering

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.

10 credits

Biomechatronics

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.

10 credits

Design of Medical Devices and Implants

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.

10 credits

Antennas, Radar and Navigation

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.

10 credits

Manufacturing Systems

The aim of this module is to enable students to understand the concepts and practices used by modern manufacturing organisations. The modules 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.

10 credits

Renewable Energy

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.

10 credits

Core modules:

Machine Vision

The module gives knowledge of machine vision methods for a broad range of applications. It introduces you to image and video processing models and methods and provides you with skills on how to embed them in autonomous systems. You will be able to apply the acquired knowledge to both industrial and research areas.

15 credits

Mobile Robotics and Autonomous Systems

Robotics and autonomous systems are having an increasing impact on society and the way we live. From advanced manufacturing and surgical robots to unmanned aerial systems and driverless cars, this exciting area is presenting increasing technological challenges. This module provides you with the advanced knowledge and understanding to apply control and systems engineering concepts to the closely related disciplines of robotics and autonomous systems. The module covers theoretical and technical analysis, and design aspects of mobile and manipulator robots with reference to their applications. The module further covers advanced techniques in autonomous decision making for robots and autonomous vehicles.

15 credits

Advanced Project

This module provides the opportunity for you to undertake an advanced piece of project work on an individual basis. The project will enhance knowledge and skills, to an advanced level, in the following areas: critical evaluation of technical literature; project planning and management; deepening knowledge in one or more technical areas; initiative, creativity and stamina in solving problems; and developing the ability to convey technical information in both orally and in written forms.

45 credits

Optional modules:

Optimal Control

The module teaches how to design optimal controllers. It starts by explaining the main ideas of infinite-dimensional optimization. In particular, it introduces the Calculus of Variations, a field of mathematics used to find maxima/minima of mappings defined on functions e.g. it allows you to find a trajectory corresponding to the minimum energy/fuel waste. This theory is then used to develop tools for designing optimal controllers. Namely, the maximum principle and dynamic programming are introduced. The module is supported by extensive examples and home assignments that will help you to learn how to apply all the covered techniques.

15 credits

Deep Learning

An important field within artificial intelligence is machine learning, which enables systems to learn from data rather than being explicitly programmed to solve a task. Conventional machine learning algorithms tend to rely on a human to carefully engineer and extract features to present to a machine learning algorithm, which can be time-consuming and difficult. A deep learning system, by contrast, takes raw data as input and learns to extract features automatically. This approach has led to significant improvements in processing images, video, speech and audio. Deep learning has also had an impact on the design of intelligent agents, giving rise to the area of deep reinforcement learning, which is where an agent learns in a reward-based framework. An example of deep reinforcement learning is where the Google DeepMind team designed an agent that learned to play Atari computer games to better-than-human-expert level.

15 credits

Rapid Control Prototyping

This module represents an opportunity for you to gain hands-on experience of designing and implementing advanced controllers upon a challenging, real-world control problem. Uniquely, you will be issued with your own, portable control hardware for the duration of the course. You will learn how to interface such a system to industry-standard software using a data acquisition device, before developing your 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.

15 credits

Cybersecurity for control systems

The increase of sensing, computing, and communication technologies on control systems is enabling a host of new applications and services but it also opens the door to cybersecurity threats. Realizing the promise of secure control systems requires the development of analysis tools and design guidelines that integrate security guarantees in the performance characterization of the control system. This module aims to lay the theoretical foundations for secure control system design problems while explicitly teaching students how to account for the operational and practical constraints posed by real control systems.

15 credits

Advanced Control

The aim of this module is to provide you with an introduction to some of the advanced control techniques used in modern control engineering research and industrial applications. The module will cover both theory and practice, involving analysis and design.

Different control techniques and applications may be covered in different years. In all cases, the basic principles and concepts of a particular control technique will be introduced, and comparisons and contrasts will be made with other techniques. Subsequently, the design, analysis and implementation of advanced controllers or control laws will be covered, starting from the requirements of the basic control problem for the application at hand (i.e. stability in the presence of constraints; disturbance and noise rejection). Controller design will be illustrated by industrially-relevant case studies.

15 credits

Advanced Space Systems and Space Weather

The module provides you with an understanding of the concept advanced space systems, within the context of space weather and processes in the geo-space that can have hazardous effects on modern ground based and space based technological systems. It covers knowledge about susceptibility of services such as power supply, communications, transportation and navigation to space weather events, and introduces methodologies for space weather forecast based on systems engineering approaches from first principles. The module also provides knowledge of the requirements for transferring forecasting models into operational tools for space weather forecasting, before covering how space weather forecasting can assist in mitigating adverse effects of space weather.

15 credits

Real-Time Embedded Systems

Many systems, for example; a control system, fault detection system or health monitoring system are required to work in real-time. Such systems can be developed and implemented using a CPU and external devices in an embedded system application/device to perform the desired tasks in the 'real' world. This module covers the hardware associated with building an embedded system and how the desired functionality and thus real-time operation of an embedded system can be realised through software/hardware.

15 credits

Agent-Based Modelling and Multi-Agent Systems

This module introduces multi-agent systems and agent-based modelling. It will motivate the many diverse types of complex adaptive system that can be represented and simulated by these approaches (including engineering applications, artificial intelligence and socio-technical systems). The module introduces a set of key theories, methods and tools in the domain of multi-agent systems and agent-based models. You will gain experience of implementing agent-based simulations in state-of-the-art software, building on your experience in object-oriented programming and agile software development methods.

15 credits

Optimisation: Theory, algorithms and applications

This unit provides detailed presentations on the use of numerical optimisation and search methods for a wide range of engineering problems. Traditional approaches drawn from Operations Research will be enhanced by topics based on recent developments in heuristic methods, such as evolutionary computing, e.g. genetic algorithms and swarm intelligence.

15 credits

Data Modelling and Machine Intelligence

All of our lives are affected by machine intelligence and data models - Google is a very visible example. But if you are a victim of identity theft, if you want a loan to buy a house or if you want to pass through immigration at an airport, a model derived from data using some form of machine learning technique will be involved.
Engineers increasingly look to machine intelligence techniques such as neural networks and other machine learning methods to solve problems that are not amenable to conventional analysis e.g. by application of Newton's and Kirchhoff's laws, and other physical principles. Instead they use measurements of system variables to compute a model of the process that can then be used in design, analysis and forecasting. System identification is a specific example of data modelling.
We will look at the underlying principles of machine learning, the advantages and limitations of the various approaches and effective ways of applying them with the aim of making you a competent practitioner.

15 credits

Human Movement Biomechanics

Biomechanics of human movement is the science concerned with the internal and external forces acting on the human body and the effects produced by these forces. This module will teach the students both the kinematics (the branch of biomechanics of entailing the study of movement from a geometrical point of view) and kinetics (the branch of biomechanics investigating what causes a body to move the way it does) of human movement and leverage on practical laboratory sessions to expose them to the most advanced technologies to measure and model the associated mechanical phenomena of interest.

15 credits

Automotive Powertrain

This module considers the performance, design and emissions of automotive powertrain - from the combustion chamber to the driven wheels. Environmental and societal developmental drivers of the attributes required of modern, globally applicable powertrain will be established. It will enable students to apply specialist knowledge (thermofluids, dynamics, materials) to internal combustion engines and their associated driveline components. Students will perform analysis of powertrain performance and select materials and design features to maximise efficiency before reviewing peers' proposals. The industrial state of the art and future technologies from research will be examined e.g. variable valvetrain, hybridisation and electric drive, modern combustion strategies.

15 credits

Additive Manufacturing - Principles and Applications

This module will provide you with a comprehensive introduction to Additive Manufacturing (3D Printing), providing you with an insight into the technologies themselves, when and how they might be applied, and the broader economic, social and industrial context within which these techniques sit. Our aim is to provide you with an understanding of the underlying principles and considerations relevant to this area, so that you are able to apply this knowledge confidently and effectively during your future career.

15 credits