Control, Automation and Artificial Intelligence MSc

Course overview

Is your undergraduate degree in engineering, mathematics or science? An accredited MSc in Control, Automation and Artificial Intelligence can help you to develop skills that would be beneficial in almost every engineering field from automotive, aircraft industry, power and energy, automation, process industry including oil and gas, food and drink, pharmaceutical industry and many others.

• Control engineering is a means of managing and measuring performance of dynamic systems in areas from power plants and nuclear reactors to construction and manufacturing. The principles of control also extend in activities as diverse as managing risk in the financial sector to studying climate change within science.
• This course is designed to provide a unique route for postgraduates to top up their background with more specialised knowledge and skills in the rich field of control systems, automation and AI relevant to various practical engineering industries as well as research in academia.
• This course aims to provide a combination of theoretical and practical modules with sufficient depth, giving graduates sufficiently strong skills and background to take up professional posts in control, automation and AI within industry and/or research, and to develop themselves further depending on the requirements of the profession.
• If you wish to embark on a career as a technical specialist in analytical aspects of control, automation or AI engineering or if you are a practicing engineer looking to stay abreast of important advances and developments, you may want to consider this course.
• Current academics delivering teaching on this course are actively involved in research and consultancy, ensuring your taught materials are based on techniques and technologies currently relevant to industry. Parts of the teaching materials are also offered as CPD training for engineers from industry. (Please note staff may be subject to change).
• You will have the option to apply for a ‘professional work placement’ opportunity², designed to further develop your skills and knowledge with the aim of maximising your employability prospects. See modules for more information.

Why you should study this course

• This professionally accredited course covers areas ranging from classical control system design to optimal, adaptive and intelligent control systems, such as proportional + Integral + Derivative (PID) control, Smith Predictor, Model Predictive Control (MPC), state variable feedback pole placement.
• We aim to develop your skills required to design, analyse and simulate automatic control systems. Teaching is practical in nature with laboratory sessions in specialist software, including MATLAB/Simulink and LabVIEW. Following these simulation studies, you should be able to deploy control systems on specialist hardware.
• We aim for dissertation project work across this course to be based on real-life situations to gain familiarity of methods and techniques from our industrial collaborators, or to support on-going research projects in automotive control systems, cooperative and autonomous vehicles, and preventive maintenance applied to medical devices.
• Where appropriate, research seminars, including staff, research students, and external guest speakers from industry are invited to provide a lecture/presentation to supplement and reinforce the practical relevance of the material. In addition, students are also encouraged to attend externally organised seminars, workshops, training, or internships to gain wider knowledge and experience, as well as build their professional network.

Careers and opportunities

Upon successful completion, you will be able to:

• Demonstrate knowledge and understanding of control engineering and the constituent components of a control system and analyse the behaviour using appropriate mathematical tools.
• Assess the performance of a system via simulation and interpret the results quantitatively, e.g. numerically and/or statistically.
• Evaluate and implement control algorithms and know their practical limitations.
• Demonstrate specialist knowledge in control engineering within the broad themes of the course depending on the chosen pathway.
• Understand and conceptualise a given complex problem and produce an appropriate model to generalise at a higher level of abstraction.
• Critically analyse, evaluate and apply advanced analytical skills.
• Apply knowledge of design via simulation to select appropriate algorithms for achieving a specific task.
• Critically evaluate and demonstrate awareness of a range of hardware and software platforms for control system design and implementation.
• Research information relevant to programme topics from a variety of sources and to critically analysis ideas, arguments and points of view.
• Successful completion of this course should provide you with skills applicable for industries including automotive, aerospace, process/chemical industries, manufacturing, robotics and automation, finance and banking.

There are also opportunities in research and development across a wide variety of these industrial and commercial sectors.