This course is designed to meet the needs of specialist and non-specialist graduates in engineering, computer science and other related disciplines. We hope that it will appeal to you if you wish to embark on a career in the area of control and information systems, as well as to practising engineers in the field wishing to keep up to date with developments in this important hi-tech growth area.
It is a challenging course, covering all the major aspects of automatic control systems, IT and software engineering with modules ranging from classical control system design to optimal, adaptive and intelligent control systems, including an introduction to artificial neural networks, evolutionary computing and software design for informatics and control systems.
Graduates of the course may apply for membership of the Institution of Electrical Engineers, the Institute of Measurement and Control and the British Computer Society.
Career opportunities range from system designers to system integrators, in a wide range of industrial sectors.
The full-time route is of one year's duration.
You will study core modules in digital computer control; linear control engineering; mathematics and computing for control; object-oriented programming in Java; simulation of systems; software development for control; and software engineering and design principles, together with three optional modules. You will also complete an individual project for the MSc.
Please note that modules may not be offered in the same order and that we reserve the right to amend the programme at short notice in the interests of improving the quality of education.
The course consists of mandatory modules and optional modules.
The mandatory modules are:-
* Digital Computer Control Systems
* Linear Control Engineering
* Mathematics and Computing for Control
* Object-Oriented Programming in Java
* Software Engineering and Design Principles
* Systems Lifecycle and Methods Overview
* Fault Detection in Control Systems
* Formal Methods for Software Engineering
* Genetic Algorithms
* Non-linear Control Engineering
* Neural Networks and Fuzzy Logic
* Optimal Filtering and Parameter Estimation
* Real-time and Embedded Systems
* Self-tuning and Adaptive Control
* Software Design
* Software Implementation and Data Structures
* System Identification
The project can be tailored to suit your own interests. A few examples of past projects are:
* Adaptive model-based control of a hot steel rolling mill.
* Development of a fuzzy logic gas engine speed controller.
* Fuzzy logic decision-making in finance and banking.
* Java for embedded microcontroller systems.
* Optimisation of radiotherapy treatment planning.
* Web-based monitoring and control