|Location||United Kingdom, (Main Site)|
|Type||Master courses, part-time|
|Nominal duration||2 or 3 years|
|Tuition fee||To be confirmed|
Undergraduate diploma (or higher)
IELTS: 6.5 (with a minimum of 5.5 in each band)
At least 1 reference(s) should be provided.
One academic reference must be sent
A motivation letter must be added to your application.
If you wish to embark on an exciting career in the area of control
systems and engineering or are a practising engineer who wishes to
update their skills then this is the course for you.
This is a challenging course which covers all the major aspects of
automatic control systems engineering.
This course covers all the major aspects of automatic control systems
engineering, with modules ranging from classical control system design
to optimal, adaptive and intelligent control systems, including an
introduction to artificial neural networks and evolutionary computing.
All students study two fundamental modules which serve to underpin the
remainder of the course. These are Linear Control Engineering and
Mathematics and Computing for Control.
The remaining modules on the course are:
- Digital Computer Control Systems
- Fault Detection in Control Systems
- Genetic Algorithms
- Neural Networks and Fuzzy Logic
- Non Linear Control Engineering
- Optimal Filtering and Parameter Estimation
- Self-tuning and Adaptive Control
- System Identification
The masters project can be tailored to suit the interests of each
individual, and have included in the past: Adaptive model based
control of a hot steel rolling mill; Comparison of rule-based and
model based control systems; Identification of diesel engine
characteristics from operating records and Development of a fuzzy
logic gas engine speed controller.
On completion of this course you can expect to pursue a career in the
area of control and systems engineering.
The course also provides the necessary groundwork for a career in
research in academia or another such research organisation, including
our own Control Theory and Applications Centre (CTAC) and Applied
Mathematics Research Group (AMRC).