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.
WHY CHOOSE THIS COURSE?
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.
WHAT WILL I LEARN?
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.
You should have a first degree (or equivalent) in any engineering or physical science subject with a good mathematical content.Candidates with relevant industrial experience may be allowed entry to the course provided their experience can be taken in lieu of formal qualifications.
Recipient: Coventry University
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