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Control Engineering – (M.Sc.)
Coventry University
Faculty of Engineering and ComputingTherefore, information might be incorrect, incomplete or outdated. We apologise for your inconvenience..
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| Annual Tuition Fee: | ≈ € 5,450 - | ||
| Location: | Coventry / United Kingdom | ||
| Duration: | 12 months | Start Date: | September |
| Educational Form: |
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| Education Variants: |
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| Languages: | English | ||
Location of Coventry University
This course is designed to meet the needs of both specialist and non-specialist graduates in engineering and science. We hope that it will appeal to you if you wish to embark on an exciting career in the area of control and systems engineering, as well as to practising engineers in the field who wish to update their skills and become aware of recent advances in this growth area of hi-tech engineering.
It is a challenging course which 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. Furthermore, modules on the course are registered as part of the continuing Professional Development schemes of the IEE and IMechE.
On completion of the course you should be able to appreciate the importance of control engineering as a fundamental multidisciplinary subject as well as a subject in its own right; design, evaluate and implement control algorithms and techniques for a wide range of processes and plant and form a critical and objective judgment on aspects relating to advantages and limitations of control system strategies.
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 and Applied Mathematics Research Group
Contents
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.
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Requirements
Entry requirements
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.
Applicants whose first language is not English must have a minimum IELTS 6.5 or TOEFL 600 or equivalent.
Additional Requirements
| Minimal degree required: | Bachelor's degree |
| Minimal amount of work experience | Not specified |
Language Proficiency
| IELTS Band: | 6.5 |
| Cambridge English: Advanced (CAE): | Grade C (Score: 60) |
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