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Control Theory & Applications Master in Science by Research

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  • Entry requirements
    The normal entry criteria are a first or second class degree with Honours in an appropriate subject area. Applicants who possess equivalent academic or experiential learning at graduate or diploma level will also be considered. All applicants will normally be interviewed to assess their suitability for the course. An applicant for registration must have a sufficient command of the English language to be able to complete the programme of work satisfactorily and to prepare and defend the thesis in English.
  • Academic Title
    Control Theory & Applications Master in Science by Research
  • Course description
    This degree will provide you with the general research skills required to carry out independent work. The course comprises introductory training in research skills and the study of an appropriate subject area. The greater part of it is devoted to project work. The course improves your chances of promotion if you are already working in the field and gives a sound training for a career in research and design in the area of control theory and its applications.

    You can take the degree full-time over one or two years, or part-time over between 18 and 36 months.

    Course content

    In common with taught MSc courses the total course is valued at 180 credits at Masters level. This being made up of taught modules and a project, with a single module valued at 12 credits and based on a notional 96 hours of student effort, which includes class contact, private study and assessment. The class contact time is normally 30 hours, which for those attending in the evenings is equivalent to one evening a week over a ten week term.

    The minimum period of full-time registration is 12 months, maximum 24 months; for part-time students the periods are 18 months and 36 months, respectively.

    For the MSc by Research in Control Theory and Applications the course structure adopted consists of three components:

    1. A 12 credits core study skills module, Research Methods and Professional Skills. This module consists of five units:

        * Information Search and Retrieval
        * Project Management
        * Research Roles and Principles
        * Legislation: Intellectual Property and Health and Safety
        * Presentation Skills

    with each unit being assessed against learning outcomes, a proportion of which will be met through periodic review of progress on the research project. The module must be passed.

    2. Two more 12 credits modules (or equivalent) selected from the following list, available on either the MSc in Mathematical Modelling and Computer Simulation or the MSc in Control Engineering:

        * Linear Control Systems (24 credits)
        * Fault Detection in Control Systems (12 credits)
        * Neural Nets and Fuzzy Logic (12 credits)
        * Genetic Algorithms (12 credits)
        * Signal Processing (24 credits)
        * Linear Control Engineering (12 credits)
        * Digital Computer Control Systems (12 credits)
        * Non-Linear Control Engineering (12 credits)
        * System Identification (12 credits)
        * Optimal Filtering and Parameter Estimation (12 credits)
        * Self-Tuning and Adaptive Control (12 credits)

    The module(s) will be specified when you register for the course and selected to give coverage for related studies essential to the successful completion of the course. Exceptionally, subject to approval, a programme may consist of three 12 credits modules where the need for an additional module to remedy deficiencies has been identified. Normally a module may be studied by day-time or evening attendance. Assessment is by in-course evaluation of set coursework assignments, together with examinations in most modules at the end of the teaching block. The modules must be passed.

    3. A research project. Normally this will be rated at 144 credits at M-level. The nature of the project is different from an MPhil and PhD project in that it will be primarily of an investigative or scholarly nature, with possibly limited innovating elements. It is expected to be more extensive and show greater depths of originality and insight than the dissertation for a taught Masters degree.

    The project will normally be formulated, including specification of objectives, in consultation between the student and the nominated Director of Studies. Where the project is able to be pursued (wholly or partially) within an industrial organisation then, where appropriate, a representative of that organisation should be involved in the formulation of the project.

    On completion of the project the student will present a written report (thesis) and defend the same at an oral examination (viva voce). The thesis should demonstrate the student's knowledge and understanding of the subject and should satisfy the agreed objectives.

    Supervision

    Students registered on the course will be attached to the Control Theory and Applications Centre, a research centre carrying out collaborative research with a large number of Midland-based companies. Supervision will be provided by staff associated with the Centre; all of whom have an established research record and supervisory experience up to and including PhD level.

    There will be either one or two supervisors for each research project. One will be identified as the Director of Studies, with the specific responsibility to ensure that the student receives proper guidance and support. Where the project is linked to an external organisation (eg work based) use of a second supervisor from that organisation will be encouraged.

    Areas of Research

    The projects currently undertaken within the Control Theory and Applications Centre cover a range of activities including

        * Adaptive control and self-tuning systems
        * Automotive, marine and aerospace systems
        * Bilinear self-tuning control systems
        * Biomedical engineering systems
        * Energy efficiency and environmental systems
        * Fault detection and condition monitoring
        * Industrial process control systems
        * Intelligent rule-based and fuzzy systems
        * Neural networks and genetic algorithms
        * Robust controller and observer design

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