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ENGR406: Intelligent System Control


Department: Engineering NCF Level: FHEQ/QCF/NQF7//RQF7
Study Level: Part II (yr 4) Credit Points: 15.0
Start Date: 15-01-2018 End Date: 26-01-2018
Available for Online Enrolment?: Y Enrolment Restriction: Only available to students majoring in delivering department
Module Convenor: Professor CJ Taylor

Syllabus Rules and Pre-requisites

Curriculum Design: Outline Syllabus

  • Intelligent control, hierarchical control architectures, reviews of classical and modern control, digital control systems, state-space design, and system identification, with fully worked practical examples from across the engineering discipline.

  • 80% Exam
  • 20% Coursework

Educational Aims: Subject Specific: Knowledge, Understanding and Skills

  • This module introduces students to the design and application of intelligent control systems, with a focus on modern algorithmic, computer-aided design methods. Starting from the well-known proportional-integral algorithm, essential concepts such as digital and optimal control are introduced using straightforward algebra and block diagrams. The module addresses the needs of students across the engineering discipline who would like to advance their knowledge of automatic control and optimisation, with practical worked-examples from robotics, industrial process control and environmental systems, among other areas.

Educational Aims: General: Knowledge, Understanding and Skills

  • This module introduces students to statistical modelling concepts that are rather different to classical engineering model development based on physical equations. These methods have wide ranging application for control, signal processing, and forecasting, with applications beyond engineering into medicine, economics, environment sciences, and so on. The module also aims to develop an appreciation of the constraints under which industrial applications of control operate, and to introduce computational tools for designing control systems.

Learning Outcomes: Subject Specific: Knowledge, Understanding and Skills

  • On successful completion of this module students will:

    • understand various hierarchical architectures of intelligent control;
    • be able to analyse and design discrete-time models and digital control systems;
    • be able to design optimal model-based control systems;
    • identify mathematical models from engineering data;
    • design and evaluate system performance for practical applications.

Learning Outcomes: General: Knowledge, Understanding and Skills

  • On successful completion of this module students will:

    • be able to use statistical tools for the analysis of data;
    • be able to use modern computational aids for the design of control systems;
    • appreciate cutting-edge research developments in these areas;
    • demonstrate an understanding of the control objectives and practical constraints, and be able to suggest design solutions for a range of case study examples.

Contact Information

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