SHE Level 4
SCQF Credit Points 20.00
ECTS Credit Points 10.00
Module Code MHH624871
Module Leader Paul McKenna
School School of Computing, Engineering and Built Environment
Subject SCEBE - School Office
  • B (January start)

Pre-Requisite Knowledge

Control Engineering 3

Summary of Content

The aim of this module is to provide the student with a foundation in advanced control system design and digital signal processing.


Digital Control Systems, sampled data systems. Introduction to z-transforms and the z-plane. Estimate the stability of sampled data systems using bi-linear transformations. Time and frequency analysis of sampled data systems. Sample rates. State variable analysis. Explain the benefit of using state space models. Describe how to choose appropriate state space models for a range of engineering systems. State the general state space equation for a linear system. Solve state space equations to calculate system response in the time and frequency domain. Describe the operation and implementation of fuzzy logic controllers in a closed loop control system. Implement algorithms used in the previously described control systems using MATLAB / SIMULINK software and DSP hardware. The syllabus consists of a list of topics normally covered within the module. Each topic may not be dealt with in the same detail.

Learning Outcomes

On completion of this module the student should be able to:Distinguish between analogue and digital control systems (sampled data systems) and identify suitable applications for digital control systems.Describe in general terms the hardware components used in digital control systems (zero order hold etc) and state each components associated z-transform.Use tables to convert from time domain into transfer functions in terms of Laplace and z-transforms.Use block diagram reduction techniques to obtain the transfer function of digital control systems in terms of z-transforms.Calculate and sketch the response of a system in the time and frequency domain using inverse z- transform and bi-linear transformation techniques.Explain the benefit of using state space models.Describe how to select the most appropriate state space variables for a system and create state space models for a range of engineering systems.State the general state space equation for a linear system and solve state space equations to calculate the time and frequency response of control systems.Describe the principle of operation of a fuzzy logic controlled system and describe how fuzzy logic control is implemented in real time control applications.Identify industrial applications which would be suited to fuzzy logic control.Compare fuzzy logic control with digital, state variable and classical control techniques.Design and implement algorithms used in the previously described control systems using MATLAB / SIMULINK software and DSP hardware.Use root locus techniques and design of continous control systems.

Teaching / Learning Strategy

Lectures, Laboratory Exercises, Tutorial Questions, Demonstrations and Directed Study.

Indicative Reading

Feedback Control of Dynamic Systems 4e Gene F Franklin, J David Powell, Abbas Emami-Naeini. 0-13-032393-4 Prentice Hall, 1994. Modern Control Systems 10e Dorf, R.C.; Bishop, R.H. Prentice Hall 0-13-127765-0

Transferrable Skills

Further development of skills and problem solving, numerical analysis and control system design methods. Writing a technical report, presenting results - written, orally and visually.

Module Structure

Activity Total Hours
Assessment (FT) 18.00
Practicals (PT) 12.00
Tutorials (FT) 12.00
Independent Learning (FT) 122.00
Independent Learning (PT) 134.00
Lectures (PT) 24.00
Lectures (FT) 24.00
Tutorials (PT) 12.00
Assessment (PT) 18.00
Practicals (FT) 24.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 0.00 18.00 n/a Lab exercise report 2000 words
Exam (Exams Office) 3.00 70.00 35% Final Examination: Unseen written examination-3 Hours
Exam (School) 1.50 12.00 n/a Mid Term Test - Unseen written examination-1½ Hours