module specification

CT6003 - DSP Applications and Control Systems (2017/18)

Module specification Module approved to run in 2017/18
Module title DSP Applications and Control Systems
Module level Honours (06)
Credit rating for module 30
School School of Computing and Digital Media
Total study hours 300
 
81 hours Scheduled learning & teaching activities
219 hours Guided independent study
Assessment components
Type Weighting Qualifying mark Description
Coursework 25%   Individual Report 1
Coursework 25%   Individual Report 2
Unseen Examination 50%   Unseen Exam, 3-Hours
Running in 2017/18
Period Campus Day Time Module Leader
Year North Tuesday Morning

Module summary

This module provides students with a comprehensive knowledge of a range of digital signal processing techniques including z-transformation, Discrete Fourier Transform, Power Spectral Density and their applications in a variety of scientific fields such as Sonar and Radar, Telecommunications, Medical, Geology and Astronomy.  It also provides fundamentals of control systems engineering concepts and develops knowledge and understanding of the various feedback control systems leading to the design of such systems mainly in continuous time but also touches upon discrete-time systems.

Module aims

For Signal Processing this module aims to:
• Provide a through understanding of the fundamental concepts of discrete-time signals and systems;
• Provide a non-mathematical approach to the applications of Digital Signal Processing;
• Provide an understanding and appropriate interpretation of the results of some of the complex DSP algorithms;
• Illustrate how complex algorithms may be implemented using a software approach or special DSP processors;
• Illustrate, using a system approach, a range of application areas where DSP has made most impact and an awareness of ethical issues related to each.

For Fundamentals of Control Systems the module aims to:
• Provide the necessary mathematical tools for analysing various control systems
• Provide the necessary mathematical tools for designing control systems, given a set of specifications
• Demonstrate the way in which these mathematical tools are applied in real applications for stabilising operation of unstable plants

Syllabus

Discrete time signals: Sampling continuous time signals, Sampling theorem, Nyquist rate, some standard discrete-time signals (Sequences).  Discrete-time Systems: Systems defined by Difference equations, Moving Average (MA) systems, Auto-regressive (AR) systems, Auto-regressive- Moving-Average (ARMA) Systems.  Finite Impulse Response (FIR) Systems, Infinite Impulse Response (IIR) systems.  Evaluation of the response of a discrete-time linear time-invariant system by convolution.  Graphical evaluation of convolution.  Frequency response of discrete-time LTI systems. Steady-state sinusoidal response.  Z-transform: definition, some standard z-transform pairs, properties of z-transforms.  Z-transform of the general form of a difference equation, the transfer function of a discrete-time LTI system, Unit impulse and Unit step responses of Discrete-time LTI systems, Poles and Zeros, the z-plane, stability of discrete-time causal LTI systems.
Classification: Deterministic data, random data, real examples. Basic description properties (and the information they provide) of random data including, mean, variances, probability distribution function, autocorrelation, joint properties of random data, cross-correlation function.
Discrete Fourier Transform: Fast Fourier Transform, Examples and applications. Frequency resolution.
General Applications: Poles / Zeros Diagrams, geometric evaluation of filters magnitude and phase responses.
Power Spectral Density function (PSD): Cross-Spectral Density function, Non-Parametric PSD estimation, windowing. Parametric PSD estimation, Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA). Coherency. Applications of PSD in system identification.
Controllers, Control elements, Plant systems, Measurement (or sensor) elements. 
Open-loop, Forward control, Feedback control, Safety criteria.  Examples of control systems.
Principles of feedback control:
Types of feedback, Proportional feedback, Integral feedback, Derivative feedback, PID feedback. 
Stability criteria, Rooth-Horwitz Stability criteria, modelling of control systems,
Root-locus design, Guidelines for sketching a root locus, Selecting root loci, Selecting gain, Dynamic compensation.
 

Learning and teaching

The majority of teaching and learning activities will be based on formal lectures, tutorials and laboratory work. A scientific simulator such as Matlab is used to provide students with a platform to initially understand various topics of the module.  A series of laboratory exercises emphasise concepts covered lectures.  The logbook (formative) and the formal report (summative) are to be submitted as the coursework component of the module assessment.  The module is supported by a comprehensive web site providing students with all the necessary lecture material, laboratory handouts, study guides and self-assessment tests.

Learning outcomes

On successfully completing the work covered in this module, the student should be able to:
LO1.   Understand principles, usefulness and application of DSP systems filters;
LO2.   Provide analysis and design of basic DSP systems and filters;
LO3.   Use DSP systems in real-world applications such as correlation and power spectral analysis;
LO4.   Explain types of controllers commonly used for improving performance of feedback control systems;
LO5.   Analyse behaviour of feedback control systems;
LO6.   Apply commonly used design methods in designing compensator;
LO7.   Acquire awareness of ethical issues particularly important in DSP and control systems engineering.
 

Assessment strategy

The module is assessed by:

Two coursework:
Coursework 1 (25%), (LO1, LO2,  LO3 and LO7):
This coursework is set on the DSP Application part of the module that is covered in the first semester of the academic year.  It is in two parts: Part one is based on fundamental concepts of discrete-time systems analysis.  Students once completed the theoretical section of this part, would then use the industry standard simulation environment (Matlab) and simulate behaviour of the system that they have produced its theoretical expectation.  This would enhance student’s learning of various topics of the lectures.  The second part of coursework 1 is based on a real-world application of DSP which would also have a theoretical and a simulation section.  This would give students appreciation of how these theoretical concepts actually applied in real-world situations.  Students are expected to maintain an up-to-date logbook for the coursework which would help them in writing their summative individual report (due submitted by the end of the first semester as detailed in the assessment table below).

Coursework 2 (25%), (LO4, LO5, LO6 and LO7):
This coursework is set on the Control Systems Design and Analysis which is covered in the second semester of the academic year.  Students are given an appropriate coursework hand-out which contains the theory and practical simulation of a feedback control system.  In completing this coursework students would obtain deeper understanding of concepts of control systems and its effectiveness in modifying undesirable response of a system by means of introducing a controller in the feed-forward path of the feedback control system.  Students are expected to maintain an up-to-date logbook for this coursework which would help them in writing their summative individual report (due submitted by the end of the second semester as detailed in the assessment table below).

In Addition to these course work components, deeper learning of students are assessed by the end-of-module closed-book 3-hours unseen examination (summative) which takes place during the exam weeks at the end of the academic year.   This assessment component carries the further 50% of the total module mark.

Bibliography

Essential/Highly recommended:
1. Ifeachor & Jervis (1993), “Digital Signal Processing - A Practical Approach”, Addison-Wesley, ISBN 020154413X
2. Stranneby D., Walker W., (2004), “Digital Signal Processing and Applications”, 2nd Ed., Elsevier, ISBN 0750663448
3. Ogata (1996), “Modern Control Engineering”, 3rdEd., Prentice-Hall, ISBN 0132613891

Background reading:
4. Smith S. K., (2003), “Digital Signal Processing - A Practical Guide for Engineers and Scientists”,Newnes,  ISBN 075067444X
5. Balmer (1997), “Signals and systems - An Introductio”, 2nd Ed., Prentice-Hall, ISBN 0134956729
6. Porat (1997), “A Course in Digital Signal Processing”, Wiley, ISBN 0471149616
7. Proakis, Rader, Ling & Nikias (1992), “Advanced Digital Signal Processing”, Maxwell Macmillan, ISBN 02946367X.
8. Stergiopoulos S., (Editor), (2009)ADVANCED SIGNAL PROCESSING, “Theory and Implementation for Sonar, Radar, and Non-Invasive Medical Diagnostic Systems”,2nd Ed., CRC Press, ISBN 9781420062380
9. Stubberud & Williams (1990), “Feedback and control systems”, McGraw-Hill, ISBN 0070170479
10. Powell & Emami-Naeini, (1986), “Feedback Control of Dynamic Systems”, Addison Wesley, ISBN 0201115409
11. Golten & Verwer (1991), “Control System Design and Simulation”, McGraw-Hill, ISBN 0077074122
12. Leonard & Levine (1995), “Using MATLAB to Analyse and Design Control Systems”, 2nd Ed.,  Benjamin Cummings ISBN 0805321934