Unit Reference: UNIT TITLE: Control Engineering CREDIT POINTS: 20 LEVEL: 3 Parent Course: BEng (Hons) Electronic Engineering Delivering Faculty: FOT Level (on parent course): 3 Date validated: March 2003

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Unit Reference:


UNIT TITLE: Control Engineering




CREDIT POINTS: 20


LEVEL: 3


Parent Course: BEng (Hons) Electronic Engineering


Delivering Faculty: FOT

Level (on parent course): 3





Date validated: March 2003


TOTAL STUDENT WORKLOAD


Students are required to attend and participate in all the formal timetabled sessions for the
unit. Students are also expected to manage their directed learning and independent study in
support of the unit.


Where normal timetabled sessions do not take
place, additional directed learning may be
provided, and/or students are expected to undertake additional independent learning
.


PREREQUISITES


Signals & Circuits I
-

Level 1

Signals & Circuits II
-

Level 2

Instrumentation and Control systems
-

Level 2

Ma
thematics II
-

Level 2

or equivalent


UNIT DESCRIPTION

This unit is designed to develop a sound understanding of the operation of modern control
systems. The study of continuous control systems in Instrumentation and Control (Level 2) is
extended to consid
er the design of analogue controllers and discrete
-
time systems. It also
considers in detail the major areas of intelligent control. Delivery will place equal emphasis
on traditional approach to system modelling and control. The traditional techniques are
then
extended to cover modern techniques required for the analysis/design of sampled
-
data control
systems. Case studies drawn from engineering journals will be used to illustrate the operating
characteristics and relative merits of various types of intelli
gent control applicable to real
-
world industrial control problems.



LEARNING OUTCOMES


Understanding and knowledge



Relate the operation of the modern control system and the AI
-
based control
methodologies applicable to industrial control.


Cognitive skil
ls


1.

Obtain a mathematical model of a physical system and investigate its behaviour.


2.

Analyse various techniques and methods employed for determining stability of
control systems

3.

Discuss and critically appraise the use of AI techniques for industri
al control.


4.

Synthesise an AI
-
based solution to an industrial control problem.


Practical skills


5.

Implement and evaluate the performance of a continuous/sampled
-
data control
systems and AI
-
based control system using MATLAB.


AREAS OF STUDY


Continuou
s Systems

Mathematical modelling of physical systems. Transfer functions, signal flow graphs and their
applications. Time and frequency domain analysis of continuous control systems. Root
-
Locus
techniques and compensator design. Three term controllers; ana
lysis and design.


Sampled
-
Data Systems

The sampling process. Representation of sampled
-
data control systems. The z
-
transform and
inverse z
-
transform. Time and frequency domain response of sampled
-
data systems. Stability
consideration of a sampled
-
data con
trol system.


Overview of artificial intelligence in engineering.


Tree search. Calculus
-
based search techniques: Newton
-
Raphson and gradient descent.
Stochastic search techniques: simulated annealing and genetic algorithms.


The Artificial Neural Networ
k. Feedforward networks, learning using the delta rule and
back
-
propagation. Feedback networks. Industrial applications of neural networks.


Scheduling by critical path analysis. Use of simulated annealing and genetic algorithms.
Intelligent schedulin
g.


Deterministic reasoning, propositional and predicate logic. Reasoning with uncertainty.
Possibilistic and fuzzy reasoning.


Rule
-
based (expert) systems. Industrial applications of fuzzy systems.



TEACHING AND LEARNING STRATEGY


The core theoretical

concepts of the unit are introduced through a series of lectures. These
concepts are then further developed and applied through small group teaching sessions where
a series of case studies will be presented, drawn from current engineering practice.
Work
shops will provide practical experience in the design and simulation of control systems
to satisfy an engineering specification. MATLAB software will be employed to illustrate
application of the methodologies considered in lectures and workshops. Investiga
tive sections
in the workshop will require the student to utilise an appropriate computer package (ie
MATLAB) to analyse the behaviour of continuous/sampled
-
data control systems appropriate
to real
-
world applications. Computer simulation will be used to in
vestigate important AI
techniques; for example stochastic search using simulated annealing or genetic algorithms
and training multi
-
layer feedforward neural networks. An investigative assignment will
require the student to propose and critically appraise
an AI
-
based solution to an industrial
control problem.



ASSESSMENT


In
-
Unit

assessment(s)


IU1

Weighting:

20%

Assessment Type:

Workshops and Logbook

Special Facilities:

Using MATLAB

Duration:


In
-
Course

Additional Details:


In
-
Unit
assessment(s)


IU2

weig
hting %:

20%


assessment type:


Assignment

duration:


In
-
course

special facilities:

-

additional details:

-



End
-
of
-
Unit
assessment


weighting:


60%

assessment type:

Closed
-
book examination

special facilities:

N/A

duration:


2hr



ASSESSMENT STRATEGY


Th
e assessment instruments for this unit are investigative assignment and workshops and a
two hour examination. The assignment and the workshops will provide the assessment of
Learning Outcome 5, while Learning Outcomes 1, 2, 3 and 4 are assessed by a formal

examination.


Learning Outcome

Assessment


Weighting


1

2

3

4

5

Examination


60%



x

x

x

x


Workshops


20%







x


Assignment


20%







x



INDICATIVE READING


Core Texts

Control Systems Engineering

Second Edition

Norman S Nise

Benjamin/Cummings Publish
ing Company, Inc. 1995.


Mechatronics: The Design of Intelligent Machines

Volume 2
-

Concepts in Artificial Intelligence

Jeffrey Johnson and Philip Picton

Butterworth
-
Heinemann 1994


Recommended Reading

Modern Control Systems

Seventh Edition

Richard C Dorf

and Robert H Bishop

Addison
-
Wesley 1995.


Applied Digital Control: Theory, Design and Implementation

J R Leigh

Prentice
-
Hall, 1985.


Control Engineering

C C Bissell

Chapman & Hall, 1994.


A Course in Fuzzy Systems and Control

Li
-
Xin Wang

Prentice Hall 199
7


Intelligent Control Systems

N K Sinha and M M Gupta (Eds)

IEEE Press 1996


An Introduction to Artificial Intelligence

Janet Finlay and Alan Dix

UCL Press 1996


Artificial Neural Networks: Concepts and Control Applications

V Rao Vemuri (ed)

IEEE Computer

Society Press 1992


Neural Network Applications in Control

G W Irwin, K Warwick and K J Hunt (Eds)

Institution of Electrical Engineers 1995


Industrial Applications of Fuzzy Logic and Intelligent Systems

John Yen, Reza Langari and Lotfi A Zadeh (Eds)

IEEE

Press 1995

Journals


IEEE Control Systems Journal.

IEEE Tranasactions on Automatic Control.

IEE Computing and Control Engineering Journal

Control Engineering Journal

Computers in Industry

Expert Systems Journal

IEEE Transactions on Neural Networks

Artific
ial Intelligence Journal




Unit Author: A A Wardak

Date Prepared: February 2003