ES3C815 Systems Modelling and Control
Introductory description
ES3C815 Systems Modelling and Control
Module aims
Most disciplines of the engineering profession require a sound understanding of the techniques used in the modelling and control of dynamic, multidomain physical, and other, systems. The aims of this module are: to build on techniques and computer tools for modelling, predicting and analysing the behaviour of dynamic systems; and to build on concepts, principles and techniques employed in classical methods of single loop feedback control system design.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
The module will focus on a broad and generic systems approach to understanding physical systems modelling and their control. Techniques for systems analysis, approaches to systems modelling and the techniques for the simulation of systems models will be considered together with control algorithms and the conditions for which a system is controllable. In particular, a rigorous approach to the application of physical laws to formulate appropriate dynamical systems representations, and their subsequent analysis using linear and nonlinear methods, will be taught.
The application of appropriate computational tools for systems analysis and simulation will naturally be included. The examples presented will be drawn from a range of different engineering disciplines ranging from mechanical and electrical to biological systems to illustrate the advantages of a systems approach.
In particular the module includes:
System modelling and analysis in time domain: review of systems modelling (1st and 2nd order) linking behavior to physical parameters, block diagrams, signalflow graphs, system classification, inputoutput models, free and forced responses, transient and steady state responses, poles, Argand diagram.
System modelling and analysis in complex frequency domain: transfer function analysis, Laplace transform, initial and final value theorems, characteristic polynomial, stable/unstable/marginally stable systems with examples, systems modes; system representation: convolution in time domain, unit impulse and unit step responses and their applications.
Frequency domain analysis: frequency response, steady state frequency response, gain and phase, graphical representations of frequency response, magnitude and phase, Bode plots, Nyquist plots, links between timedomain specifications and frequency domain specifications; stability analysis using root locus, Nyquist plot, and Bode plots; robustness characterization using gain margin and phase margin.
Systems control: stability and feedback, feedback systems, openloop and closed loop transfer functions, root locus plots, Nyquist stability criterion, conditionally stable systems, phase crossover frequency and gain margin, gain crossover frequency and phase margin, feedback control of linear systems, PID controllers, conditions on controllers parameters for their optimal performance, realizable controllers.
State space modelling and analysis: state space description, linear state space models, transfer function, transient response, characteristic equation and stability, system diagonalization and normal modes, stiff systems; nonlinear systems: equilibrium points/steady states, linearization around equilibrium points, Jacobian matrices, stability; state space analysis: systems controllability and observability, controllability and observability matrices, rank criteria, system in a diagonal form and normal modes, relationship with transfer function, minimal realization of a system; state feedback: feedback control and stability.
Computer tools for modelling: simulating and analysing dynamical systems in MATLAB/Simulink.
Learning outcomes
By the end of the module, students should be able to:
 4. Develop state space models for both linear and nonlinear systems, and utilize appropriate techniques to perform state space analysis including design of state space feedback control systems.
 1. Develop mathematical models of physical systems using appropriate physical laws and expressing the models with ordinary differential equations, utilise engineering analysis to demonstrate commonality in behaviour.
 2. Apply analytical techniques for analyzing the response of both linear and nonlinear systems in time and frequency domain to a range of inputs.
 3. Utilise computational methods (Matlab/Simulink) to analyse and predict dynamical behaviour of physical systems (e.g. steadystate and transient response to a range of inputs) including stability performance analysis.
 5. Utilize computational methods in MATLAB/SIMULINK to apply concepts and techniques for analysis of the behaviour of open loop physical systems, and to design feedback control systems (PID), analyse their behaviour and assess their stability.
Indicative reading list
 Close C.M., Frederick D.H., Newell J.C., Modelling and Analysis of Dynamic Systems, M John Wiley and Sons Ltd, 1995, ISBN 9780395661581
 Norman Nise, Control Systems Engineering (7th Edition). John Wiley & Sons, 2013.
 Franklin, G.F., Powell, J.D. and EmamiNaeini, A., Feedback Control of Dynamic Systems (6th Edition), Pearson Academic Computing, 2012.
Subject specific skills
Ability to apply relevant practical and laboratory skills
Ability to be pragmatic, taking a systematic approach and the logical and practical steps necessary for, often complex, concepts to become reality
Transferable skills
Numeracy: apply mathematical and computational methods to communicate parameters, model and optimize solutions.
Apply problem solving skills, information retrieval, and the effective use of general IT facilities.
Overcome difficulties by employing skills, knowledge and understanding in a flexible manner
Be professional in their outlook, be capable of team working, be effective communicators, and be able to exercise responsibility and sound management approaches.
Study time
Type  Required 

Lectures  16 sessions of 1 hour (11%) 
Seminars  6 sessions of 2 hours (8%) 
Practical classes  (0%) 
Supervised practical classes  2 sessions of 4 hours (5%) 
Other activity  3 hours (2%) 
Private study  111 hours (74%) 
Total  150 hours 
Private study description
111 hrs guided independent learning
Other activity description
Laboratory  Control of Hot Air using PID controller
Costs
No further costs have been identified for this module.
You must pass all assessment components to pass the module.
Students can register for this module without taking any assessment.
Assessment group D4
Weighting  Study time  

Systems Modelling & Control Assignment  40%  
Systems Modelling & Control Design Assignment 

Inperson Examination  60%  

Feedback on assessment
 Model solutions to past papers (if available).
 Support through advice and feedback hours.
 Cohortlevel feedback on assignment
 Cohortlevel feedback on final exam.
Postrequisite modules
If you pass this module, you can take:
 ES4G415 Nonlinear Control and Reinforcement Learning
 ES4F015 Advanced Control Systems
Courses
This module is Core for:
 Year 3 of UESAH335 BEng Automotive Engineering
 Year 4 of UESAH334 BEng Automotive Engineering with Intercalated Year
 Year 3 of UESAH161 BEng Biomedical Systems Engineering
 Year 3 of UESAHH35 BEng Systems Engineering
 Year 3 of UESAHH36 BEng Systems Engineering
 Year 4 of UESAHH34 BEng Systems Engineering with Intercalated Year
 Year 3 of UESAH336 MEng Automotive Engineering
 Year 3 of UESAH163 MEng Biomedical Systems Engineering

UESAHH31 MEng Systems Engineering
 Year 3 of HH31 Systems Engineering
 Year 3 of HH35 Systems Engineering
 Year 4 of UESAHH32 MEng Systems Engineering with Intercalated Year
 Year 3 of UESAH605 Undergraduate Electrical and Electronic Engineering
 Year 4 of UESAH60V Undergraduate Electrical and Electronic Engineering (with Intercalated Year)
 Year 3 of UESAH606 Undergraduate Electrical and Electronic Engineering MEng
 Year 4 of UESAH607 Undergraduate Electrical and Electronic Engineering with Intercalated Year
This module is Core optional for:
 Year 4 of UESAH334 BEng Automotive Engineering with Intercalated Year
 Year 4 of UESAH337 MEng Automotive Engineering with Intercalated Year
 Year 4 of UESAH164 MEng Biomedical Systems Engineering with Intercalated Year
 Year 3 of UESAH115 MEng Engineering with Intercalated Year
 Year 4 of UESAHH32 MEng Systems Engineering with Intercalated Year
 Year 3 of UESAH11L Undergradaute Engineering (with Intercalated Year)

UESAH607 Undergraduate Electrical and Electronic Engineering with Intercalated Year
 Year 3 of H607 Electrical and Electronic Engineering with Intercalated year
 Year 4 of H607 Electrical and Electronic Engineering with Intercalated year
This module is Optional for:
 Year 3 of UESAH113 BEng Engineering
 Year 3 of UESAH114 MEng Engineering
 Year 4 of UESAH115 MEng Engineering with Intercalated Year

RESAH6P9 Postgraduate Research Wide Bandgap Power Electronics
 Year 1 of H6P9 Wide Bandgap Power Electronics (EngD)
 Year 2 of H6P9 Wide Bandgap Power Electronics (EngD)
 Year 1 of TESAH800 Postgraduate Taught Biomedical Engineering

UESAH11L Undergradaute Engineering (with Intercalated Year)
 Year 3 of H11L Engineering (with Intercalated Year)
 Year 4 of H11L Engineering (with Intercalated Year)
This module is Option list A for:
 Year 4 of UESAH111 BEng Engineering with Intercalated Year

UESAH112 BSc Engineering
 Year 3 of H112 Engineering
 Year 3 of H112 Engineering
 Year 1 of TESAH643 Postgraduate Taught Electrical Power Engineering
 Year 1 of TESAH642 Postgraduate Taught Energy and Power Engineering

UMAAG100 Undergraduate Mathematics (BSc)
 Year 3 of G100 Mathematics
 Year 3 of G100 Mathematics
 Year 3 of G100 Mathematics
 Year 3 of UMAAG103 Undergraduate Mathematics (MMath)
 Year 4 of UMAAG101 Undergraduate Mathematics with Intercalated Year
This module is Option list B for:
 Year 3 of UCSAG406 Undergraduate Computer Systems Engineering
 Year 3 of UCSAG408 Undergraduate Computer Systems Engineering
 Year 4 of UCSAG407 Undergraduate Computer Systems Engineering (with Intercalated Year)
 Year 4 of UCSAG409 Undergraduate Computer Systems Engineering (with Intercalated Year)

UMAAG105 Undergraduate Master of Mathematics (with Intercalated Year)
 Year 4 of G105 Mathematics (MMath) with Intercalated Year
 Year 5 of G105 Mathematics (MMath) with Intercalated Year

UMAAG103 Undergraduate Mathematics (MMath)
 Year 3 of G103 Mathematics (MMath)
 Year 3 of G103 Mathematics (MMath)
 Year 4 of G103 Mathematics (MMath)
 Year 4 of G103 Mathematics (MMath)

UMAAG106 Undergraduate Mathematics (MMath) with Study in Europe
 Year 3 of G106 Mathematics (MMath) with Study in Europe
 Year 4 of G106 Mathematics (MMath) with Study in Europe