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ARC Centre of Excellence for Complex Dynamic Systems and
Control
2009 ANNUAL REPORT
The University of Newcastle Callaghan NSW 2308 Australia
T +61 2 4921 7072 F +61 2 4960 1712 W
www.newcastle.edu.au/centre/cdsc
UoN 2010/1001
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2009 ANNUAL REPORT 01
Enquiries and further information:
Laureate Professor Graham C.Goodwin Director ARC Centre of
Excellence for Complex Dynamic Systems and Control
The University of Newcastle Callaghan, NSW 2308 Australia
T: +61 2 4921 7072 F: +61 2 4960 1712 E: [email protected]
W: www.newcastle.edu.au/centre/cdsc
Publication details: Design: Bounce Editorial Assistant: Dianne
Piefke, CDSC Printing: NCP Printing
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ARC Centre of Excellence for Complex Dynamic Systems and
Control02
TABLE Of CONTENTS
OUR VISION 6
DIRECTOR’S REPORT 7
STAFF 8
POSTGRADUATE RESEARCH STUDENTS 9
THESES SUBMITTED IN 2009 10 GRADUATED 2009 10
UNDERGRADUATE RESEARCH STUDENTS 11
ADVISORY BOARD 12
VISITORS 14
ACADEMIC VISITORS 14 STUDENT VISITORS 15
INDUSTRIAL INTERACTIONS AND SELECTED OUTCOMES 2009 16
CONFERENCES, COURSES AND WORKSHOPS 2009 19
SEMINARS 20
SELECTED HIGHLIGHTS 2009 22
RESEARCH PROGRAMS 2009 23
A INDUSTRIAL CONTROL AND OPTIMIZATION 24 A.1 OPTIMISATION BASED
OPERATOR GUIDANCE SCHEMES (BHP – BILLITON) 24 A.1.1 Sferics
reduction in electromagnetic mineral exploration 24 A.1.2
Co-generation at WestVAMP 25
A.2 INTEGRATED MINE PLANNING (BHP – BILLITON) 26 A.2.1
Estimation of commodity price modelling 26 A.2.2 Discrete event
simulation modelling of open pit mine shovel and truck operations
26
A.3 NEXT GENERATION MODEL-BASED CONTROL TOOLS (MATRIKON) 28
A.3.1 Next generation model based control tools for cpo 28 A.3.2
Automated downtime cause classifier for processMORE 28
A.4 CSR SUGAR (INDUSTRIAL AffILIATE) 29 A.4.1 Constrained,
multivariable control of an integrated sugar mill system for
economic enhancement 29
A.5 INTELLIGENT ELECTRICITY NETWORK PROJECTS (ENERGY AUSTRALIA)
30 A.5.1 fault accommodation in electricity networks 30 A.5.2 fault
detection in electricity networks 30
A.6 APPLICATION Of SYSTEM IDENTIfICATION TO PARAMETER ESTIMATION
IN THE POWER INDUSTRY (AURECON) 31
A.7 MARINE AND AEROSPACE SYSTEMS 32 A.7.1 Marine simulation
tools 32 A.7.2 Control of marine vessels with mater jets (CfW
Hamilton Jet & Co., New Zealand) 32 A.7.3 Experiment design and
identification of nonlinear manoeuvring models of marine vessels
(Austal Ships, Australia) 32 A.7.4 Gyroscopic stabilisation of
marine platforms (Halcyon International, Australia) 32 A.7.5
Adaptive and fault-tolerant control of underwater vehicles 34 A.7.6
Ship motion control for offshore marine operations in training
simulators (Offshore Simulator Centre AS, Norway) 35
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2009 ANNUAL REPORT 03
A.7.7 Evaluation of robust autonomy for uninhabited airborne
systems (UAS) (Boeing Research & Technology Australia) 36 A.7.8
A USA simulator for testing fault-tolerant flight control and
guidance systems (Boeing Research & Technology Australia) 36
A.7.9 Identification of dynamic models for uninhabited airborne
systems (UAS) (Boeing Research & Technology Australia) 37
B MECHATRONICS 38 B.1 INTEGRAL RESONANT CONTROL fOR VIBRATION
DAMPING AND PRECISE TIP-POSITIONING Of A SINGLE-LINK fLEXIBLE
MANIPULATOR 38
B.2 REDUCING CROSS-COUPLING IN A COMPLIANT XY NANOPOSITIONER fOR
fAST AND ACCURATE RASTER SCANNING 40
B.3 ATOMIC fORCE MICROSCOPE WITH A 12-ELECTRODE PIEZOELECTRIC
TUBE SCANNER 42
B.4 ULTRASONIC ENERGY TRANSMISSION AND CONVERSION USING A 2D
MEMS RESONATOR 43
B.5 SIGNAL TRANSfORMATION APPROACH TO fAST NANOPOSITIONING
44
B.6 SPIRAL SCANNING: AN ALTERNATIVE TO CONVENTIONAL RASTER
SCANNING IN HIGH-SPEED ATOMIC fORCE MICROSCOPES 45
B.7 IMPROVING THE SPEED AND ACCURACY Of A COMMERCIAL ARM BY
fASTER USING POSITIVE POSITION fEEDBACK CONTROL 46
B.8 OPTIMAL PERIODIC TRAJECTORIES fOR BAND-LIMITED SYSTEMS
47
B.9 HIGH-SPEED SERIAL-KINEMATIC SCANNER DESIGN 47
B.10 INTEGRAL RESONANCE CONTROL Of LATERAL AfM SCANNERS 48
B.11 ULTRA-WIDEBAND DRIVES fOR PIEZOELECTRIC ACTUATORS 49
C CONTROL SYSTEM DESIGN 50 C.1 NONLINEAR MODEL PREDICTIVE
CONTROL 50 C.1.1 Constrained nonlinear model predictive control
50
C.2 ROBUST MODEL PREDICTIVE CONTROL 51 C.2.1 Robust
output-feedback MCP with integral action 51 C.2.2 Inverse minimax
optimality of model predictive control policies 52
C.3 VIRTUAL LABORATORIES 52
C.4 ADAPTIVE CONTROL 52 C.4.1 Adaptive control of a special
class of systems having fixed “plant” and non-stationary noise
model 52
C.5 fAULT TOLERANT CONTROL 52 C.5.1 Actuator fault tolerant
control 52 C.5.2 Strategies for dealing with sensor faults and
recoveries 53
C.6 INVARIANT SETS AND ULTIMATE BOUNDS IN PERTURBED SYSTEMS
53
D SIGNAL PROCESSING 54 D.1 SYSTEM IDENTIfICATION 54 D.1.1 Errors
in variables 54 D.1.2 Time and frequency domain identification 55
D.1.3 Identification of systems having quantized output data 55
D.1.4 Parameter estimation of structural commodity price models 55
D.1.5 Short or long memory estimators? 55 D.1.6 fundamental
limitations on the accuracy of mimo linear models obtained by pem
for systems operating in open loop 56 D.1.7 Redundancy vs. Multiple
starting points in nonlinear systems related inverse problems 56
D.1.8 Continuous-time system identification using indirect
inference 56
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ARC Centre of Excellence for Complex Dynamic Systems and
Control04
D.2 COMMUNICATIONS 57
D.3 fILTER DESIGN AND SPEECH SIGNAL PROCESSING 58 D.3.1 Variance
or spectral density in sampled data filtering? 58 D.3.2 Nonlinear
filtering 58 D.3.3 Time-frequency synthesis of noisy sounds using
narrow spectral components 58 D.3.4 On pole-zero model estimation
methods minimizing a logarithmic criterion for speech analysis
58
D.4 QUANTIZED CONTROL SYSTEMS 59 D.4.1 Stabilization of jump
linear systems using quantized feedback 59 D.4.2 Input and output
quantized feedback linear systems 59 D.4.3 Distributed consensus
with limited communication data rate 59 D.4.4 Quantized linear
quadratic gaussian control 59
D.5 DUAL-STAGE ACTUATOR SYSTEMS 60 D.5.1 Stability analysis and
design of reset systems: theory and an application 60 D.5.2 A
factorization approach to sensitivity loop shaping for disturbance
rejection in hard disk drives 60 D.5.3 Dual-stage actuator control
design using a doubly coprime factorization approach 60
D.6 A SCENARIO BASED APPROACH TO ROBUST EXPERIMENT DESIGN 61
E STATISTICS 62 BAYESIAN LEARNING (QUT NODE) 62 E.1 ADVANCES IN
BAYESIAN METHODOLOGY 63 E.1.1 Mixture models 63 E.1.2 Space/time/+
models 63 E.1.3 Meta-analysis 64 E.1.4 Bayesian networks 64 E.1.5
Priors 64
E.2 ADVANCES IN BAYESIAN COMPUTATION 65 E.2.1 importance
sampling 65 E.2.2 New agorithms 65 E.2.3 Sparse matrix
representation 65 E.2.4 Segmentation algorithms 66
E.3 ADVANCES IN BAYESIAN APPLICATIONS 66 E.3.1 Ecology 66 E.3.2
Genetics 67 E.3.3 Agriculture 67 E.3.4 Health 67
STATISTICAL INFERENCE AND MODELLING (UON NODE) 68
E.4 COST DISTRIBUTIONS fOR DYNAMIC STOCHASTIC SCHEDULING 69
E.5 CATEGORICAL DATA ANALYSIS 69 E.5.1 Graphical analysis of
categorical data 70 E.5.2 Numerical analysis of categorical data
70
E.6 ANALYSING AND REPORTING CLINICAL INDICATORS USING BAYESIAN
HIERARCHICAL MODELS 71
E.7 NONLINEAR TIME SERIES ESTIMATION AND DNA SEQUENCE MODELLING
IN BIOINfORMATICS 72
E.8 SMOOTH TESTS fOR GOODNESS Of fIT 73
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2009 ANNUAL REPORT 05
E.9 HIERARCHICAL APPROACHES TO META-ANALYSIS 74
E.10 CONSENSUS PRIORS fOR BAYESIAN ANALYSIS 75
F DISTRIBUTED SENSING AND CONTROL 76 f.1 POWER TRANSfORMER
MODELLING 76 f.1.1 The physical modelling of power transformers
from fRA data 76 f.1.2 Constraining transformer model parameters
77
f.2 ROBOTICS RESEARCH 78 f.2.1 Multimodal UKf localization using
visual landmarks and odometery motion model 78 f.2.2 A study of
manifold alignment using an artificial acoustic dataset 79 f.2.3
Autonomous optimisation of joint stiffnesses over the entire gait
cycle for the nao robot 79 f.2.4 Perturbation sensing for humanoid
robots using a multiclass support vector machine 80 f.2.5 Modelling
and simulation of the john hunter hospital emergency department
80
f.3 NETWORK CONTROL 81 f.3.1 Analysis and design of networked
control systems using the additive noise model methodology 81 f.3.2
Design of control systems over unreliable channels 81
f.4 SENSOR NETWORKS 81 f.4.1 Innovations-based state estimation
with wireless sensor networks 81
G MATHEMATICAL SYSTEMS THEORY 82 G.1 BEYOND SPECTRUM 82
G.2 NONLINEAR ANALYSIS, OPTIMIZATION AN D fIXED-POINT THEORY
83
G.3 HYPERCOMPLEX SIGNAL PROCESSING 85
G.4 SAMPLING IN PAKLEY-WIENER AND SHIfT-INVARIANT SPACES 86
PUBLICATIONS 87
BOOKS 87
BOOKS IN PREPARATION/TO APPEAR 87
CHAPTERS IN BOOKS 87
BOOK CHAPTERS IN PREPARATION 87
PLENARY AND KEYNOTE ADDRESSES 87
PATENTS 88
JOURNAL PAPERS 88
JOURNAL PAPERS ACCEPTED fOR PUBLICATION 91
REfEREED CONfERENCE PAPERS 94
TECHNICAL REPORTS TO INDUSTRY 97
PERFORMANCE INDICATORS REPORT 100
INCOME AND EXPENDITURE STATEMENTS 108
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OUR VISION
To be a world leader in analysis, design and optimisation of
complex dynamic systems; pursuing outstanding fundamental and
applied research.
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2009 ANNUAL REPORT 07
DIRECTOR’S REPORT
The past year has seen many developments by our research
team.
This report summarizes the outcomes in both basic and applied
research. As for previous reports, we include a special section on
selected outcomes achieved in collaboration with our industrial
partners. We take particular pride in these outcomes.
You will also see in the report that our work continues to
achieve high international recognition. In particular, I am pleased
to report that Professor Reza Moheimani (CDSC Associate Director)
won the 2009 IEEE CSS Control Systems Technology Award for
outstanding contributions to nanopositioning for
microelectromechanical systems (MEMS)-based storage and other
applications jointly with co-workers from IBM Zurich.
We currently support (via various funding mechanisms), a team of
approximately 60 researchers including academics, postdocs and
postgraduate students. We are also engaged in over 20 separate
industrial R&D projects. Naturally, the existence of this
unique team depends upon the availability of continued funding.
Thus 2010 will be an important year for CDSC since our current
funding ceases in December. We will thus need to apply for new
funding from the Australian Research Council. We believe that our
track record is excellent and, hopefully, this will put us in a
strong position in the new funding round.
On a personal note, it has been announced that I will be awarded
the 2010 IEEE Control System Society field Award. This is a great
personal honour for me and, of course, also reflects the wonderful
team with whom I work.
I believe that CDSC provides an exciting and vibrant research
environment spanning basic research through to relevant industrial
applications. The work would not be possible without the support of
many organizations. In particular, I wish to gratefully acknowledge
financial support from the Australian Research Council, NSW
Department of State and Regional Development, The University of
Newcastle, Queensland University of Technology, our industrial
partners, and our industrial affiliates.
finally, I would like to take this opportunity to express my
thanks to the full CDSC team for their hard work and support during
the past year.
Graham C. GoodwinDirector and Laureate Professor
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ARC Centre of Excellence for Complex Dynamic Systems and
Control08
STAff
STAff MOVEMENTS
Director
Laureate Professor Graham Goodwin
Associate Directors
Professor Minyue fu Professor S.O. Reza Moheimani
Chief Operating Officer
Dr Greg Adams
Program Leaders
Signal Processing Professor Minyue fu (Leader) Dr Juan-Carlos
Agüero (Deputy Leader)
Control System Design Dr Maria Seron (Leader) Laureate Professor
Graham Goodwin (Deputy Leader)
Bayesian Learning (QUT Node) Professor Kerrie Mengersen
(Leader)Professor Ian Turner (Deputy Leader)
Industrial Control and Optimization Dr Julio Braslavsky (Leader)
Dr Tristan Perez (Deputy Leader)
Mechatronics Professor S.O. Reza Moheimani (Leader)Dr Andrew
fleming (Deputy Leader)
Statistical Inference Professor John Rayner (Leader)
Dr Robert King Associate Professor Eric Beh (Deputy Leaders)
Mathematical Systems Theory Associate Professor Brailey Sims
(Leader) Dr Jose De Doná (Deputy Leader)Professor George Willis
(Research Coordinator)
Distributed Sensing and Control Dr James Welsh (Leader)
Professor Rick Middleton (Deputy Leader)
Industry Liaison Officer
Dr Tristan Perez
Industry Partner Investigators
Dr Salvatore (Sam) Crisafulli (Matrikon)
Dr Merab Menabde (BHP-Billiton Innovation)
Dr R. Arthur M. Maddever (BHP-Billiton Innovation)
Mr Peter Stone (BHP-Billiton Innovation)
Mr Richard Thomas (Matrikon)
Industrial Affiliates:
Aurecon (previously Connell Wagner)
Boeing Research & Technology, Australia
CfW-Hamilton Jet & Co. (New Zealand)
CSR Sugar
Halcyon International
Hatch IAS
IBM Zurich Research Laboratories
Other Investigators
Laureate Professor Jon Borwein
Dr Jeffrey Hogan
Dr Peter Howley
Dr Kaushik Mahata
Dr Darfiana Nur
Dr Daniel Quevedo
Dr Elizabeth Stojanovski
Dr frank Tuyl
CDSC Funded Researchers
Dr David Allingham
Dr Clair Alston (QUT)
Mr Miroslav Bacak
Dr Ali Bazaei
Dr John Best
Dr Li Chai
Mr O-Yeat Chan
Mr Pierre de Lamberterie
Dr Alejandro Donaire
Dr Boris Godoy
Dr fawang Liu (QUT)
Dr Katrina Lau
Dr Paula Lennon (QUT)
Mr Iskandar Mahmood
Dr Damian Marelli
Dr Adrian Medioli
Mr Sean Moyniham (QUT)
Dr Claus Müller
n Alejandro Donaire commenced working with Tristan Perez in the
Marine and Aerospace Projects in August.
n Raheleh Nazari worked with Maria Seron and has been accepted
into the University of Newcastle PhD program to commence 2010.
n Priyanka Vaidya is working with James Welsh and Julio
Braslavsky in the Industrial Control and Optimization Program.
n Dr Ross McVinish and Dr Ian Wood were successful in obtaining
academic positions at the University of Queensland.
n Research Assistant Pierre De Lamberterie commenced work with
Tristan Perez and James Welsh on the Boeing project.
Ms Raheleh Nazari
Dr Jun Ning
Dr Jaime Peters (QUT)
Dr Alejandro Rojas
Ms Priyanka Vaiyda
Ms Zoe van Havre (QUT)
Dr Meng Wang
Dr Yuenkuan Yong
Dr Mei Mei Zhang
Dr Jinchuan Zheng
Engineering Staff
Mr frank Sobora
Support Staff
Mr Jason Kimberley
Mr Andrew Lawrence
Mr Gabriel Noronha
Mr Kevin Monahan
Mrs Jayne Disney
Mrs Dianne Piefke
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2009 ANNUAL REPORT 09
POSTGRADUATE RESEARCH STUDENTS
Stephen Allen Thesis Title: “Corners in graph
algebra”Supervisor: D. PaskCo-Supervisor: I. RaeburnDegree: PhD
Sri Astuti Thamrin – (QUT) (Commenced 2009)Thesis Title:
“Bayesian methods for survival analysis using high-dimensional
data”Supervisor: K.L. MengersenDegree: PhD
Brendan BurkeThesis Title: “Constrained, multi- variable control
of an integrated sugar mill system for economic
enhancement”Supervisor: G. AdamsCo-Supervisor: G.C. GoodwinDegree:
ME
Francisco Eduardo Castillo SantosThesis Title: “Aspect of metric
fixed point theory”Supervisor: B. SimsCo-Supervisor: G.
WillisDegree: PhD
Mauricio Cea (Commenced 2009)Thesis Title: “Scheduling and
control of WCDMA wireless communications”Supervisor: G.C. Goodwin
Co-Supervisor: K. LauDegree: ME
Ben Dean Thesis Title: “Modelling with the generalised lambda
distribution” Supervisor: R. KingCo-supervisor: P. HowleyDegree:
PhD
Margaret Donald Thesis Title: “Bayesian spatio- temporal models
and networks”Supervisor: K.L. MengersenDegree: PhD
Arul Earnest Thesis Title: “Bayesian spatial modelling of sparse
outcomes”Supervisor: K.L. MengersenDegree: PhD
Matthew Fairbairn (Commenced 2009)Thesis Title: “feedback
control of an atomic force microscope”Supervisor: S.O.R.
MoheimaniCo-Supervisor: A. flemingDegree: ME
Naomi Henderson Thesis Title: “Improving robot vision using
spatial and temporal correlations”Supervisor: R. KingCo-Supervisor
S. Chalup/R.H. MiddletonDegree: MPhil
Kenny Hong Thesis Title: “face perception and face expression
dynamics”Supervisor S. ChalupCo-Supervisor: R. King / S.LuoDegree:
PhD
Wenbiao Hu (QUT)Thesis Title: “Bayesian spatio- temporal
CART”Supervisor: K. MengersenDegree: ME
Jason Kulk Thesis Title: “Anthropomorphic stance and walk for
consumer robots”Supervisor: J.S. WelshCo-Supervisor: Z. ChenDegree:
ME
Saeid Mehrkanoon (Commenced 2009)Thesis Title: “Implementation
of blind signal separation and neural network based system for
epileptic EEG signal extraction and seizure source
localization”Supervisor: J.S. WelshCo-Supervisor: J.C.
AgüeroDegree: ME
Steven MitchellThesis Title: “Physical interpretation of the
broadband frequency response of power transformersSupervisor: J.S.
WelshCo-Supervisor: R.E. BetzDegree: PhD
Raheleh Nazari (Commenced 2009)Thesis title: “fault tolerant
control of uncertain systems”Supervisor: M.M. SeronCo-Supervisor:
J.A. De DonáDegree: ME
Steven NicklinThesis Title: “Using model predictive control in
bipedal locomotion”Supervisor: J.S. Welsh/R.H.
MiddletonCo-Supervisor: K. MahataDegree: PhD
Cristian Perfumo (Commenced 2009)Thesis Title: “Multiobjective”
` optimisation for building comfort and energy”Supervisor: J.H.
BraslavskyCo-Supervisor: J. Ward (CSIRO Energy Technology)Degree:
ME
Paul RipponThesis Title: “Application of smooth tests of
goodness of fit to generalised linear models”Supervisor: J.
RaynerCo-Supervisor: f. TuylDegree: PhD
Eduardo Rohr (Commenced 2009)Thesis Title: “Estimation problems
arising in networked control aystems”Supervisor: M.
fuCo-Supervisor: D. MarelliDegree: ME
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ARC Centre of Excellence for Complex Dynamic Systems and
Control10
Fatimah Almah Saaid Thesis Title: “Detecting telecommunications
fraud using time series data” Supervisor: D. NurCo-supervisor: R.
KingDegree: PhD
Aurelio SaltonThesis Title: “Dual-stage actuator control
systems”Supervisor: M. fuCo-Supervisor: Z. Chen/J. ZhengDegree:
PhD
Matthew SkerrittThesis Title: Projection of algorithms in the
abence of convexityy”Supervisor: B. SimsDegree: MPhil
Fajar SuryawanThesis title: “Nonlinear model predictive
control”Supervisor: J.A. De DonáCo-Supervisor: M.M. SeronDegree:
PhD
Xin Tai (Commenced 2009)Thesis Title: “Distributed estimation in
sensor networks”Supervisor: M. fuCo-Supervisor: D. MarelliDegree:
ME
Ian SearstonThesis Title: “Analysis in geodesic metric
spaces”Supervisor: B. SimsCo-Supervisor: G. WillisDegree: PhD
Alain Yetendje-LemegniThesis Title: “fault tolerant multisensory
systems”Supervisor: M.M. SeronCo-Supervisor: J.A. De DonáDegree:
PhD
Lukasz WiklendtThesis Title: “Learning and control in
robotics”Supervisor: S. ChalupCo-Supervisor: M.M. SeronDegree:
PhD
THESES SUBMITTED IN 2009
Kingsley Ezeh Thesis Title: “Statistical techniques for
improving health care”Supervisor: P. HowleyCo-Supervisor: R.
KingDegree: MSc
Kate Lee (QUT) Thesis Title: “MCMC algorithms”Supervisor: K.
MengersenCo-Supervisor: R. McVinishDegree: PhD
Iskandar Mahmoud Thesis Title: “System identification and robust
control of spatially distributed systems”Supervisor: S.O.R.
MoheimaniCo-Supervisor: B.M. NinnessDegree: PhD
Zhuo, Xiang WeiThesis Title: “Estimation and control:
Multisensors, explicit solutions and duality”Supervisor: J.A. De
DonáCo-Supervisor: G.C. GoodwinDegree: PhD
GRADUATED 2009
Milan DerpichThesis Title: “Sampling and quantization in audio
compression”Supervisor: G.C. Goodwin Co-Supervisor: D.
QuevedoDegree: PhD
Sandra Johnson (QUT)Thesis Title: “Bayesian networks”Supervisor:
K. MengersenDegree: PhD
Chris Oldmeadow Thesis Title: “Bayesian latent variable
models”Supervisor: K. MengersenDegree: PhD
Eduardo SilvaThesis Title: “Performance limitations in networked
control”Supervisor: G.C. Goodwin Co-Supervisor: D. QuevedoDegree:
PhD
Meng WangThesis Title: “Parsimonious information structures in
real time signal processing”Supervisor: G.C. Goodwin Co-Supervisor:
D. QuevedoDegree: PhD
Darren Wraith (QUT)Thesis Title: “Bayesian mixture models for
environmental health”Supervisor: K. MengersenCo-Supervisor: S.
Tong/R. KingDegree: PhD
Dr Meng Wang and Professor Graham Goodwin, graduation ceremony
2009.
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2009 ANNUAL REPORT 11
UNDERGRADUATE RESEARCH STUDENTS
David Ferris University of Newcastle Industry Scholarship
Student (UNISS)Project Title: “Virtual Laboratory on Wind Power
Generation” Supervisor: Graham Goodwin
Hal Cooper CDSC Industrial Development Scholarship Student
(funded by NSW Department of State and Regional Development)
Project Title: “Emergency Department Modelling” Supervisor: Graham
Goodwin/ James Welsh
Elizabeth Ryan QUT Australian Mathematical Sciences Institute
Scholarship Student Project Title: “Spatio-temporal Modelling of
Outbreaks” Supervisor: Kerrie Mengersen
HONOURS STUDENTS
Remy Dyer Project Title: “Piezoelectric Injector for a Coal
fuelled Internal Combustion Engine” Supervisor: Andrew fleming
James Elliot Project Title: “Modeling and Simulation of the John
Hunter Hospital Emergency Department” Supervisor: James Welsh
Anthony Fowler Project Title: “Multidimensional Wave Energy
Harvester” Supervisor: Andrew fleming
Megan Ford (University Medalist) Project Title: “A Comparison of
The Bernouli CUSUM Chart and the Beta- Binomial Posterior
Predictive Chart” Supervisor: Brailey Sims
Ben Grabau Project Title: “Modeling and Simulation of an Alpha
60 Autonomous Aircraft” Supervisor: James Welsh
Aaron Hammond Project Title: “Electronic Safe Cracker”
Supervisor: James Welsh
Sam Johnson Project Title: “The Scale function on Groups of
Automorphisms of Locally finite Trees” Supervisor: George
Willis
Phillip Smith Project Title: “Piezoelectric Loudspeaker”
Supervisor: Andrew fleming
Daniel Sutherland Project Title: “The Game of Hex and the Brower
fixed Point Theorem” Supervisor: Brailey Sims
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ADVISORY BOARD
The CDSC Advisory Board met in Newcastle on friday 15 May 2009
to review progress, consider management issues and offer advice on
strategic directions for the Centre. The following are current
members of the Board.
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CHAIRMAN
Professor M. CalfordDeputy Vice-Chancellor, Research, The
University of Newcastle
CURRENT MEMBERS
Distinguished Professor B.D.O. AndersonResearch School of
Information Sciences and Engineering, The Australian National
University, Canberra, ACT
Professor A. CareyMathematical Sciences, Australian National
University, Canberra, ACT
Professor J. CarterPro. Vice-Chancellor, faculty of Engineering
and Built Environment, The University of Newcastle, Callaghan,
NSW
Dr S. CrisafulliManaging Director, Matrikon, Asia Pacific
Newcastle
Dr W.J. EdwardsIndustrial Automation Services Pty. Ltd.,
Teralba, NSW
Dr S. GaleaCSIRO, DSTO, Melbourne, Victoria
Mr R. HayesShell Refining (Australia) Pty. Ltd., Clyde Refinery,
Rosehill, NSW
Professor W. HogarthPro. Vice-Chancellor, faculty of Science and
Information Technology, The University of Newcastle, Callaghan,
NSW
Professor R. JarvisDepartment of Electrical and Computer Systems
Engineering, Monash University, Melbourne, Victoria
Dr B. JenkinsChief Executive Officer, Newcastle Innovation
Callaghan, NSW
Mr R. PeirceTechnical Systems, CSR Victoria Mill, Ingham,
Queensland
Professor I.R. PetersenAustralian Defence force Academy, UNSW,
Canberra, ACT
Mr C. ThewNSW Department of State and Regional Development,
Sydney, NSW
Professor A. SharmaDeputy Vice-Chancellor, Queensland University
of Technology
INVITED TO 2009 ADVISORY BOARD
Dr D. Hodgson (Representing Professor Hogarth)
Mr R. Thomas (Representing Dr S. Crisafulli)
Mr G. Wallace (Hatch-IAS)
Mr B. Williams (Boeing Research & Technology Australia)
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Professor Arthur JutanCanadaJuly - August 2009
Professor S. Mansour VaezpourAmirkabir University of Technology,
Tehran, Iranfebruary – July 2009
Professor Rick MiddletonMaynooth InstituteDublin, Republic of
IrelandApril 2009
Dr John-Jairo Molina-MartinezGIPSA-Lab, INPGSaint Martin
d’Hères, franceMay - June 2009
Dr Cristian RojasRoyal Institute of TechnologyStockholm,
SwedenMarch – April 2009
Dr Monica RomeroUniversidad Nacional de RosarioArgentinaOctober
– November 2009
Professor Judith Rousseau (QUT)Universite DauphineParis,
franceSeptember 2009
Professor Mario SalgadoUniversidad Tecnica federico Santa
MariaValparaiso, ChileNovember 2009
Dr Holger Schwender (QUT)University of KahlsruheGermanyApril
2009
Dr Gavin Stewart (QUT)University of YorkUnited KingdomSeptember
2009
Dr Cristina StoicaSUPELECGif-Sur-Yvette, franceNovember –
December 2009
Dr Wei TangNorthwestern Polytechnical UniversityPeoples Republic
of ChinaAugust 2009 – August 2010
Dr Olivier ThasGhent UniversityBelgiumfebruary 2009
Dr Paul van StadenUniversity of PretoriaSouth AfricaDecember
2009
Dr Damjan Vukcevic (QUT)Oxford UniversityUnited KingdomOctober
2009
Professor Lihua XieNanyang Technological
UniversitySingapore.february 2009
ACADEMIC VISITORS
Dr Irit Aitkin (QUT)University of MelbourneJanuary 2009
Professor Murray Aitkin (QUT)University of MelbourneJanuary
2009
Professor Peter Donnelly (QUT)Oxford UniversityUnited
KingdomJuly 2009
Professor Antoine Ferreira ENSI, Bourgesfrancefebruary 2009
Professor Arie FeuerTechnion – Israel Institute of
TechnologyHaifa, Israel.March – September 2009
Professor Peter FlemingUniversity of SheffieldUnited
KingdomMarch – April 2009
Professor Thomas GustafssonLuleå University of
TechnologySwedenOctober 2009 – March 2010
Dr Hernan HaimovichNational University of
RosarioArgentinaDecember 2008 - March 2009
VISITORS
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Student ViSitorS
Keng-Yuen Chennational Chiao tung universitytaiwanAugust 2009 –
January 2010
Han ChunyenShandong universityPeoples republic of ChinaJuly 2009
– January 2010
Norbert Ehmsotto-von-Guericke – universitat
MagdeburgGermanyMarch - September 2009
Tom Gommans eindhoven university of technologythe
netherlandsAugust 2009 - January 2010
Elias Herrerouniversity of CantabriaSpainoctober – december
2009
Pierre de LamberterieGrenoble institute of
technologyFranceFebruary – August 2009
David Maennickotto-von-Guericke – universitat
MagdeburgGermanyMarch – September 2009
Jaap Nieuwenhuijseneindhoven university of technologythe
netherlandsnovember 2009 – January 2010
Solheil SalehpourLuleå university of technologySwedennovember
2009 – March 2010
Mads Sølver SvendsenAalborg universitydenmarkAugust – december
2009
Tai, XinZhijiang university Hangzhou, Peoples republic of
Chinanovember 2007 – April 2009
Joris Termaateindhoven university of technologythe
netherlandsAugust – december 2009
Wei WangHarbin institute of technologyPeoples republic of
ChinaAugust 2009 – January 2010
Visitors at the Annual Centre retreat
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ARC Centre of Excellence for Complex Dynamic Systems and
Control16
INDUSTRIAL INTERACTION AND SELECTED OUTCOMES 2009
A prime goal of CDSC is to combine outstanding fundamental and
applied research to back Australia’s industrial competitiveness and
capabilities. This section reports selected outcomes achieved in
collaboration with our industrial partners during 2009 and on our
outreach efforts to schools and undergraduate students.
for further information on how to establish an industrially
linked research partnership with CDSC, contact the Industrial
Liaison Officer, Dr. Tristan Perez,
[email protected]
Support from the NSW Department of State and Regional
DevelopmentWe greatly appreciate and acknowledge the support of the
NSW Department of State and Regional Development (DSRD), who
contribute significant funds to CDSC each year for the purposes of
development/NSW industries and research capabilities.
In 2009, our DSRD funds were used in the following ways:
n funding of the CDSC Industrial Development Scholarship to Hal
Cooper.
n Virtual Laboratories support
n Aurecon project support
n Outreach activities (Ambulance Research Institute of NSW,
Giant Magellan Telescope Organisation)
n Equipment for Mechatronics Laboratory
Industrial InteractionDuring 2009, CDSC:
n Opened fruitful discussions on collaboration with the
Ambulance Research Institute of NSW. It is expected that this
collaboration will grow in 2010.
n Started a major project with Boeing Research and Technology
Australia on safety and reliability aspects of uninhabited airborne
systems.
n Agreed on goals and aims for joint research project with DSTO
–Maritime Platforms Division, VIC. This project will start in 2010
and will be dedicated to the design of novel robust and
fault-tolerant control strategies for underwater vehicles.
1. COMMENTS BY INDUSTRIAL PARTNERS
Boeing Research & Technology Australia (BR&TA)“Aircraft
under pilot control can fly to any point on the globe, and the
general public perceives these events as having an acceptable level
of safety. Often these flights utilise the autopilot system for
long periods, without impacting this perception. Thus, this
perception is largely driven by the inclusion of humans in the loop
who are constantly monitoring the health of the vehicle and making
decisions regarding guidance and motion control. As we move towards
uninhabited systems (land, marine, aerospace), both regulation
authorities and the general public need to perceive a similar level
of safety as for piloted vehicles. The use of uninhabited systems
is increasing in both military and civil applications, like for
example, search and rescue, tactical reconnaissance, border patrol,
communication relay, and inspection of the environment, traffic,
crops, and power lines. This increase in use and applications
brings the need to attain high levels of safety and reliability,
which are captured by the term Robust Autonomy.
Robust autonomy can be described as the characteristic that
allows Uninhabited Airborne Systems (UAS) to either continue
operating in the presence of
faults or safely shut down. To achieve this characteristic, a
UAS has to incorporate mechanisms that augment the safety and
reliability of its guidance, navigation, communication, and control
(GNCC) systems.
In 2009, BR&TA became a partner of CDSC, and initiated a
joint research project under the flag of robust autonomy. The aim
of the project is develop novel methods for quantifying robust
autonomy of UAS and develop new fault-tolerant flight control and
guidance systems for UAS. During this first year, CDSC
proposed:
n A formalism to specify the GNCC required system functionality
based on the analysis of missions and vehicle use modes.
n A method to quantify robust autonomy of UAS based on
mission-vehicle specific performance criteria, which can be
evaluated using simulation scenarios for an envelope of
environmental conditions. The result of these evaluations is a
number from 0 to 1 (figure of merit) that captures operational
effectiveness. The procedure is then augmented to consider faults,
which leads to another figure of merit related to robust autonomy.
The objective of these figures of merit is to use them at both
vehicle development stage and with hardware-in-the-loop testing at
certification stage.
n A set of tests to collect flight-data to identify a
mathematical model of a UAS.
n Developed a UAS simulator that will be used to demonstrate the
use of fault-tolerant flight control and guidance systems and the
evaluation of robust autonomy.
The work done by CDSC provides a fundamental support of
BR&TA work on the Advanced UAS Applications
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2009 ANNUAL REPORT 17
Program. Our initial collaboration has exceeded our
expectations, and we look forward to continuing our partnership
with CDSC in 2010 and beyond.”
Brendan Williams Associate Technical fellow, Advanced UAS
Applications Program Leader, Boeing Research & Technology
Australia, QLD, AUSTRALIA
CSR SugarEconomic Enhancement of an Integrated Sugar Mill
‘The Co-generation plant at CSR Sugar’s Pioneer Mill (Ayr, NQ)
has brought significant benefits to CSR’s business, notably in
efficiency improvements, carbon abatement and new income streams.
The main factors in running the cogeneration plant involve the more
efficient operation of process units, and the optimal sharing of
mill resources between units, in particular steam.
Multi-effect evaporators are key process units in a sugar mill,
as it is there where the most efficient evaporation of water from
sugar syrup occurs. Pioneer Mill currently suffers from
unsatisfactory control of sugar content (brix) in syrup from the
evaporator sets, resulting in less efficient use of steam, and
hence loss of export power generation capability.
In 2009, CSR Sugar’s partnership with CDSC has resulted in
significant improvements to brix control. The reduction in
variability makes it possible to optimise operations at Pioneer
Mill significantly through better steam usage.”
Rob PeirceManager, Computer Services Department CSR Sugar
Ingham, QLD
Halcyon International Pty Ltd.“In 2009, Halcyon continued its
successful partnership with CDSC. This year the marine control
systems research at CDSC that was behind our previously successful
ship motion control system development was focussed on the
development of an active-adaptive control architecture for our line
of ship roll gyrostabilisers. The work carried out by CDSC has
resulted in a more robust control system with improved motion
attenuation capability. These developments will have real
operational benefits for our products under development. As a
result of this work we are in the process of obtaining both
Australian and International patents.”
Paul SteinmannManaging Director Halcyon International,
Australia
CFW Hamilton Jet & Co., New Zealand“Hamilton Jet was seeking
to extend the features of its integrated water jet control system
to include a motion controller for vessels that perform operations
at low speeds. CDSC designed a control architecture with a
dual-mode control, proposed a procedure for extracting key response
parameters from simple trials to assist in the developed an
automatic control tuning.
Within one year of starting the project with CDSC, Hamilton Jet
was able to run trials using the first prototype version of the
system. Also, the estimation and automatic control tuning features
incorporated in the system will reduce significantly the control
commissioning time.”
Mike MeadeDevelopment Manager – Controls CfW Hamilton Jet &
Co., New Zealand.
Norwegian Offshore Consortium (STX Europe Offshore, Scana Volda
AS, Brunvoll AS, Offshore Simulator Centre—OSC)
“The OSC is a world leader in virtual simulation of offshore
operations. The Norwegian Offshore Consortium required assistance
to select methods for rapid model prototyping and station keeping
control design and tuning within a training simulation environment.
In 2009, CDSC proposed system identification methods to extract
vessel dynamic models from computational fluid dynamic data. In
addition, a station keeping control system for a simulator was
designed.
Using the methods proposed by CDSC, the Norwegian offshore
consortium is now able to cut down the time required to incorporate
models of new vessels and implement control in their training
simulators.”
Dr Svein Peder BergManager, Modelling and Simulation Offshore
Simulator Centre AS Norway
2. OUTREACH TO SCHOOLS AND UNDERGRADUATE STUDENTSSince its
inception, CDSC has made a special effort to interact with students
in local and international schools and students engaged in
undergraduate courses. This has been aimed at enthusing students
with the idea of pursuing careers in science or engineering.
Beginning in 2008, CDSC participated in the University of
Newcastle Industrial Scholarship Scheme (UNISS). Under this scheme,
undergraduate students receive a yearly stipend. In return they are
required to spend 10 weeks per year working with one of the
sponsoring companies.
In 2008, a first year student, Hal Cooper, was accepted into a
scholarship place funded by CDSC. He spent his
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ARC Centre of Excellence for Complex Dynamic Systems and
Control18
2008/2009 employment contributing to two CDSC projects, namely,
a virtual laboratory for school students and modelling of a
hospital emergency department. Hal Cooper is an exceptionally
gifted student and plans to spend a part of his University training
at a University in the United States.
In 2009, it was decided to bring a second student, Mr David
ferris, into the UNISS program with part funding from CDSC. David
is a gifted young person. He actually completed all of his High
School studies at the age of 14. He has just completed first year
of a joint Electrical Engineering/Mathematics degree at the
University of Newcastle and is still only 15 years old!
During the 2009/2010 university vacation period, David joined
CDSC and contributed to our Virtual Laboratories for Control System
Design project (See Research Projects section C of this report).
Specifically, David joined a team comprising 4 other engineers and
researchers (Graham Goodwin, Galina Mirzaeva, Adrian Medioli and
frank Sobora) to develop a new virtual laboratory aimed at teaching
principles of Wind Power Generation. We anticipate that this
laboratory will be completed and available by June 2010. Some
figures showing the user interface to the Audio Signal Processing
and Wind Power packages of the virtual laboratory are given in
figure (a) and figure (b).
Another outreach activity in 2009 was a visit that the Director,
(Graham Goodwin) made in October 2009. Graham was asked to give a
Plenary Address at the 8th IfAC Symposium, on Advances in Control
Education in Kumamoto, Japan. During this visit he also gave a talk
to high school students in Japan. His talk had the title “The
Disappearance of Traditional Boundaries in Science”. This talk
focussed on some of the challenges facing the world and was aimed
at interesting high school students in a career in science or
engineering.
figure (a): Audio Quantization Virtual Laboratory
figure (b): Wind Power Virtual Laboratory
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2009 ANNUAL REPORT 19
A number of courses and workshops were organized during the
year. Details are:
n David Allingham chaired the organising committee of the Third
Annual ASEARC Research Conference while Peter Howley was the
Technical Chairman (Teaching Sessions) and John Rayner was
Technical Chairman (Modelling Sessions). This Conference was held
at the University of Newcastle in December 2009.
n Jon Borwein presented “Ten Lectures on Variational Approaches
to Minimization Problems” in the IMA 009 Summer Program for
Graduate Students on The Mathematics of Inverse Problems,
University of Delaware, June 29 to July 3, 2009.
n Andrew fleming together with K. Leang (University of Nevada,
Reno), Q. Zou (Iowa State) and L. Pao (University of Colorado,
Boulder), organized a workshop on “Advances in Nanopositioning and
Scanning
Probe Systems” at the American Control Conference which was held
in St Louis in July. The workshop was attended by more than 60
participants and comprised three sessions consisting of 18
papers.
n Minyue fu organized the International Workshop on Networked
Control Systems, held in Shenzhen, China, 19-20 December, 2009.
n Graham Goodwin, Julio Braslavsky, Tristan Perez and James
Welsh presented an industrial short course to ResMed in Sydney from
7-9 January 2009. This short course was tailored to ResMed’s
requirements.
n Kerrie Mengersen presented three 3-day short courses on
Bayesian Statistics, to general audiences in Brisbane and Sydney,
and to a specific audience at the Cancer Council Queensland. In
collaboration with Dr Darfiana Nur, she also presented a 5-day
course on the same topic in Surabaya, Indonesia. Kerry also
developed and presented a 5-day
course on meta-analysis in ecology to an international audience
at NESCent, Duke University, USA.
n Reza Moheimani co-organized a two-day “Workshop on Dynamics
and Control of Micro and Nanoscale Systems” at IBM Research in
Zurich, 10-11 December 2009.
n Tristan Perez presented a 3 day short course on identification
and control of marine systems at the University of Salento, Lecce
Italy in July as well as presenting a one day course on Optimal
Estimation at the Energy Division, Robotiker Tecnalia, Bilbao Spain
in July.
n CDSC staff were invited to present at special meetings
throughout the year:
– Greg Adams presented two talks on control and estimation at a
future Manufacturers forum at CSIRO, Sydney, October 2009.
– Graham Goodwin presented a talk on “Complex Systems” at a NSW
Trauma Collaborative meeting in Sydney, November 2009.
n CDSC held its annual retreat on 20 November with attendance of
all academic staff, general staff, postgraduate students, visitors
and representatives from industry.
Participants at the International Workshop on Networked Control
Systems held in Shenzhen, China
CDSC Retreat
CONfERENCES, COURSES AND WORKSHOPS 2009
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ARC Centre of Excellence for Complex Dynamic Systems and
Control20
SEMINARS 2009
30 JanuaryAuthor: Mr Paul Rippon The University of
NewcastleTitle: A CYNIC’S GUIDE TO LEARNING
26 February Author: Dr Jan Ostergaard Aalborg University
Denmark.Title: MULTIPLE-DESCRIPTION AUDIO CODING
6 MarchAuthor: Dr Hernan Haimovich School of Electronics
Engineering, Universidad Nacional de Rosario Argentina.Title:
COMPONENTWISE ULTIMATE BOUND COMPUTATION METHODS
20 MarchAuthor: Professor John Elie Sader Department of
Mathematics and Statistics, The University of Melbourne,
Australia.Title: QUANTITATIVE DYNAMIC AfM fORCE MEASUREMENTS IN
fLUID
26 MarchAuthor: Professor Peter fleming University of Sheffield
United Kingdom.Title: MANY CRITERIA DECISION MAKING IN CONTROL AND
SYSTEMS DESIGN
8 AprilAuthor: Professor Rick Middleton Hamilton Institute
National University of Ireland Maynooth, Co Kildare, Ireland.Title:
CHALLENGES fOR SYSTEMS & CONTROL RESEARCH fROM SYSTEMS
BIOLOGY
15 AprilAuthor: Ms Maureen Townley-Jones The University of
NewcastleTitle: “I HATE MATHS!” STUDENTS PERCEPTION Of MATHS AND
CHALLENGES Of TEACHING QUANTITATIVE COURSES
15 AprilAuthor: Dr Peter Howley The University of
NewcastleTitle: REPORT ON EffORTS IN STATISTICAL EDUCATION
15 AprilAuthor: Associate Professor Olivier Thas Ghent
University BelgiumTitle: A SEMIPARAMETRIC APPROACH TO THE DETECTION
Of DIffERENTIALLY EXPRESSED GENES USING MICROARRAY DATA
24 AprilAuthor: Professor Murray Aitkin The University of
MelbourneTitle: NEW BAYESIAN METHODS fOR ASSESSING GOODNESS Of fIT
Of STATISTICAL MODELS
1 MayAuthor: Mr Ben Dean The University of NewcastleTitle:
APPLICATIONS Of THE GENERALIZED LAMBDA DISTRIBUTION
15 MayAuthor: Associate Professor Stefan Steiner University of
Waterloo CanadaTitle: TEACHING APPLIED STATISTICS USING A VIRTUAL
MANUfACTURING PROCESS
5 JuneAuthor: Mr Aurelio Salton School of Electrical Engineering
and Computer Science, The University of Newcastle, Australia.Title:
PREVIEW CONTROL fOR DUAL-STAGE ACTUATORS
5 JuneAuthor: Associate Professor Uschi Mueller-Harknett Texas
A&M University USATitle: SEMIPARAMETRIC REGRESSION WITH MISSING
RESPONSES
Research students and staff from the Centre and The University
of Newcastle as well as Australian and international visitors
participate in the Centre’s seminar series. Seminars presented in
2009 follow:
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2009 ANNUAL REPORT 21
11 JuneAuthor: Mr Rodrigo Carvajal School of Electrical
Engineering and Computer Science The University of NewcastleTitle:
ITERATIVE SUBSPACE EXPANSIONS fOR WIRELESS COMMUNICATIONS.
12 JuneAuthor: Mr Mashud Hyder School of Electrical Engineering
and Computer Science The University of Newcastle.Title: SPARSE
RECOVERY USING AN 10 APPROXIMATION
23 JuneAuthor: Dr Tobias Geyer Power Electronics Group The
University of Auckland New Zealand.Title: MODEL PREDICTIVE DIRECT
TORQUE CONTROL: ALGORITHMS, PERfORMANCE EVALUATION AND RECENT
DEVELOPMENTS.
1 JulyAuthor: Professor Dragan Nesic Department of Electrical
and Electronic Engineering The University of Melbourne.Title: A
UNIfIED APPROACH TO ANALYSIS AND DESIGN Of NETWORKED AND QUANTIZED
CONTROL SYSTEMS.
9 JulyAuthor: Mr Ricardo Aguilera School of Electrical
Engineering and Computer Science The University of Newcastle.Title:
MODEL PREDICTIVE CONTROL APPLIED TO MULTICELL CONVERTERS
10 JulyAuthor: Almah Saaid The University of NewcastleTitle:
DEMAND fORECAST WITH TIME SERIES DATA MINING APPROACH
25 July Author: Bob Gibberd The University of NewcastleTitle:
MONITORING HOSPITAL PERfORMANCE USING CONTROL CHARTS, CUSUM PLOTS
AND fUNNELL PLOTS
11 AugustAuthor: Dr Craig Smith Chief Executive Officer EOS
Space Systems Pty Limited, Australia.Title: AN OVERVIEW Of ELECTRO
OPTIC SYSTEMS ACTIVITIES IN SPACE SURVEILLANCE AND REMOTE CONTROL
WEAPON STATIONS
17 AugustAuthor: Mr Alain Yetendje Lemegni School of Electrical
Engineering and Computer Science, The University of
Newcastle.Title: fAULT TOLERANT CONSTRAINED CONTROL
28 AugustAuthor: Barrie Stokes The University of NewcastleTitle:
CONTINUOUS MAXENT DISTRIBUTIONS IN MATHEMATICA: A ‘PARAMETER-fREE’
APPROACH
31 AugustAuthor: Dr Craig Robinson Mercedes-Benz Research and
Development North America Palo Alto, California, USA.Title: CONTROL
AND SYSTEMS THEORY: fROM THEORY TO PRACTICE
24 SeptemberAuthor: Dr Louise Ryan Chief, CSIRO Mathematical
& Information SciencesTitle: COMPUTATIONALLY EffICIENT METHODS
fOR THE ANALYSIS Of SPATIALLY VARYING DISEASE RATES
25 SeptemberAuthor: Dr Jonathan Keith Queensland University of
TechnologyTitle: fINDING fUNCTIONAL REGIONS IN EUKARYOTIC
GENOMES
30 SeptemberAuthor: Associate Professor Gursel Alici, School of
Mechanical, Materials and Mechatronic Engineering, University of
WollongongTitle: “HOW REAL ARE ARTIfICIAL MUSCLES? BIO-INSPIRED
APPLICATIONS Of CONDUCTING POLYMER ACTUATORS”
9 OctoberAuthor: Associate Professor Gopalan Nair University of
Western AustraliaTitle: DETECTING TELECOMMUNICATIONS fRAUD USING TI
ME SERIES DATA MINING
3 NovemberAuthor: Professor David Matthews University of
Waterloo, CanadaTitle: CONfIDENCE INTERVALS AND REGIONS fOR
DIAGNOSTIC TEST LIKELIHOOD RATIOS
6 November Author: Professor Le Yi Wang Department of Electrical
and Computer Engineering Wayne State University Detroit, Michigan,
USA.Title: SYSTEM IDENTIfICATION AND STATE ESTIMATION WITH
QUANTIZED OBSERVATIONS
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ARC Centre of Excellence for Complex Dynamic Systems and
Control22
SELECTED HIGHLIGHTS 2009
n Professor Arie feuer, a frequent visitor to CDSC, was awarded
an Honorary Doctorate of the faculty of Engineering and Built
Environment. Professor feuer is a world-leading researcher in the
field of digital signal processing. His highly technical research
focuses on converting events from real-time to digital technology.
He is head of the Control and Robotics Laboratory at the Technion -
Israel Institute of Technology. Since 1988, Professor feuer has
spent two to three months each year working at the University of
Newcastle.
n The research paper entitled “Sensorless Vibration Suppression
and Scan Compensation for Piezoelectric Tube Nanopositioners” by
Andrew fleming and Reza Moheimani, was listed by ISI as one of the
top 1% cited papers in Engineering during 2009.
n Julio Braslavsky gave an invited plenary lecture at the 13th
Workshop on Information Processing and Control (RPIC 2009), held at
the National University of Rosario, Argentina, 16 to 18 September
2009.
n Reza Moheimani was a recipient of the 2009 IEEE CSS Control
Systems Technology Award for outstanding contributions to
nanopositioning for microelectromechanical systems (MEMS)-based
storage and other applications. The award was shared with IBM
Research scientists from Zurich.
n Reza Moheimani was also awarded an ARC future fellowship.
n Tristan Perez received the Newcastle Innovation Rising Star
Award in recognition of outstanding early career achievements in
research and innovation. With the prize Tristan Perez established a
new division of Newcastle Innovation: “Advanced Control and System
Dynamics” (www.ac-sd.com). This company provides research and
consultancy services to industry.
Professor Arie feuer
n Cristian Perfumo commenced a PhD jointly with CDSC and CSIRO.
See the Postgraduate Students section of this report.
n Peter Howley continues as Co-Chair of the Statistical
Education Section of the Statistical Society of Australia, Inc.
(SSAI)
n Eric Beh continues as President of the NSW Branch of the
Statistical Society of Australia, Inc.
n T. Li, M. fu, L. Xie and J. Zhang won the best Best Paper
Award at the Asian Control Conference, September 2009, Hong Kong,
for the paper entitled “Distributed Consensus of Undirected
Networks With finite-Level quantization”.
n Minyue fu presented a Plenary Address at the 7th IEEE
International Conference on Control and Automation, Christchurch,
9-11 December 2009.
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RESEARCH PROGRAMS
09
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ARC Centre of Excellence for Complex Dynamic Systems and
Control24
Program Goals:
The partnerships between researchers and industry enable
reciprocal transfer of knowledge and new ideas of great potential
impact on the community and economy. This Program encompasses
several research projects motivated by and in collaboration with
industrial partners. The main underlying theme of these projects is
the application of advanced control and optimisation techniques to
maximise asset utilisation and production in selected industrial
processes of significant complexity. The complexity of the dynamics
of such processes arise from factors including model errors,
unknown disturbances, nonlinearities, distributed parameter
systems, elements of Human-Machine Interaction and hybrid (Discrete
and Continuous State) components. Expected outcomes of the Program
include high quality research solutions ad human resources tailored
to the needs of Australian industry.
A.1 OPTIMISATION BASED OPERATOR GUIDANCE SCHEMES (BHP –
BILLITON)
Leader: Julio Braslavsky
Researchers: Katrina Lau Graham Goodwin
Industrial Collaborators: Arthur Maddever (Resource Business
Optimisation, BHP-Billiton)
A.1.1 Sferics Reduction in Electromagnetic Mineral
Exploration
Researchers: Katrina Lau Julio Braslavsky Graham Goodwin
This is a joint project with BHP-Billiton Exploration and Mining
in Perth.
A. INDUSTRIAL CONTROL AND OPTIMISATION
Julio BraslavskyProgram Leader
Tristan PerezDeputy Program Leader
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2009 ANNUAL REPORT 25
The aim of this industry project is the reduction of noise in
electromagnetic mineral exploration. The reduction of noise is
central to the improvement of signal to noise ratio for the
detection of deeper ore bodies. In the past few years, the focus
has been on the removal of sferics noise (electromagnetic noise
originating from lightning storms) from measurements acquired using
coil-based sensors. This work resulted in the development of a
single, unbiased model for broadband (4Hz –1kHz) multinode noise
cancellation.
In September, a paper on errors-in-variables techniques with
application to mineral exploration was accepted by Automatica. The
paper describes a model estimation algorithm which exploits
non-stationarity. The algorithm is successfully applied to model
estimation for sferics noise cancellation.
This year, the focus of the project has been broadened to
include other types of sensors such as SQUIDs and total field
sensors. Another problem which is currently being considered is the
removal of powerline interference from the measured responses. The
fundamental (50Hz) component or this interference is particularly
difficult to remove because it is characterised by a broad peak at
50 Hz. The width of the peak implies that the effectiveness of a
simple notch filter is limited as the noise cannot be removed
without also removing a significant part of the signal. The broad
peak is caused by variations in the frequency, amplitude and phase
of the waveform, and so, adaptive noise cancellation techniques are
being investigated.
A.1.2 Co-generation at WestVAMP
Project Leader: Greg Adams
Researchers: Graham Goodwin Tommy Gravdahl (Norway) Alejandro
Rojas
This project investigates improvements to the control for the
Westcliff Vent Air Methane Project facility near Appin, NSW. The
details are subject to a confidentiality agreement, but overall the
facility aims to generate power from the methane that is present in
air vented from underground coal mines. In 2009, a first-principles
simulation model was developed, and various control improvements
were tested using this model.
figure 1: Graph illustrating the time-variation of the frequency
of the fundamental component of the powerline interference. The
first cycle of the data is subtracted from subsequent cycles to
remove the response (consecutive cycles shown in different
colours). The residual signal during the nth is then dominated by
the difference in the powerline interference during the n-th and
first cycle. Variations in the frequency show up as beats.
figure 2: Power spectral density of the noise and interference
at three locations. The broad peak at 50 Hz is clearly visible.
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ARC Centre of Excellence for Complex Dynamic Systems and
Control26
A.2 INTEGRATED MINE PLANNING (BHP – BILLITON)
A.2.1 Estimation of Commodity Price Modelling
Researchers: Graham Goodwin Tristan Perez Boris Godoy
The major focus of commodity price modelling is to develop
algorithms for parameter estimation. Commodity price modelling is
normally approached in terms of structural time-series models, in
which the different components (states) have a clear financial
interpretation. We have developed two different algorithms based on
the Maximum-likelihood approach.
In 2009, we took a first step and looked at multi-commodity
price models. We analysed the co-integration of copper (Cu) and
aluminum (Al) and found a linear model that describes how the
increment of copper spot price relates to the increment of Al spot
price. Using this model, we then proposed a novel model structure,
which extend the Schwartz-Smith structural time-series models.
for 2010, we will analyse the properties of the proposed
multi-commodity model and will attempt to extend it to 3
commodities.
A.2.2 Discrete Event Simulation Modelling of Open Pit Mine
Shovel and Truck Operations
Researcher: Meimei Zhang
In open pit mining operations, trucks and shovels are commonly
used to move material from production faces to dumping sites, such
as waste dumps, stockpiles and processing plants. The truck-shovel
capacity can be a bottleneck to the mine productivity, in which
case the efficient utilization of truck-shovel infrastructure is
critical to profitable operation. Mine management must therefore
determine what the most capital efficient and effective
truck-shovel configuration will be for their operation in each
phase of pit development. Work in 2009 was focused on studying the
performance of truck-shovel operation at open pit mines by applying
discrete event simulation (DES) technology to provide analysis of
bottlenecks and understanding of effects of changes in fleet size
on marginal productivity.
This work began by simulating the operation of a hypothetical
truck-shovel system and then extended to simulate a real
truck-shovel operation at BHP Billiton’s Mt Keith open pit nickel
mine using DES. A simplified DES model for the Mt Keith open pit
mine has been developed using a commercial simulation tool –
ExtendSim 7. In this DES model, we consider randomness in truck
payload tonnage, truck spotting and dumping time, and shovel
loading duration. We take into account disturbances on shovels and
trucks due to any planned and unplanned breaks. We also account for
the complexity of truck haulage from multiple material sources to
multiple dumping sites.
This work demonstrates that DES is an appropriate technology
which can be applied to simulate truck-shovel operations with
complex configurations and frequent operational disturbances.
figure 3: Residuals and their autocorrelation for a model that
relates linearly the increment of log spot price of copper to the
increment of log spot price of aluminum.
figure 4: Historical data of Aluminum (Al) and Copper log spot
price from 1991 to 2007
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2009 ANNUAL REPORT 27
figure 5: The screen snapshot of the simplified DES model of the
truck-shovel operation at Mt Keith. This DES model considers
randomness in truck payload tonnage, truck spotting and dumping
time, and shovel loading duration. The model accounts for
disturbances on shovels and trucks due to any planned and unplanned
breaks, and the complexity of truck haulage from multiple material
sources to multiple dumping sites.
figure 6: Experimental results on truck fleet sizes vs
productivity. When the truck fleet is undersized and trucks are the
bottleneck of the truck-shovel operation, the productivity can be
increased by increasing the truck fleet capacity. In this
simplified system, the level of congestion at the shovels increases
as the number of trucks increases, which reduces marginal
productivity gains.
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ARC Centre of Excellence for Complex Dynamic Systems and
Control28
A.3 NEXT GENERATION MODEL- BASED CONTROL TOOLS (MATRIKON)
A.3.1 Next Generation Model Based Control Tools for CPO
Researchers: Greg Adams Graham Goodwin Adrian Medioli Maria
Seron Richard Thomas (Matrikon) James Welsh
The aim of this project is to deliver to Matrikon process
control tools that allow
n appropriate handling of complex, nonlinear and heterogeneous
processes;
n robust and easy-to-use system identification; and
n economic optimisation of process variables.
Progress in 2009 occurred in the following areas:
n Tools for economic optimisation, including data reconciliation
strategies and interfaces for steady-state optimisation of linear
and non-linear objectives, were integrated into CPO and tested on
several benchmark problems. A hill-climbing procedure was also
developed, allowing the true economic cost to be reduced even with
inaccurate models.
n Handling of non-linear processes via the appropriate
scheduling of multiple linear controllers was made possible by the
development of an MPC Scheduler.
n Matrikon continued developing a CPOmpc control solution
platform with a German company, which will involve the control of
non-linear systems via multiple linear regions.
n The derivation of MPC tuning parameters, from parameters of
existing (non-MPC) control, was investigated for single-input,
single-output systems.
n A robust MPC algorithm from Lovaas, Seron and Goodwin is under
investigation.
n A case study involving the control and optimisation of a
simulated nutating grinding mill was done, bringing together the
features of non-linear multivariable control, system identification
and economic optimisation.
future work on next-generation model-based control tools for CPO
will investigate:
n Derivation of MPC tuning parameters from parameters of
existing (non-MPC) control - this will be extended to MIMO
systems.
n Robust MPC will be implemented.
n A major case study is planned for 2010, which will bring
together the features of non-linear multivariable control, system
identification and economic optimisation into the control and
optimisation of a sugar mill.
A.3.2 Automated Downtime Cause Classifier for ProcessMORE
Researchers: Pat farragher Damien francois (Université
Catholique de Louvain, Belgium) Adrian Medioli
A second project involves the development of algorithms for
automatically generating downtime causes from alarm sets. CDSC work
in 2009 involved:
n The application of an adaptive classifier to four data sets,
to derive baseline performance using the simplest max-norm
classification measure.
n Study of the best classification and normalisation measures -
this showed that an angular separation classification measure,
combined with normalisation of the alarm data using the Term
frequency-Inverse Document frequency algorithm, seems most
appropriate for alarm data.
n Analysis of time taken to select a selected downtime cause,
comparing the time taken to do the current manual steps (selected
from all possible causes) with the time taken to choose from the
list of estimated causes.
Items to work on in 2010 include:
n Strategies for culling irrelevant data.
n Different handling of data pre and post-downtime.
n Implementing better algorithms in the adaptive centroid scheme
to try to improve performance.
n An initial implementation of the automated downtime cause
classifier.
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2009 ANNUAL REPORT 29
A.4 CSR SUGAR (INDUSTRIAL AffILIATE)
A.4.1 Constrained, Multivariable Control of an Integrated Sugar
Mill System for Economic Enhancement
Researchers: Greg Adams Brendan Burke (CSR Sugar, PhD student)
Graham Goodwin Rob Peirce (CSR Sugar) Alejandro Rojas
At CSR Sugar’s Pioneer Mill (near Ayr, North Queensland) a
co-generation plant has been installed - this plant uses waste cane
fibre (bagasse) from a number of mills to create steam for both
sugar milling and for electricity generation. If steam is used
efficiently in sugar milling, CSR can export 50MW of power to the
local grid, gaining an income stream from a waste product and
reducing carbon emissions.
figure 8: Improved brix control in evaporators (October
2009).
figure 7: Examples of poor brix control behaviour in evaporators
(August 2009).
This project aims to study energy and steam use in sugar
processing at Pioneer Mill. The multi-effect evaporators are core
units in the process; these units are where water is evaporated out
of the syrup most efficiently. Proper control of the sugar content
(brix) exiting the evaporators, and coordination of steam/energy
use with other sections of the mill, are essential to minimise
energy losses.
This project progressed significantly in 2009. As reported in
previous annual reports, the brix control used to suffer from
periodic disturbances (approximately 90 minute periods), as well as
quicker oscillatory disturbances (10 minute periods) caused by a
type of non-linear flow reduction through the outlet valves.
following on from 2008 work, the cause of the quicker oscillatory
disturbances has been confirmed as non-linear flow reduction
through the outlet valves. Strategies have been put in place to
reduce this non-linear flow effect in all brix controllers.
After much signal and system analysis, controller changes were
implemented
that were able to significantly reduce periodic oscillations.
figure 7 shows brix control in August 2009, and figure 8 shows brix
control in October 2009 (after controller changes were implemented)
- observe the a significant reduction in oscillations.
With the brix now being controlled closer to setpoint, the focus
is now on the mill optimisation task. Brendan Burke, as part of his
postgraduate work, is now looking at quantifying the effects of
different process operations (e.g. syrup heating) on overall steam
usage, in order to derive objective function sensitivities.
Modelling work on the process units has been done, and a multiple
objective function framework, considering steam conservation,
bagasse usage, and export power, is under investigation.
Work in 2010 will focus on collecting the above work together
into a mill optimisation problem, and solving this for Pioneer
Mill. This will ultimately form a practical mill optimiser for the
mill operators to consult on a day-to-day basis.
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ARC Centre of Excellence for Complex Dynamic Systems and
Control30
A.5 INTELLIGENT ELECTRICITY NETWORK PROJECTS
(ENERGYAUSTRALIA)
These projects are funded from the University of Newcastle’s
Centre for In-telligent Electricity Networks, a research centre set
up in the School of Electrical Engineering and Computer Science,
and funded by EnergyAustralia.
A.5.1 Fault Accommodation in Electricity Networks
Researchers: Julio Braslavsky Greg Adams Maria Seron
An important question in future electricity networks is the
enhancement of current (or development of new) voltage regulation
schemes at the levels of subtransmission and distribution networks,
to incorporate the following desirable characteristics:
Subtransmission network
n coordinated regulation, to avoid detrimental interactions such
as regulating schemes chasing one another (runaway effects and
oscillations)
n flexibility and robustness, to cope with dynamic load
variations and network reconfiguration
Distribution network
n integration of distributed generation, taking advantage of
real-time communication with distributed generation sources
n integration of distributed sensor/actuator networks, taking
advantage of increased real-time distributed voltage information
and control authority.
In 2009 we reviewed recent research work on voltage regulation
in face of distributed generation to assess its potential as an
area for future collaboration between EnergyAustralia and The
University of Newcastle. We have found that voltage regulation in
electricity networks with distributed generation is an area of
active development.
Most of the works reviewed aim to extend the ranges of
operation, as well as the coordination between on-load tap-changing
transformers, to improve voltage stability and compensate
perturbations induced by distributed generation. Advanced control
schemes, such as antiwindup and model predictive control (MPC), in
which voltage regulation is formulated as a constrained control
design problem, can optimally account for the limited ranges of
actuation and quantised output characteristic of on-load
tap-changing transformers, while integrating multivariable
information from distributed sensors.
A.5.2 Fault Detection in Electricity Networks
Researchers: Steve Mitchell James Welsh Jose De Doná
This project also started in late 2009. Project work will focus
on partial and localisation discharge monitoring in underground
cables and transformers.
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2009 ANNUAL REPORT 31
A.6 APPLICATION Of SYSTEM IDENTIfICATION TO PARAMETER ESTIMATION
IN THE POWER INDUSTRY (AURECON)
This project, being undertaken in conjunction with Aurecon, is
investigating methods of parameter estimation for synchronous
machines. Its aim is to provide validation for methods already in
use, to explore alternative approaches and to investigate ways of
providing error estimates for parameter values.
Our work to date has focused on standstill frequency response
(SSfR) modeling. Here, sinusoidal inputs over a range of
frequencies, 0.5 mHz to 1 kHz, are applied to the machine with the
resulting frequency responses recorded. Using this frequency
response data, parameters of an equivalent circuit model of the
machine are then estimated. from these parameters, time constants
are obtained which describe the machine’s response to events such
as faults, and how fast it can recover from such events. Time
constants for a particular machine are given in the table below.
Note that the manufacturer test data was supplied for the machine
prior to a major overhaul.
The time constants obtained from the SSfR tests are can be used
in specific power simulation packages to validate the machine
response for on-line step tests. This involves small step changes
applied to the voltage regulator, which results in changes to the
amplitude of the machine’s real and imaginary power when it is
under load (for example, when it is connected to the power
grid).
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ARC Centre of Excellence for Complex Dynamic Systems and
Control32
A.7 MARINE AND AEROSPACE SYSTEMS
Goals: Marine and aerospace systems are designed to perform
complex operations and missions. Vehicle motion control systems are
a fundamental component, and even an enabling factor for these
missions. The goal for this group of projects is to develop novel
tools for guidance, navigation, and motion control of marine and
aerospace vehicles with the aim of optimising reliability and
vehicle performance.
Project Participants:
Leaders: Tristan Perez; James Welsh
Researchers: Alejandro Donaire
Research Assistant: Pierre de Lamberterie
External Academic Collaborators: Thor fossen (NTNU, Norway)
Gianluca Ipoliti (Universidad de La Marche, Italy)
Industry Collaborators: Tony Armstrong (Austal Ships, Australia)
Svein Peder Berg (Offshore Simulator Centre, Norway) Robert Borret
(CfW Hamilton Jet & Co., New Zealand) Paul Steinmann (Halcyon
International Pty. Ltd., Australia) Brendan Williams (Boeing
Research and Technology Australia) francis Valentinis (DSTO
Maritime Platforms Division, Australia)
Visiting Students: Elias Revestido Herrero (University of
Cantabria, Spain) Jaap J. Nieuwenhuijsen (Eindhoven University, The
Netherlands) Joris Termaat (Eindhoven University, The
Netherlands)
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2009 ANNUAL REPORT 33
A.7.1 Marine Simulation Tools
Researchers: Tristan Perez Thor fossen (Norway), Gianluca
Ippoliti (Italy)
The Marine Systems Simulator (MSS) is an environment developed
to provide the necessary resources for rapid implementation of
mathematical models of marine systems with focus on control system
design. The platform adopted for the development of MSS is Matlab/
Simulink. Openness and modularity of software components have been
prioritised in the design, which enables a systematic reuse of
knowledge and results in efficient tools for research and
education. The software can be accessed at
www.marinecontrol.org
In 2009, we developed a new toolbox component for parametric
identification of fluid-memory models associated with the radiation
forces ships and offshore structures. Radiation forces are a key
component of force-to-motion models used in simulators, motion
control designs, and also for initial performance evaluation of
wave-energy converters. The software described provides tools for
preparing non-parametric data and for identification with automatic
model-order detection.
for 2010, we are extending the toolbox to incorporate functions
for model order reduction. This has application in modelling for
control system design.
A.7.2 Control of Marine Vessels with Water Jets (CFW Hamilton
Jet & Co., New Zealand.
Researchers: Tristan Perez Alejandro Donaire Robert Borret (New
Zealand)
In this project we are considering the problem of vessel motion
control at low speeds using water jets. This is part of an upgrade
of the current control systems of CfW-HJ.
In 2009, we designed a multi-mode control architecture, proposed
tests and system identification techniques to augment the system
with a auto-tuning capabilities. Hamilton Jet was able to run
trials on its first commercial version of the system in Sept
2009.
for 2010, we plan to improve the functionality of system by
making it adaptive to changes in the sea state, and we are moving
to motion control at high speeds.
A.7.3 Experiment Design and Identification of Nonlinear
Manoeuvring Models of Marine Vessels (Austal Ships Australia)
Researchers: Tristan Perez Elias Herrero (Student, Spain) Tony
Armstrong (Austal Ships)
The mathematical models of marine vessels can be obtained from
first principle or analytical modelling. The parameters of the
model, however, often need to be estimated from full-scale trials.
The ability of an estimation method to produce good estimates of
the parameters depends on how much information about the dynamics
of the system is contained in the data, which in turn depends on
the experiment performed. Hence, the design of experiments is of
paramount importance to obtain accurate model parameters and to
reduce the time to perform experiments. Some of the hydrodynamic
phenomenon involved in ship dynamic response are too complex for
analytical modelling. Therefore, parts of the model structure may
also be determined based on analysis of experimental data.
In 2009, we develop a new identification scheme based on two
steps that can be applied to full-scale trial data. The first step
uses regression modes and statistical hypothesis testing to
determine the model structure and initial
parameter estimates. The second step uses a nonlinear prediction
error method with the unscented Kalman filter to refine the initial
parameter estimates obtained in the first step. The proposed
estimator has been tested successfully with simulated data
generated from a high-fidelity model of Austal’s novel 137m
trimaram ferry.
for 2010, we are planing to use the proposed estimator with full
scale trial data of new 100m trimaran recently constructed by
Austal.
A.7.4 Gyroscopic Stabilisation of Marine Platforms (Halcyon
International, Australia)
Researchers: Tristan Perez Paul Steinmann (Halcyon
International)
The use of gyroscopic effects for the roll stabilisation of
marine structures was proposed over 100 years ago. This approach
was very effective, but limited control and large sizes hindered
further developments. In recent years there has been significant
interest in revitalising gyrostabilisers due to improvements in
materials, bearings, and lubricants, which have contributed to fast
spinning devices and size reduction. This project aims at
supporting Halcyons development of high performance
gyrostabilisers.
In 2009, we followed our previous work on adaptive control of
gyrostabilisers, and proposed a multi-mode control architecture
with the aim of augmenting the system with a fault-tolerance
capability. The new controller combines three different controllers
that make used of varying levels of information related to vessel
and gyro-actuator motion.
for 2010, we are planning to perform experiments on full-scale
gyro stabiliser on board of Halcyon’s control testing vessel. We
will also prepare a provisional patent application based on the new
controller.
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ARC Centre of Excellence for Complex Dynamic Systems and
Control34
A.7.5 Adaptive and Fault-Tolerant Control of Underwater
Vehicles
Researchers: Tristan Perez Alejandro Donaire
In this project we look at novel motion control strategies for
underwater vehicles. We consider the joint design of motion control
and control allocation, and the handling of actuator faults within
this scheme.
In 2009, we have proposed a new control system design
methodology for over-actuated open-frame vehicle positioning
controllers, which incorporate a control allocation function. The
proposed control system uses a mapping that translates the actuator
force constraint set to a set in the generalised force space (force
for degrees of freedom being controlled.) This novel problem
formulation allows the designer to consider a constrained motion
control strategy with unconstrained control allocation. Hence, the
computational complexity of the controller is significantly
reduced. We have also been able to demonstrate stability of
closed-loop control system analytically, and this has lead to
closed form control tuning rules for robust performance.
for 2010, we are planning to extend the proposed control design
method to under actuated vehicles. DSTO – Maritime Platforms
Division will be joining the project in 2010 to test the proposed
control system on one of their research underwater vehicles.
figure 9: Uninhabited underwater vehicle motion control system
with control allocation.
figure 10: Performance of an underwater vehicle position
regulation controller in ocean current
and position set point change.
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2009 ANNUAL REPORT 35
A.7.6 Ship Motion Control for Offshore Marine Operations in
Training Simulators (Offshore Simulator Centre AS, Norway)
Researchers: Tristan Perez Alejandro Donaire Svein PederBerge
(Norway)
Ship training simulators are used to improve crew efficiency and
thus safety of marine operations. At the core of any
virtual-reality simulator lays a mathematical model that describes
the ship dynamic response to control and environmental forces. When
a new vessel is to be incorporated into a simulator, different type
of data of the vessel may be available to be used for system
identification to extract a mathematical model for dynamic
response.
In 2008, CDSC evaluated various identification methods for
obtaining parametric models of vessel response based on frequency
domain data computed by hydrodynamic codes, and made
recommendations to the Offshore Simulator Centre AS as to which
method to use for rapid identification of vessel dynamic
response.
In 2009, we developed a position hold controller with
auto-tuning and a novel adaptive wave filter capability. CDSC
personnel has lodged a provisional patent application of an
enhanced version of the wave filter, which can be used in real
control implementation of dynamic positioning of offshore
vessels.
for 2010, we plan to test the implementation of proposed
controller and wave filter in the OSC simulator.
figure 11: Simulation of wave filter performance for a vessel
under positioning control. The wave filter is switched on at 500s,
and the vessel is moved forward by 10m at 600s.
(a) shows the measured and wave-filtered surge position.
(b) shows the measured and wave-filtered surge velocity.
(c) shows the surge force generated by the controller.
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ARC Centre of Excellence for Complex Dynamic Systems and
Control36
A.7.7 Evaluation of Robust Autonomy for Uninhabited Airborne
Systems (UAS) (Boeing Research & Technology Australia)
Researchers: Tristan Perez Alejandro Donaire Brendan Williams
(BR&TA)
Robust autonomy (RA) for uninhabited airborne systems (UAS)
refers to the ability of the vehicle to either continue operating
in the presence of faults or safely shut down. To achieve this
characteristic, an UAS has to incorporate mechanisms that augment
the safety and reliability of its guidance, navigation,
communication, and control (GNCC) systems. This project seeks the
development of various measures of performance and method that
would yield a figure of merit to assess robust autonomy. This
figure of merit is related to the reliability of the
fault-tolerant-control system. The purpose of such figure is the
evaluation of UAS flight control and guidance system performance in
terms of simulation scenarios under the presence of faults and
environmental conditions relevant the mission of the UAS.
In 2009, we proposed methodology to specify the mission-specific
requirements for fault-tolerant GNCC system of AUS. We also
proposed a method to quantify robust autonomy of UAS. Based on
mission-vehicle specific performance criteria, we define a utility
function, which can be evaluated using simulation scenarios for an
envelope of environmental conditions. The result of these
evaluations is a figure of merit for operational effectiveness. The
procedure was then augmented to consider faults, which leads to a
figure of merit related to robust autonomy. The proposed figures of
merit are interpreted within a probability framework. The objective
of these figures of merit is to use them at both vehicle
development stage and with hardware-in-the-loop testing at
certification stage. In addition, performance indices based on
dynamic and geometric tasks associated with vehicle manoeuvring
problems were proposed, and an example of a two-dimensional fly
scenario was considered to illustrate the use of the proposed
evaluation methods.
for 2010, we plant to extend the proposed performance criteria
to 3D flight scenarios and demonstrate the application of figure of
merit based on a real UAS mission. This extension will be presented
to the airtraffic regulation authorities.
A.7.8 A UAS Simulator for Testing Fault-Tolerant Flight Control
and Guidance Systems (Boeing Research & Technology
Australia)
Researchers: Tristan Perez Alejandro Donaire Brendan Williams
(BR&TA) Jaap Nieuwenhuijsen (Student, The Netherlands)
In this project, we are developing a flight simulator for rapid
UAS model prototyping and testing of fault-tolerant flight control
and guidance systems. The simulator includes linear and nonlinear
aerodynamic models of winged UAS, and sensors and actuators in
healthy and faulty modes. The simulator is being developed in
Matlab/Simulink.
In 2009, we proposed a modular simulator structure and completed
the first stage of the simulator implementation for the nominal
airborne system (faultless case.) We implemented a non-linear model
of a small UAS from the literature, design a basic altitude
controller and were able to simulate basic flight manoeuvres of
vertical plane motion (heave and pitch). The Matlab implementation
of the simulator was by a visiting student, J.J. Nieuwenhuijsen,
and form part of a project work towards a MSc thesis.
for 2010, we plan to incorporate into the simulator the ability
to select various types of actuator and sensor faults, so we can
test fault-tolerant flight control and guidance systems.
figure 12: Region of acceptable performance for the geometric
task of a given trajectory (shaded area) and sample geometric
errors (characterised by the white area on the circles centred at
the vehicle).
figure 13: Region of acceptable performance for the dynamic task
of a given trajectory and sample dynamic errors (characterised by
the white area on the circles centred at the vehicle).
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2009 ANNUAL REPORT 37
A.7.9 Identification of Dynamic Models for Uninhabited Airborne
Systems (UAS) (Boeing Research & Technology Australia)
Researchers: Tristan Perez James Welsh Pierre de Lamberterie
Alejandro Donaire Elias Herrero (Student, Spain)
In order to design a fault-tolerant flight control and guidance
systems (fT-fCG) and to implement simulations to test the
performance of the aircraft, one can adopt a grey-box approach for
rapid prototyping of an aircraft model. That is, postulate a-priori
a model structure based on physical considerations, and then use
data from experiments to extract information related to the
parameters, namely, parameter estimation. Different estimators
(algorithms) produce estimates (value of the parameters) with
different statistical properties. The choice of the estimator
depends on its accuracy, computational, and robustness with
respect. In this project, we are investigating the use of different
parameter estimation methods for UAS dynamic models.
In 2009, we proposed a method for the estimation of thrust model
parameters of UAS using specific flight tests. Particular tests are
proposed to simplify the estimation. The estimation method
considered is based on three steps. The first step uses a
regression model in which the thrust is assumed constant. This
allows us to obtain biased initial estimates of the aerodynamic
coefficients of the surge model. In the second step, a robust
nonlinear state estimator is implemented using the initial
parameter estimates, and the model is augmented by considering the
thrust as random walk. In the third step, the estimate of the
thrust obtained by the observer is used to fit a polynomial model
in terms of the propeller advanced ratio.
figure 15: Sampling characteristics of a 3-step estimator
applied to an aircraft thrust model. Histograms of estimated thrust
coefficients based on 100 Monte-Carlo simulations.
figure 14: Performance of the UKf state estimator for an
aircraft thrust during a self-oscillation test in pitch.
We considered a numerical example based on Monte-Carlo
simulations to quantify the sampling properties of the proposed
estimator given realistic flight conditions.
for 2010, we are planning to apply the estimator de flight test
data from BR&TA’s testing UAS, and also to extend the
identification method to the all the vehicle degrees of
freedom.
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ARC Centre of Excellence for Complex Dynamic Systems and
Control38
Program Goals:
Many technical processes and products in the area of mechanical
and electrical engineering show an increasing integration of
mechanics with electronics and information processing. This
integration is between the components (hardware) and the
information-driven functions (software), resulting in integrated
systems called mechatronic systems. The development of mechatronic
systems involves finding an optimal balance between the basic
mechanical structure, sensor and actuator implementation, automatic
digital information processing and overall control, and this
synergy results in innovative solutions. The practice of
mechatronics requires multidisciplinary expertise across a range of
disciplines such as: mechanic
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