Associate Professor Adrian Wills

Associate Professor Adrian Wills

Associate Professor

School of Engineering (Mechatronics)

Career Summary

Biography

Bio
I was born in Orange NSW and was awarded my B.E. (Elec.) and Ph.D. degrees from The University of Newcastle, Australia, (Callaghan Campus) in May 1999 and May 2003, respectively. Since then, I have held postdoctoral research positions at Newcastle and spent three years working in industry. The focus of my research is in the areas of system identification and estimation. In July 2015, I returned to the University of Newcastle to lead the mechatronics engineering program.



Research Expertise
My research interests are focussed on Bayesian estimation of both parameter and state values based on measured data. This includes the fields of robotics and mechatronics where estimates of position and orientation together with estimates of the surrounding environment are crucial to mission success. 


Teaching Expertise
I deliver courses within the Mechatronics Engineering program at the University of Newcastle. This includes delivery MCHA6100 and MCHA6300, which are Masters courses on Advanced Estimation and Optimisation, respectively.

Administrative Expertise
Since July 2015, I have been the program convenor for Mechatronics Engineering.


Collaborations
I have collaborated and published with Professor Lennart Ljung from Linköping University and Professor Thomas Schön from Uppsala University, Sweden. I have published and collaborated with Professor Will Heath, Dr Barry Lennox and Dr Guang Li from Manchester University, UK, and with Professor Bhushan Gopaluni from University of British Columbia, Canada. Locally, I have collaborated and published with Professor Brett Ninness, Professor Reza Moheimani, Professor Steve Weller and Professor Andrew Fleming all from University of Newcastle, Australia.

Qualifications

  • PhD, University of Newcastle
  • Bachelor of Engineering (Honours), University of Newcastle

Keywords

  • Bayesian machine learning
  • data fusion
  • embedded real-time microprocessors
  • model predictive control
  • optimisation
  • real-time operating systems
  • state estimation
  • system identification

Fields of Research

Code Description Percentage
010499 Statistics not elsewhere classified 10
090699 Electrical and Electronic Engineering not elsewhere classified 70
091399 Mechanical Engineering not elsewhere classified 20

Professional Experience

UON Appointment

Title Organisation / Department
Associate Professor University of Newcastle
School of Engineering
Australia

Academic appointment

Dates Title Organisation / Department
1/01/2007 - 1/12/2009 Fellow - APD ARC (Australian Research Council)

Membership

Dates Title Organisation / Department
IFAC Technical Committee Member - Modelling, Identification and Signal Processing, TC 1.1. IFAC Technical Committee
Australia
IEEE Technical Committee Member - System Identification and Adaptive Control IEEE
Australia
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Publications

For publications that are currently unpublished or in-press, details are shown in italics.


Chapter (2 outputs)

Year Citation Altmetrics Link
2010 Wills AG, Ljung L, 'Wiener system identification using the maximum likelihood method', Block-oriented Nonlinear System Identification, Springer, Berlin 89-110 (2010) [B1]
Citations Scopus - 8
2007 Wills AG, Heath WP, 'Interior-point algorithms for nonlinear model predictive control', Assessment and Future Directions of Nonlinear Model Predictive Control, Springer, Berlin 207-216 (2007) [B1]
DOI 10.1007/978-3-540-72699-9_16
Citations Scopus - 4Web of Science - 4

Journal article (32 outputs)

Year Citation Altmetrics Link
2019 Hendriks JN, Jidling C, Schön TB, Wills A, Wensrich CM, Kisi EH, 'Neutron transmission strain tomography for non-constant stress-free lattice spacing', Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms, 456 64-73 (2019) [C1]
DOI 10.1016/j.nimb.2019.07.005
Co-authors Erich Kisi, Christopher Wensrich
2019 Hendriks JN, Wensrich CM, Wills A, Luzin V, Gregg AWT, 'Robust inference of two-dimensional strain fields from diffraction-based measurements', Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms, 444 80-90 (2019) [C1]
DOI 10.1016/j.nimb.2018.11.019
Co-authors Christopher Wensrich
2019 Hendriks J, Gregg A, Wensrich C, Wills A, 'Implementation of traction constraints in Bragg-edge neutron transmission strain tomography', STRAIN, 55 (2019) [C1]
DOI 10.1111/str.12325
2019 Fleming AJ, Ghalehbeygi OT, Routley BS, Wills AG, 'Scanning Laser Lithography With Constrained Quadratic Exposure Optimization', IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 27 2221-2228 (2019) [C1]
DOI 10.1109/TCST.2018.2836910
Co-authors Andrew Fleming
2018 Jidling C, Hendriks J, Wahlström N, Gregg A, Schön TB, Wensrich C, Wills A, 'Probabilistic modelling and reconstruction of strain', Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms, 436 141-155 (2018) [C1]
DOI 10.1016/j.nimb.2018.08.051
Citations Scopus - 4Web of Science - 3
Co-authors Alexander Gregg, Christopher Wensrich
2018 Gregg AWT, Hendriks JN, Wensrich CM, Wills A, Tremsin AS, Luzin V, et al., 'Tomographic Reconstruction of Two-Dimensional Residual Strain Fields from Bragg-Edge Neutron Imaging', PHYSICAL REVIEW APPLIED, 10 (2018) [C1]
DOI 10.1103/PhysRevApplied.10.064034
Citations Scopus - 4Web of Science - 4
Co-authors Alexander Gregg, Christopher Wensrich, Mike Meylan, Erich Kisi
2016 Fleming AJ, Wills AG, Routley BS, 'Exposure Optimization in Scanning Laser Lithography', IEEE Potentials, 35 33-39 (2016) [C1]

© 2015 IEEE. In 1959, the integrated circuit (IC) was invented simultaneously by Jack Kilby of Texas Instruments and Robert Noyce of Shockley Semiconductor [Ki lby, 2000]. This de... [more]

© 2015 IEEE. In 1959, the integrated circuit (IC) was invented simultaneously by Jack Kilby of Texas Instruments and Robert Noyce of Shockley Semiconductor [Ki lby, 2000]. This development has been considered one of mankind's most significant innovations.

DOI 10.1109/MPOT.2016.2540039
Co-authors Andrew Fleming
2015 Kok M, Dahlin J, Schön TB, Wills A, 'Newton-based maximum likelihood estimation in nonlinear state space models', IFAC-PapersOnLine, 48 398-403 (2015)

© 2015 Maximum likelihood (ML) estimation using Newton's method in nonlinear state space models (SSMs) is a challenging problem due to the analytical intractability of the lo... [more]

© 2015 Maximum likelihood (ML) estimation using Newton's method in nonlinear state space models (SSMs) is a challenging problem due to the analytical intractability of the loglikelihood and its gradient and Hessian. We estimate the gradient and Hessian using Fisher's identity in combination with a smoothing algorithm. We explore two approximations of the log-likelihood and of the solution of the smoothing problem. The first is a linearization approximation which is computationally cheap, but the accuracy typically varies between models. The second is a sampling approximation which is asymptotically valid for any SSM but is more computationally costly. We demonstrate our approach for ML parameter estimation on simulated data from two different SSMs with encouraging results.

DOI 10.1016/j.ifacol.2015.12.160
Citations Scopus - 5
2013 Fleming AJ, Ninness B, Wills A, 'Recovering the spectrum of a low level signal from two noisy measurements using the cross power spectral density', Review of Scientific Instruments, 84 (2013) [C1]
DOI 10.1063/1.4815982
Co-authors Andrew Fleming, Brett Ninness
2013 Ninness B, Wills A, Mills A, 'UNIT: A freely available system identification toolbox', Control Engineering Practice, 21 631-644 (2013) [C1]
DOI 10.1016/j.conengprac.2012.10.007
Citations Scopus - 18Web of Science - 14
Co-authors Brett Ninness
2013 Wills A, Schön TB, Ljung L, Ninness B, 'Identification of Hammerstein-Wiener models', Automatica, 49 70-81 (2013) [C1]

This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein-Wiener model structures. A central aspect is that a very general si... [more]

This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein-Wiener model structures. A central aspect is that a very general situation is considered wherein multivariable data, non-invertible Hammerstein and Wiener nonlinearities, and colored stochastic disturbances both before and after the Wiener nonlinearity are all catered for. The method developed here addresses the blind Wiener estimation problem as a special case. © 2012 Elsevier Ltd. All rights reserved.

DOI 10.1016/j.automatica.2012.09.018
Citations Scopus - 129Web of Science - 104
Co-authors Brett Ninness
2012 Wills AG, Ninness BM, 'Generalised Hammerstein-Wiener system estimation and a benchmark application', Control Engineering Practice, 20 1097-1108 (2012) [C1]
Citations Scopus - 31Web of Science - 24
Co-authors Brett Ninness
2012 Wills AG, Knagge GS, Ninness BM, 'Fast linear model predictive control via custom integrated circuit architecture', IEEE Transactions on Control Systems Technology, 20 59-71 (2012) [C1]
DOI 10.1109/TCST.2010.2096224
Citations Scopus - 63Web of Science - 48
Co-authors Brett Ninness
2012 Mills AJ, Wills AG, Weller SR, Ninness BM, 'Implementation of linear model predictive control using a field-programmable gate array', IET Control Theory and Applications, 6 1042-1054 (2012) [C1]
DOI 10.1049/iet-cta.2010.0739
Citations Scopus - 13Web of Science - 11
Co-authors Brett Ninness, Steven Weller
2011 Schon TB, Wills AG, Ninness BM, 'System identification of nonlinear state-space models', Automatica, 47 39-49 (2011) [C1]
DOI 10.1016/j.automatica.2010.10.013
Citations Scopus - 282Web of Science - 221
Co-authors Brett Ninness
2010 Ninness BM, Wills AG, 'Discussion on: 'generalised linear dynamic factor models: An approach via singular autoregressions'', European Journal of Control, 16 225-227 (2010) [C3]
Citations Scopus - 1
Co-authors Brett Ninness
2010 Ljung L, Wills AG, 'Issues in sampling and estimating continuous-time models with stochastic disturbances', Automatica, 46 925-931 (2010) [C1]
DOI 10.1016/j.automatica.2010.02.011
Citations Scopus - 29Web of Science - 23
2009 Wills AG, Ninness BM, Gibson S, 'Maximum likelihood estimation of state space models from frequency domain data', IEEE Transactions on Automatic Control, 54 19-33 (2009) [C1]
DOI 10.1169/tac.2008.2009485
Citations Scopus - 45Web of Science - 33
Co-authors Brett Ninness
2009 Fleming AJ, Wills AG, 'Optimal periodic trajectories for band-limited systems', IEEE Transactions on Control Systems Technology, 17 552-562 (2009) [C1]
DOI 10.1109/tcst.2008.2001375
Citations Scopus - 51Web of Science - 45
Co-authors Andrew Fleming
2008 Wills AG, Bates DR, Fleming AJ, Ninness BM, Moheimani SO, 'Model predictive control applied to constraint handling in active noise and vibration control', IEEE Transactions on Control Systems Technology, 16 3-12 (2008) [C1]
DOI 10.1109/tcst.2007.903062
Citations Scopus - 93Web of Science - 67
Co-authors Reza Moheimani, Brett Ninness, Andrew Fleming
2008 Fleming AJ, Wills AG, Moheimani SO, 'Sensor fusion for improved control of piezoelectric tube scanners', IEEE Transactions on Control Systems Technology, 16 1265-1276 (2008) [C1]
DOI 10.1109/tcst.2008.921798
Citations Scopus - 56Web of Science - 45
Co-authors Andrew Fleming, Reza Moheimani
2008 Hagenblad A, Ljung L, Wills AG, 'Maximum likelihood identification of Wiener models', Automatica, 44 2697-2705 (2008) [C1]
DOI 10.1016/j.automatica.2008.02.016
Citations Scopus - 145Web of Science - 122
2008 Wills AG, Ninness BM, 'On gradient-based search for multivariable system estimates', IEEE Transactions on Automatic Control, 53 298-306 (2008) [C1]
DOI 10.1109/TAC.2007.914953
Citations Scopus - 71Web of Science - 52
Co-authors Brett Ninness
2007 Heath WP, Wills AG, 'Zames-Falb multipliers for quadratic programming', IEEE Transactions on Automatic Control, 52 1948-1951 (2007) [C1]
DOI 10.1109/tac.2007.906233
Citations Scopus - 32Web of Science - 25
2005 Gibson S, Wills AG, Ninness BM, 'Maximum-likelihood parameter estimation of bilinear systems', IEEE Transactions on Automatic Control, 50 1581-1596 (2005) [C1]
DOI 10.1109/TAC.2005.856664
Citations Scopus - 65Web of Science - 52
Co-authors Brett Ninness
2005 Wills AG, Heath WP, 'Application of barrier function based model predictive control to an edible oil refining process', Journal of Process Control, 15 183-200 (2005) [C1]
DOI 10.1016/j.jprocont.2004.05.004
Citations Scopus - 12Web of Science - 8
2005 Heath WP, Wills AG, Akkermans JAG, 'A sufficient condition for the stability of optimizing controllers with saturating actuators', International Journal of Robust and Nonlinear Control, 15 515-529 (2005) [C1]
DOI 10.1002/rnc.1008
Citations Scopus - 36Web of Science - 25
2005 Wills A, Ninness B, Gibson S, 'On gradient-based search for multivariable system estimates', IFAC Proceedings Volumes (IFAC-PapersOnline), 16 832-837 (2005)

This paper addresses the design of gradient based search algorithms for multivariable system estimation. in particular, the work here considers so-called 'full parametrizatio... [more]

This paper addresses the design of gradient based search algorithms for multivariable system estimation. in particular, the work here considers so-called 'full parametrization' approaches, and establishes that the recently developed 'Data Driven Local Coordinate' (DDLC) methods can be seen as a special case within a broader class of techniques that are designed to deal with rank-deficient Jacobians. This informs the design of a new algorithm that, via a strategy of dynamic Jacobian rank determination, is illustrated to offer enhanced performance. Copyright © 2005 IFAC.

Citations Scopus - 7
Co-authors Brett Ninness
2005 Ninness B, Wills A, Gibson S, 'The University of Newcastle identification toolbox (Unit)', IFAC Proceedings Volumes (IFAC-PapersOnline), 16 838-843 (2005)

This paper describes a MATLAB-based software package for estimation of dynamic systems. A wide range of standard estimation approaches are sup- ported. These include the use of no... [more]

This paper describes a MATLAB-based software package for estimation of dynamic systems. A wide range of standard estimation approaches are sup- ported. These include the use of non-parametric, subspace-based and prediction- error algorithms coupled (in the latter case) with either MIMO state space or MISO polynomial model structures. A key feature of the software is the implementation of several new techniques that have been investigated by the authors. These include the estimation of non-linear models, the use of non-standard model parametrizations, and the employment of Expectation Maximisation (EM) methods. Copyright © 2005 IFAC.

Citations Scopus - 8
Co-authors Brett Ninness
2004 Wills AG, Heath WP, 'Barrier function based model predictive control', Automatica, 40 1415-1422 (2004) [C1]
DOI 10.1016/j.automatica.2004.03.002
Citations Scopus - 62Web of Science - 50
2004 VanAntwerp JG, Braatz RD, Heath WP, Wills AG, 'Discussion on: "Design of cross-directional controllers with optimal steady state performance"', European Journal of Control, 10 28-29 (2004)
DOI 10.3166/ejc.10.28-29
2002 Wills AG, Heath WP, 'Analysis of steady-state performance for cross-directional control', IEE Proceedings Control Theory and Applications, 149 433-440 (2002) [C1]
Citations Scopus - 10Web of Science - 7
Show 29 more journal articles

Conference (48 outputs)

Year Citation Altmetrics Link
2018 Balenzuela MP, Dahlin J, Bartlett N, Wills AG, Renton C, Ninness B, 'Accurate Gaussian Mixture Model Smoothing using a Two-Filter Approach', 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), Miami Beach, FL (2018) [E1]
Co-authors Brett Ninness
2018 Dahlin J, Wills A, Ninness B, 'Sparse Bayesian ARX models with flexible noise distributions', IFAC-PapersOnLine. Proceedings of the 18th IFAC Symposium on System Identification SYSID 2018, Stockholm, Sweden (2018) [E1]
DOI 10.1016/j.ifacol.2018.09.085
Citations Scopus - 1Web of Science - 1
Co-authors Brett Ninness
2018 Wills A, Yu C, Ljung L, Verhaegen M, 'Affinely Parametrized State-space Models: Ways to Maximize the Likelihood Function', IFAC-PapersOnLine. Proceedings of the 18th IFAC Symposium on System Identification SYSID 2018, Stockholm, Sweden (2018) [E1]
DOI 10.1016/j.ifacol.2018.09.170
Citations Scopus - 1
2018 Dahlin J, Wills A, Ninness B, 'Constructing Metropolis-Hastings proposals using damped BFGS updates', IFAC-PapersOnLine. Proceedings of the 18th IFAC Symposium on System Identification SYSID 2018, Stockholm, Sweden (2018) [E1]
DOI 10.1016/j.ifacol.2018.09.208
Co-authors Brett Ninness
2017 Wills AG, Schön TB, 'On the construction of probabilistic Newton-type algorithms', 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, Melbourne, Australia (2017) [E1]
DOI 10.1109/CDC.2017.8264638
2017 Jidling C, Wahlström N, Wills A, Schön TB, 'Linearly constrained Gaussian processes', Advances in Neural Information Processing Systems, Long Beach, CA (2017) [E1]
Citations Scopus - 6
2017 Fleming AJ, Ghalehbeygi OT, Routley BS, Wills AG, 'Experimental Scanning Laser Lithography with Exposure Optimization', IFAC Proceedings Volumes (IFAC-PapersOnline), Toulouse, France (2017) [E1]
DOI 10.1016/j.ifacol.2017.08.1524
Citations Scopus - 1
Co-authors Andrew Fleming
2017 Geng LH, Ninness B, Wills A, Schön T, 'Smoothed State Estimation via Efficient Solution of Linear Equations', IFAC-PapersOnLine, Toulouse, France (2017) [E1]
DOI 10.1016/j.ifacol.2017.08.323
Co-authors Brett Ninness
2017 Del Giudice A, Wills A, Mears A, 'Development of a Planning Tool for Network Ancillary Services Using Customer-Owned Solar and Battery Storage', 2017 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE EUROPE (ISGT-EUROPE), Torino, ITALY (2017)
2016 Fleming AJ, Wills A, Ghalehbeygi OT, Routley B, Ninness B, 'A Nonlinear Programming Approach to Exposure Optimization in Scanning Laser Lithography', 2016 AMERICAN CONTROL CONFERENCE (ACC), Boston, MA (2016) [E1]
Citations Scopus - 2Web of Science - 1
Co-authors Andrew Fleming, Brett Ninness
2014 Knagge G, Wills A, Mills A, Ninness B, 'ASIC and FPGA implementation strategies for Model Predictive Control', 2009 European Control Conference, ECC 2009 (2014) [E1]

© 2009 EUCA. This paper considers the system architecture and design issues for implementation of on-line Model Predictive Control (MPC) in Field Programmable Gate Arrays (FPGAs) ... [more]

© 2009 EUCA. This paper considers the system architecture and design issues for implementation of on-line Model Predictive Control (MPC) in Field Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits (ASICs). In particular, the computationally itensive tasks of fast matrix QR factorisation, and subsequent sequential quadratic programming, are addressed for control law computation. An important aspect of this work is the study of appropriate data word-lengths for various essential stages of the overall solution strategy.

Citations Scopus - 14
Co-authors Brett Ninness
2013 Fleming AJ, Ninness B, Wills AG, 'Spectral Estimation using Dual Sensors with Uncorrelated Noise', 2013 IEEE SENSORS, Baltimore, MD (2013) [E2]
Citations Scopus - 1
Co-authors Brett Ninness, Andrew Fleming
2012 Wills AG, Schon TB, Lindsten F, Ninness BM, 'Estimation of linear systems using a Gibbs sampler', Proceedings 16th IFAC Symposium on System Identification, Bruxelles, Belgium (2012) [E1]
Citations Scopus - 15
Co-authors Brett Ninness
2012 Henriksen SJ, Wills AG, Schon TB, Ninness BM, 'Parallel implementation of particle MCMC methods on a GPU', Proceedings 16th IFAC Symposium on System Identification, Bruxelles, Belgium (2012) [E1]
Citations Scopus - 13
Co-authors Brett Ninness
2012 Dahlin J, Lindsten F, Schon TB, Wills AG, 'Hierarchical Bayesian ARX models for robust inference', Proceedings 16th IFAC Symposium on System Identification, Bruxelles, Belgium (2012) [E1]
Citations Scopus - 4
2011 Wills AG, Mills AJ, Ninness BM, 'FPGA implementation of an interior-point solution for linear model predictive control', Proceedings of the 18th IFAC World Congress 2011, Milano, Italy (2011) [E1]
DOI 10.3182/20110828-6-it-1002.02857
Citations Scopus - 21
Co-authors Brett Ninness
2011 Wills AG, Schon TB, Ljung L, Ninness BM, 'Blind identification of Wiener models', Proceedings of the 18th IFAC World Congress, 2011, Milano, Italy (2011) [E1]
DOI 10.3182/20110828-6-it-1002.02610
Citations Scopus - 16
Co-authors Brett Ninness
2011 Gopaluni RB, Schon TB, Wills AG, 'Input design for nonlinear stochastic dynamic systems - A particle filter approach', Proceedings of the 18th IFAC World Congress, 2011, Milano, Italy (2011) [E1]
DOI 10.3182/20110828-6-it-1002.03722
Citations Scopus - 8
2010 Ninness BM, Wills AG, Schon TB, 'Estimation of general nonlinear state-space systems', Proceedings of the 49th IEEE Conference on Decision and Control, Atlanta, GA (2010) [E1]
Citations Scopus - 8Web of Science - 1
Co-authors Brett Ninness
2010 Wills AG, Schon TB, Ninness BM, 'Estimating state-space models in innovations form using the expectation maximisation algorithm', Proceedings of the 49th IEEE Conference on Decision and Control, Atlanta, GA (2010) [E1]
Citations Scopus - 4Web of Science - 5
Co-authors Brett Ninness
2009 Wills AG, Ninness BM, 'Estimation of generalised Hammerstein-Wiener systems', Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France (2009) [E1]
DOI 10.3182/20090706-3-fr-2004.0179
Citations Scopus - 15
Co-authors Brett Ninness
2009 Wills AG, Mills AJ, Ninness BM, 'A MATLAB software environment for system identification', Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France (2009) [E1]
DOI 10.3182/20090706-3-FR-2004.0314
Citations Scopus - 6
Co-authors Brett Ninness
2009 Mills AJ, Wills AG, Ninness BM, 'Nonlinear model predictive control of an inverted pendulum', Proceedings of the American Control Conference, St Louis, MO (2009) [E1]
DOI 10.1109/acc.2009.5160391
Citations Scopus - 28Web of Science - 17
Co-authors Brett Ninness
2009 Gopaluni RB, Schön TB, Wills AG, 'Particle filter approach to nonlinear system identification under missing observations with a real application', IFAC Proceedings Volumes (IFAC-PapersOnline) (2009)

This article reviews authors' recently developed algorithm for identification of nonlinear state-space models under missing observations and extends it to the case of unknown... [more]

This article reviews authors' recently developed algorithm for identification of nonlinear state-space models under missing observations and extends it to the case of unknown model structure. In order to estimate the parameters in a state-space model, one needs to know the model structure and have an estimate of states. If the model structure is unknown, an approximation of it is obtained using radial basis functions centered around a maximum a posteriori estimate of the state trajectory. A particle filter approximation of smoothed states is then used in conjunction with expectation maximization algorithm for estimating the parameters. The proposed approach is illustrated through a real application. © 2009 IFAC.

DOI 10.3182/20090706-3-FR-2004.0360
Citations Scopus - 8
2008 Fleming AJ, Wills AG, 'Optimal input signals for bandlimited scanning systems', Proceedings of the 17th World Congress of the International Federation of Automatic Control, Seoul, Korea (2008) [E1]
DOI 10.3182/20080706-5-kr-1001.1892
Citations Scopus - 7
Co-authors Andrew Fleming
2008 Wills AG, Schon TB, Ninness BM, 'Parameter estimation for discrete-time nonlinear systems using EM', Proceedings of the 17th World Congress of the International Federation of Automatic Control, Seoul, Korea (2008) [E1]
DOI 10.3182/20080706-5-kr-1001.2594
Citations Scopus - 27
Co-authors Brett Ninness
2008 Ljung L, Wills AG, 'Issues in sampling and estimating continuous-time models with stochastic disturbances', IFAC Proceedings Volumes (IFAC-PapersOnline) (2008)

The standard continuous time state space model with stochastic disturbances contains the mathematical abstraction of continuous time white noise. To work with well defined, discre... [more]

The standard continuous time state space model with stochastic disturbances contains the mathematical abstraction of continuous time white noise. To work with well defined, discrete time observations, it is necessary to sample the model with care. The basic issues are well known, and have been discussed in the literature. However, the consequences have not quite penetrated the practise of estimation and identification. One example is that the standard model of an observation being a snapshot of the current state plus noise independent of the state cannot be reconciled with this picture. Another is that estimation and identification of time continuous models require a more careful treatment of the sampling formulas. We discuss and illustrate these issues in the current contribution. An application of particular practical importance is the estimation of models based on irregularly sampled observations. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.

DOI 10.3182/20080706-5-KR-1001.0271
Citations Scopus - 6
2008 Hagenblad A, Ljung L, Wills AG, 'Maximum likelihood identification of Wiener models', IFAC Proceedings Volumes (IFAC-PapersOnline) (2008)

The Wiener model is a block oriented model having a linear dynamic system followed by a static nonlinearity. The dominating approach to estimate the components of this model has b... [more]

The Wiener model is a block oriented model having a linear dynamic system followed by a static nonlinearity. The dominating approach to estimate the components of this model has been to minimize the error between the simulated and the measured outputs. We show that this will in general lead to biased estimates if there is other disturbances present than measurement noise. The implications of Bussgang's theorem in this context are also discussed. For the case with general disturbances we derive the Maximum Likelihood method and show how it can be efficiently implemented. Comparisons between this new algorithm and the traditional approach confirm that the new method is unbiased and also has superior accuracy. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.

DOI 10.3182/20080706-5-KR-1001.0269
Citations Scopus - 12
2007 Heath WP, Li G, Wills AG, Lennox B, 'The Robustness of Input Constrained Model Predictive Control to Infinity-Norm Bound Model Uncertainty', Preprints of the 5th IFAC Symposium on Robust Control Design, Toulouse, France (2007) [E1]
2007 Ninness BM, Wills AG, 'An Identification Toolbox for Profiling Novel Techniques', Preprints of the 14th IFAC Symposium on System Identification, Newcastle, Australia (2007) [E1]
Co-authors Brett Ninness
2007 Fleming AJ, Wills AG, Moheimani SO, 'Sensor fusion for improved control of piezoelectric tube scanners', 2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Proceedings, Zurich, Switzerland (2007) [E1]
Citations Scopus - 4
Co-authors Andrew Fleming, Reza Moheimani
2007 Schon TB, Wills AG, Ninness BM, 'Maximum Likelihood Nonlinear System Estimation', Preprints of the 14th IFAC Symposium on System Identification, Newcastle, Australia (2007) [E1]
Co-authors Brett Ninness
2007 Schon TB, Wills AG, Ninness BM, 'Proccedings of the 14Tth IFAC Symposium on system identification', Preprints of the 14th IFAC Symposium on System Identification, Newcastle, Australia (2007) [E1]
Co-authors Brett Ninness
2007 Wills AG, Ninness BM, Gibson S, 'Maximum likelihood estimation of state space models from frequency domain data', Proceedings of the European Control Conference 2007, Kos, Greece (2007) [E1]
Co-authors Brett Ninness
2006 Heath WP, Li G, Wills AG, Lennox B, 'The robustness of input constrained model predictive control to infinity-norm bound model uncertainty', IFAC Proceedings Volumes (IFAC-PapersOnline) (2006)

The nonlinearity that arises in constrained MPC (model predictive control) satisfies an IQC (integral quadratic constraint), provided zero is feasible. It is thus possible to cons... [more]

The nonlinearity that arises in constrained MPC (model predictive control) satisfies an IQC (integral quadratic constraint), provided zero is feasible. It is thus possible to construct a robust stability test against any model uncertainty that also satisfies an IQC. In particular the test may be applied to structured and unstructured infinity-norm bound uncertainty. The test may be applied with predictive controllers of arbitrary horizon. The test is illustrated for several simple MPC schemes and simulation results are shown for a two-input two-output plant with left matrix fraction uncertainty. Copyright © 2006 IFAC.

Citations Scopus - 17
2006 Wills AG, Ninness BM, Gibson SH, 'On Gradient-Based Search For Multivariable System Estimates', Proceedings of 16th IFAC World Congress, Prague, Czech Republic (2006) [E1]
Co-authors Brett Ninness
2006 Ninness BM, Wills AG, Gibson SH, 'The University of Newcastle Identification ToolBox', Proceedings of The 16th IFAC World Congress, Prague, Czech Republic (2006) [E1]
Co-authors Brett Ninness
2005 Wills AG, Bates DR, Fleming AJ, Ninness BM, Moheimani SO, 'Application of MPC to an Active Structure Using Sampling Rates up To 25kHz', Proceedings of the 44th IEEE Conference On Decision And Control, Seville, Spain (2005) [E1]
Citations Scopus - 24Web of Science - 9
Co-authors Reza Moheimani, Andrew Fleming, Brett Ninness
2005 Heath WP, Wills AG, 'The inherent robustness of constrained linear model predictive control', IFAC Proceedings Volumes (IFAC-PapersOnline) (2005)

We show that a sufficient condition for the robust stability of constrained linear model predictive control is for the plant to be open-loop stable, for zero to be a feasible solu... [more]

We show that a sufficient condition for the robust stability of constrained linear model predictive control is for the plant to be open-loop stable, for zero to be a feasible solution of the associated quadratic programme and for the input weighting be sufficiently high. The result can be applied equally to state feedback and output feedback controllers with arbitrary prediction horizon. If integral action is included a further condition on the steady state modelling error is required for stability. Copyright © 2005 IFAC.

Citations Scopus - 12
2005 Heath WP, Wills AG, 'Zames-Falb multipliers for quadratic programming', Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 (2005)

In constrained linear model predictive control a quadratic program must be solved on-line at each control step. If zero is feasible the resultant static nonlinearity is sector bou... [more]

In constrained linear model predictive control a quadratic program must be solved on-line at each control step. If zero is feasible the resultant static nonlinearity is sector bound. We show that the nonlinearity is also monotone nondecreasing and slope restricted; furthermore it may be expressed as the gradient of a convex potential function. Hence we show the existence of Zames-Falb multipliers for such a nonlinearity. For completeness, we construct such multipliers both for the general case of multi-input multi-output static nonlinearities and for the particular case where the nonlinearity arises from a quadratic program. We also express the results in terms of integral quadratic constraints. These multipliers may be used in a general and versatile analysis of the robust stability of constrained model predictive control. © 2005 IEEE.

DOI 10.1109/CDC.2005.1582282
Citations Scopus - 12Web of Science - 7
2004 Wills AG, Heath WP, 'Nonlinear MPC and self-concordant barrier functions', IFAC Proceedings Volumes (IFAC-PapersOnline) (2004)

©2004 IFAC. The theory of self-concordant barriers was introduced by Nesterov and Nemirovskii (1994) in the context of interior-point methods for convex optimisation. Their develo... [more]

©2004 IFAC. The theory of self-concordant barriers was introduced by Nesterov and Nemirovskii (1994) in the context of interior-point methods for convex optimisation. Their development is general, elegant and enjoys widespread implementation in state-of-the-art. algorithms. In this paper we exploit the theory of self-concordant functions with application to nonlinear MPC. In particular we construct an invariant terminal constraint set via properties of self-concordant functions. We also extend earlier results on recentred barrier function MPC to nonlinear MPC (model predictive control) with state constraints. We show nominal closed-loop stability for a wide class of nonlinear systems under full state feedback. Copyright

DOI 10.1016/S1474-6670(17)31411-8
2004 Akkermans JAG, Wills AG, Heath WP, 'Robust cross-directional control of paper making machines with saturating actuators', Control Systems, Preprints, Conference (2004)

We discuss the design of cross-directional controllers which are guaranteed to be robustly stabilizing while incorporating a quadratic program for steady state performance. In par... [more]

We discuss the design of cross-directional controllers which are guaranteed to be robustly stabilizing while incorporating a quadratic program for steady state performance. In particular we propose implementing cross-directional controllers in modal form with a constrained internal model control structure. Nominal optimal steady state performance is guaranteed via a non-linear element that incorporates a quadratic program. The quadratic program can be expressed as a continuous sector bounded nonlinearity together with two linear transformations. Thus the multivariable circle criterion can be used to guarantee closed-loop stability in the presence of disturbances and modeling uncertainties.

Citations Scopus - 1
2003 Wills AG, Heath WP, 'An Exterior/Interior-point Approach to Infeasibility in Model Predictive Control', Proceedings for CDC 2003 (CD ROM), Maui, Hawaii (2003) [E1]
Citations Scopus - 5Web of Science - 3
2003 Heath WP, Wills AG, 'Design of Cross-Directional Controllers with Optimal Steady State Performance', Proceedings for ECC 2003, Cambridge, England (2003) [E1]
Citations Scopus - 19Web of Science - 14
2003 Heath WP, Wills AG, 'Design of cross-directional controllers with optimal steady state performance', European Control Conference, ECC 2003 (2003)

© 2003 EUCA. Actuator constraint handling is necessary for many cross-directional controllers. We discuss how optimal steady state performance can be guaranteed by modifying an in... [more]

© 2003 EUCA. Actuator constraint handling is necessary for many cross-directional controllers. We discuss how optimal steady state performance can be guaranteed by modifying an internal model control structure with a non-linear element. For the simple dynamics associated with most web processes this also gives good closed-loop dynamic behaviour. Thus unconstrained control design techniques may be applied directly to the constrained control problem.

2003 Heath WP, Wills AG, 'Design of cross-directional controllers with optimal steady state performance', European Control Conference, ECC 2003 (2003)

© 2003 EUCA. Actuator constraint handling is necessary for many cross-directional controllers. We discuss how optimal steady state performance can be guaranteed by modifying an in... [more]

© 2003 EUCA. Actuator constraint handling is necessary for many cross-directional controllers. We discuss how optimal steady state performance can be guaranteed by modifying an internal model control structure with a non-linear element. For the simple dynamics associated with most web processes this also gives good closed-loop dynamic behaviour. Thus unconstrained control design techniques may be applied directly to the constrained control problem.

Citations Scopus - 1
2002 Wills AG, Heath WP, 'Using A Modified Predictor-Corrector Algorithm for model Predictive Control', 15th Triennial World Congress, Barcelona, Spain (2002) [E1]
Citations Scopus - 4
2002 Wills AG, Heath WP, 'A Recentred Barrier for Constrained Receding Horizon Control', Proceedings of the American Control Conference, Anchorage, Alaska (2002) [E1]
Citations Scopus - 17Web of Science - 8
Show 45 more conferences

Report (1 outputs)

Year Citation Altmetrics Link
2009 Perez T, Wills AG, '[Commercial in confidence]', CFW-Hamilton Jet & Co Ltd, New Zealand, 27 (2009) [R2]
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Grants and Funding

Summary

Number of grants 11
Total funding $2,120,143

Click on a grant title below to expand the full details for that specific grant.


20181 grants / $1,473,200

Development and implementation of an advanced clinical decision-making support tool for the delivery of efficient, personalised rehabilitation for patients undergoing total knee arthroplasty (TKA).$1,473,200

Funding body: Ramsay Hospital Research Foundation Ltd

Funding body Ramsay Hospital Research Foundation Ltd
Project Team Professor Michael Nilsson, Professor Rohan Walker, Professor Sarah Johnson, Associate Professor Adrian Wills, Doctor Nattai Borges, Associate Professor Michael Pollack
Scheme Research Project
Role Investigator
Funding Start 2018
Funding Finish 2021
GNo G1801043
Type Of Funding C3112 - Aust Not for profit
Category 3112
UON Y

20171 grants / $103,307

Develop specific proprietary software for the automation of shiploading facilities$103,307

Funding body: Multiskilled Resources Australia Pty Ltd

Funding body Multiskilled Resources Australia Pty Ltd
Project Team Associate Professor Adrian Wills, Mr Jarrad Courts
Scheme Entrepreneurs’ Programme: Innovation Connections
Role Lead
Funding Start 2017
Funding Finish 2018
GNo G1700994
Type Of Funding C3111 - Aust For profit
Category 3111
UON Y

20164 grants / $136,099

Collision avoidance technology for ship loading facilities$97,909

Funding body: Department of Industry, Innovation and Science

Funding body Department of Industry, Innovation and Science
Project Team Associate Professor Adrian Wills, Mr Nathan Bartlett
Scheme Entrepreneurs' Programme: Innovation Connections
Role Lead
Funding Start 2016
Funding Finish 2016
GNo G1600552
Type Of Funding Grant - Aust Non Government
Category 3AFG
UON Y

Rapid Phenotyping Grinder$15,190

Funding body: Red Pineapple

Funding body Red Pineapple
Project Team Associate Professor Phil Clausen, Associate Professor Adrian Wills, Antony Martin, Dr Jamie Flynn, William Palmer
Scheme Tech Vouchers
Role Investigator
Funding Start 2016
Funding Finish 2016
GNo G1600953
Type Of Funding C3111 - Aust For profit
Category 3111
UON Y

Rapid Phenotyping Grinder$15,000

Funding body: NSW Trade & Investment

Funding body NSW Trade & Investment
Project Team Associate Professor Phil Clausen, Associate Professor Adrian Wills, Antony Martin, Dr Jamie Flynn, William Palmer
Scheme TechVouchers Program
Role Investigator
Funding Start 2016
Funding Finish 2016
GNo G1600841
Type Of Funding Other Public Sector - State
Category 2OPS
UON Y

Cooperative Navigation of Autonomous Underwater and Surface Vehicles in Littoral waters$8,000

Funding body: UVS Pty Ltd

Funding body UVS Pty Ltd
Project Team Associate Professor Adrian Wills, Mr Mark Gibson
Scheme Scholarship
Role Lead
Funding Start 2016
Funding Finish 2017
GNo G1600951
Type Of Funding C3111 - Aust For profit
Category 3111
UON Y

20151 grants / $20,000

Research for Stockpile Management Systems$20,000

Funding body: Department of Industry, Innovation and Science

Funding body Department of Industry, Innovation and Science
Project Team Associate Professor Adrian Wills
Scheme Entrepreneurs' Programme: Innovation Connections
Role Lead
Funding Start 2015
Funding Finish 2015
GNo G1501471
Type Of Funding Grant - Aust Non Government
Category 3AFG
UON Y

20111 grants / $106,447

Multicore Computing of Advanced Engine Control Algorithms$106,447

Funding body: General Motors, USA.

Funding body General Motors, USA.
Project Team Professor Brett Ninness, Associate Professor Adrian Wills
Scheme Research Grant
Role Investigator
Funding Start 2011
Funding Finish 2011
GNo G1000979
Type Of Funding International - Non Competitive
Category 3IFB
UON Y

20091 grants / $20,000

Fast and Robust Model Predictive Control$20,000

Funding body: University of Newcastle

Funding body University of Newcastle
Project Team Associate Professor Adrian Wills, Professor Brett Ninness, Doctor Geoffrey Knagge
Scheme Near Miss Grant
Role Lead
Funding Start 2009
Funding Finish 2009
GNo G0189828
Type Of Funding Internal
Category INTE
UON Y

20081 grants / $15,000

Advanced nonlinear constrained control$15,000

Funding body: University of Newcastle

Funding body University of Newcastle
Project Team Associate Professor Adrian Wills, Professor Brett Ninness
Scheme Pilot Grant
Role Lead
Funding Start 2008
Funding Finish 2008
GNo G0189105
Type Of Funding Internal
Category INTE
UON Y

20071 grants / $246,090

Advancing System Identification using Modern Optimisation Methods$246,090

Funding body: ARC (Australian Research Council)

Funding body ARC (Australian Research Council)
Project Team Professor Brett Ninness, Associate Professor Adrian Wills
Scheme Discovery Projects
Role Investigator
Funding Start 2007
Funding Finish 2009
GNo G0186347
Type Of Funding Aust Competitive - Commonwealth
Category 1CS
UON Y
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Research Supervision

Number of supervisions

Completed0
Current9

Current Supervision

Commenced Level of Study Research Title Program Supervisor Type
2019 PhD The Development of Bayesian Machine Learning Estimation Techniques with Direct Application to a Clinical Decision Support Tool for Rehabilitation Services PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
2019 PhD Particle Smoothing for Partially Deterministic Process Models PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
2018 PhD Infinite-Dimensional Non-Parametric Mapping for Online Simultaneous Localisation and Mapping PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
2018 PhD Fusion of Dense Optical Flow with Existing Sensor Systems for Localisation PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
2017 PhD Nonlinear System Identification using Gaussian Mixture Models PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
2016 PhD Cooperative Navigation of Autonomous Underwater and Surface Vehicles in Littoral Waters PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
2016 PhD Particle Markov Chain Monte Carlo Methods for Autonomous Vehicle Navigation PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
2016 PhD Probabilistic Modelling and Estimation of Elastic Strain from Diffraction-Based Measurements PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
2016 PhD Novel Collision Avoidance Algorithms for Autonomous Systems in 3D Environments PhD (Mechanical Engineering), Faculty of Engineering and Built Environment, The University of Newcastle Principal Supervisor
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Associate Professor Adrian Wills

Position

Associate Professor
School of Engineering
School of Engineering
Faculty of Engineering and Built Environment

Focus area

Mechatronics

Contact Details

Email adrian.wills@newcastle.edu.au
Phone (02) 4985 4109
Fax (02) 4921 6946
Link Personal webpage

Office

Room ES.331
Building Engineering S
Location Callaghan
University Drive
Callaghan, NSW 2308
Australia
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