
Associate Professor Adrian Wills
Associate Professor
School of Engineering (Mechatronics)
- Email:adrian.wills@newcastle.edu.au
- Phone:(02) 4985 4109
Career Summary
Biography
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
Professional Experience
UON Appointment
Title | Organisation / Department |
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Associate Professor | University of Newcastle School of Engineering Australia |
Associate Professor | University of Newcastle School of Engineering Australia |
Academic appointment
Dates | Title | Organisation / Department |
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1/1/2007 - 1/12/2009 | Fellow - APD | ARC (Australian Research Council) |
Membership
Dates | Title | Organisation / Department |
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IFAC Technical Committee Member - Modelling, Identification and Signal Processing, TC 1.1. | IFAC Technical Committee Australia |
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IEEE Technical Committee Member - System Identification and Adaptive Control | IEEE Australia |
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Chapter (2 outputs)
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2010 |
Wills AG, Ljung L, 'Wiener system identification using the maximum likelihood method', Block-oriented Nonlinear System Identification, Springer, Berlin 89-110 (2010) [B1]
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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]
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Journal article (40 outputs)
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2020 |
Cochrane JA, Flynn T, Wills A, Walker FR, Nilsson M, Johnson SJ, 'Clinical Decision Support Tools for Predicting Outcomes in Patients Undergoing Total Knee Arthroplasty: A Systematic Review', Journal of Arthroplasty, (2020) © 2020 Elsevier Inc. Background: Total knee arthroplasty is the standard surgical treatment for end-stage osteoarthritis. Although widely accepted as a successful procedure, appro... [more] © 2020 Elsevier Inc. Background: Total knee arthroplasty is the standard surgical treatment for end-stage osteoarthritis. Although widely accepted as a successful procedure, approximately 30% of patients are not satisfied due to non-optimal postoperative outcomes. Clinical decision support tools that are able to accurately predict post-surgery outcomes would assist in providing individualized advice or services to help alleviate possible issues, resulting in significant benefits to both the healthcare system and individuals. Methods: Five databases (Ovid Medline, Ovid EMBASE, CINAHL complete, Cochrane Library, and Scopus) were searched for the key phrases ¿knee replacement¿ or ¿knee arthroplasty¿ and ¿decision support tool,¿ ¿decision tool,¿ ¿predict* tool,¿ ¿predict* model,¿ ¿algorithm¿ or ¿nomogram.¿ Searches were limited to peer-reviewed journal articles published between January 2000 and June 2019. Reference lists of included articles were examined. Authors came to a consensus on the final list of included articles. Results: Eighteen articles were included for review. Most models reported low predictive success and inability to externally validate. Both candidate and final predictor variables were inconsistent between studies. Only 1 model was considered strongly predictive (AUROC >0.8), and only 2 studies were able to externally validate their developed model. In general, models that performed well used large patient numbers, were tested on similar demographics, and used either nonlinear input transformations or a completely nonlinear model. Conclusion: Some models do show promise; however, there remains the question of whether the reported predictive success can continue to be replicated. Furthermore, clinical applicability and interpretation of predictive tools should be considered during development.
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2020 |
Hendriks J, O Dell N, Wills A, Tremsin A, Wensrich C, Shinohara T, 'Bayesian non-parametric Bragg-edge fitting for neutron transmission strain imaging', Journal of Strain Analysis for Engineering Design, (2020) © IMechE 2020. Energy resolved neutron transmission techniques can provide high-resolution images of strain within polycrystalline samples allowing the study of residual strain an... [more] © IMechE 2020. Energy resolved neutron transmission techniques can provide high-resolution images of strain within polycrystalline samples allowing the study of residual strain and stress in engineered components. Strain is estimated from such data by analysing features known as Bragg-edges for which several methods exist. It is important for these methods to provide both accurate estimates of strain and an accurate quantification the associated uncertainty. Our contribution is twofold. First, we present a numerical simulation analysis of these existing methods, which shows that the most accurate estimates of strain are provided by a method that provides inaccurate estimates of certainty. Second, a novel Bayesian non-parametric method for estimating strain from Bragg-edges is presented. The numerical simulation analysis indicates that this method provides both competitive estimates of strain and accurate quantification of certainty, two demonstrations on experimental data are then presented.
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2020 |
Bartlett NJ, Renton C, Wills AG, 'A Closed-Form Prediction Update for Extended Target Tracking Using Random Matrices', IEEE Transactions on Signal Processing, 68 2404-2418 (2020) [C1]
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2020 |
Eielsen AA, Leth J, Fleming AJ, Wills AG, Ninness B, 'Large-Amplitude Dithering Mitigates Glitches in Digital-to-Analogue Converters', IEEE Transactions on Signal Processing, 68 1950-1963 (2020) [C1]
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2020 |
Gregg AWT, Hendriks JN, Wensrich CM, Luzin V, Wills A, 'Neutron diffraction strain tomography: Demonstration and proof-of-concept', REVIEW OF SCIENTIFIC INSTRUMENTS, 91 (2020) [C1]
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2020 |
Hendriks JN, Wensrich CM, Wills A, 'A Bayesian approach to triaxial strain tomography from high-energy X-ray diffraction', Strain, 56 (2020) [C1]
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2020 |
Yu C, Ljung L, Wills A, Verhaegen M, 'Constrained subspace method for the identification of structured state-space models (cosmos)', IEEE Transactions on Automatic Control, 65 4201-4214 (2020) [C1]
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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]
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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]
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2019 |
Hendriks JN, Gregg AWT, Jackson RR, Wensrich CM, Wills A, Tremsin AS, et al., 'Tomographic reconstruction of triaxial strain fields from Bragg-edge neutron imaging', PHYSICAL REVIEW MATERIALS, 3 (2019) [C1]
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2019 |
Hendriks J, Gregg A, Wensrich C, Wills A, 'Implementation of traction constraints in Bragg-edge neutron transmission strain tomography', STRAIN, 55 (2019) [C1]
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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]
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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]
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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]
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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.
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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.
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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]
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2013 |
Ninness B, Wills A, Mills A, 'UNIT: A freely available system identification toolbox', Control Engineering Practice, 21 631-644 (2013) [C1]
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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.
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2012 |
Wills AG, Ninness BM, 'Generalised Hammerstein-Wiener system estimation and a benchmark application', Control Engineering Practice, 20 1097-1108 (2012) [C1]
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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]
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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]
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2011 |
Schon TB, Wills AG, Ninness BM, 'System identification of nonlinear state-space models', Automatica, 47 39-49 (2011) [C1]
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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]
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2010 |
Ljung L, Wills AG, 'Issues in sampling and estimating continuous-time models with stochastic disturbances', Automatica, 46 925-931 (2010) [C1]
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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]
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2009 |
Fleming AJ, Wills AG, 'Optimal periodic trajectories for band-limited systems', IEEE Transactions on Control Systems Technology, 17 552-562 (2009) [C1]
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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]
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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]
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2008 |
Hagenblad A, Ljung L, Wills AG, 'Maximum likelihood identification of Wiener models', Automatica, 44 2697-2705 (2008) [C1]
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2008 |
Wills AG, Ninness BM, 'On gradient-based search for multivariable system estimates', IEEE Transactions on Automatic Control, 53 298-306 (2008) [C1]
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2007 |
Heath WP, Wills AG, 'Zames-Falb multipliers for quadratic programming', IEEE Transactions on Automatic Control, 52 1948-1951 (2007) [C1]
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2005 |
Gibson S, Wills AG, Ninness BM, 'Maximum-likelihood parameter estimation of bilinear systems', IEEE Transactions on Automatic Control, 50 1581-1596 (2005) [C1]
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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]
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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]
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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.
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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.
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2004 |
Wills AG, Heath WP, 'Barrier function based model predictive control', Automatica, 40 1415-1422 (2004) [C1]
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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)
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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]
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Show 37 more journal articles |
Conference (48 outputs)
Year | Citation | Altmetrics | Link | ||||||||
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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]
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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]
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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]
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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]
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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]
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2017 |
Jidling C, Wahlström N, Wills A, Schön TB, 'Linearly constrained Gaussian processes', Advances in Neural Information Processing Systems, Long Beach, CA (2017) [E1]
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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]
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2017 |
Geng LH, Ninness B, Wills A, Schön T, 'Smoothed State Estimation via Efficient Solution of Linear Equations', IFAC-PapersOnLine, Toulouse, France (2017) [E1]
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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)
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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]
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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.
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2013 |
Fleming AJ, Ninness B, Wills AG, 'Spectral Estimation using Dual Sensors with Uncorrelated Noise', 2013 IEEE SENSORS, Baltimore, MD (2013) [E2]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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.
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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]
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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]
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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.
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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.
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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]
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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]
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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]
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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]
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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]
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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.
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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]
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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]
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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]
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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.
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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.
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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
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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.
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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]
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2003 |
Heath WP, Wills AG, 'Design of Cross-Directional Controllers with Optimal Steady State Performance', Proceedings for ECC 2003, Cambridge, England (2003) [E1]
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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. |
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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.
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2002 |
Wills AG, Heath WP, 'Using A Modified Predictor-Corrector Algorithm for model Predictive Control', 15th Triennial World Congress, Barcelona, Spain (2002) [E1]
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2002 |
Wills AG, Heath WP, 'A Recentred Barrier for Constrained Receding Horizon Control', Proceedings of the American Control Conference, Anchorage, Alaska (2002) [E1]
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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] |
Grants and Funding
Summary
Number of grants | 13 |
---|---|
Total funding | $2,574,555 |
Click on a grant title below to expand the full details for that specific grant.
20202 grants / $454,412
Robotic rail isolation device$304,412
Funding body: Australasian Centre for Rail Innovation
Funding body | Australasian Centre for Rail Innovation |
---|---|
Project Team | Doctor Joel Ferguson, Professor Craig Wheeler, Associate Professor Adrian Wills, Doctor Michael Carr |
Scheme | PF34 - Trackside Robotic Devices |
Role | Investigator |
Funding Start | 2020 |
Funding Finish | 2020 |
GNo | G1901599 |
Type Of Funding | C2110 - Aust Commonwealth - Own Purpose |
Category | 2110 |
UON | Y |
Robo-Laser: A Novel System for Remediation of Marine Corrosion in Confined Spaces Within Naval Platforms Using Laser Carrying Spider Robots$150,000
Funding body: NSW Department of Industry
Funding body | NSW Department of Industry |
---|---|
Project Team | Professor Behdad Moghtaderi, Doctor Jafar Zanganeh, Professor Robert Melchers, Associate Professor Adrian Wills, Doctor Joel Ferguson, Professor Assaad Masri, Dr Matthew Dunn, Dr Shima Taheri |
Scheme | Defence Innovation Network Pilot Project |
Role | Investigator |
Funding Start | 2020 |
Funding Finish | 2020 |
GNo | G1901315 |
Type Of Funding | C2210 - Aust StateTerritoryLocal - Own Purpose |
Category | 2210 |
UON | Y |
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, Doctor 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 |
Research Supervision
Number of supervisions
Current Supervision
Commenced | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2020 | PhD | Machine Decision Making for the Qualification of Autonomy | PhD (Mechanical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
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), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2019 | PhD | State and Parameter Estimation for Jump Markov Linear Systems | PhD (Mechanical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2018 | PhD | Fusion of Dense Optical Flow with Existing Sensor Systems for Localisation | PhD (Mechanical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2018 | PhD | Collaborative Control Methodology in Rehabilitation Robotics | PhD (Electrical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2017 | PhD | Nonlinear System Identification using Gaussian Mixture Models | PhD (Mechanical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2016 | PhD | Particle Markov Chain Monte Carlo Methods for Autonomous Vehicle Navigation | PhD (Mechanical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
Past Supervision
Year | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2020 | PhD | Probabilistic Modelling and Estimation of Elastic Strain from Diffraction-Based Measurements | PhD (Mechanical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2020 | PhD | Bayesian Methodologies for Extended Target Tracking | PhD (Mechanical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
Associate Professor Adrian Wills
Position
Associate Professor
School of Engineering
School of Engineering
College of Engineering, Science and Environment
Focus area
Mechatronics
Contact Details
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 |