Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New ....Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New design methods that deal with noise in an optimal way;
(iii) Noise resistant methods for distributed consensus seeking systems and cooperative control systems.
The outcomes will advance and benefit spatio-temporal data analysis and coordination in areas such as transport, health and video-security.Read moreRead less
Point processes system identification under simultaneity. Neuroscientists study neuronal brain dynamics of mammals via recordings from scores of tiny electrodes. But analysing these experiments is a problem because current methods cannot handle the common case where neurons discharge simultaneously. This project aims to provide powerful new tools to overcome this bottleneck.
Riemannian System Identification. A growing number of applications such as satellite attitude estimation, pose estimation in computer vision and direction estimation in statistics require the study of random processes in Riemannian manifolds and Lie Groups. This project will provide: methods for the construction/ numerical simulation of such processes; methods of system identification and their asymptotic performance analysis; and, algorithms for process state estimation.
Modeling stochastic systems in Riemannian manifolds. This project aims to develop new statistical signal processing and control engineering algorithms and tools that will enable tracking of objects remotely on land and in space. A growing number of applications require the study of random processes in Riemannian manifolds, that is processes that evolve subject to a geometric constraint. This project aims to provide methods for the numerical simulation of such processes, methods of online and off ....Modeling stochastic systems in Riemannian manifolds. This project aims to develop new statistical signal processing and control engineering algorithms and tools that will enable tracking of objects remotely on land and in space. A growing number of applications require the study of random processes in Riemannian manifolds, that is processes that evolve subject to a geometric constraint. This project aims to provide methods for the numerical simulation of such processes, methods of online and offline system identification from data on such processes and asymptotic performance analysis; and algorithms for process state estimation that obeys the geometry. The outcomes will advance and benefit spatio-temporal data analysis in areas such as transport, health and video-security.Read moreRead less
Vector network system identification. This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliabl ....Vector network system identification. This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliable operation in large complex human systems (such as financial systems) or natural systems (such as gene regulatory networks).Read moreRead less
Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to bu ....Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to build practical mathematical models for droplet impaction, spreading and evaporation on leaf surfaces, and experimentally calibrate and validate the models. The software is expected to drive the development of agrichemical products that increase retention, minimise environmental impacts, and reduce costs for end-users.Read moreRead less
Mass transport in high entropy alloys. This project aims to understand mass transport in high entropy alloys. Alloys of 5 to 13 components have technologically attractive mechanical properties. A knowledge of mass transport could control their stabilities and optimise their properties. This project will develop an atomistic theory and a phenomenological method for rapidly performing experiments, and experiment on two key high entropy alloys. The outcome of this research will be an in-depth under ....Mass transport in high entropy alloys. This project aims to understand mass transport in high entropy alloys. Alloys of 5 to 13 components have technologically attractive mechanical properties. A knowledge of mass transport could control their stabilities and optimise their properties. This project will develop an atomistic theory and a phenomenological method for rapidly performing experiments, and experiment on two key high entropy alloys. The outcome of this research will be an in-depth understanding of mass transport that is expected to fast-track these alloys to commercial uptake.Read moreRead less
Microstructural-Functional Effect of Silver Diammine Fluoride on Apatites. This project aims to develop a fundamental understanding at the nanostructural level of the factors that contribute to the enhanced mineralisation and mechanical properties of dentine and enamel following the treatment with silver diammine fluoride (SDF). A variety of advanced nanomechanical, tomographic and microscopic techniques will be used to characterise sound, carious and SDF treated tissue. The new biomechanical ev ....Microstructural-Functional Effect of Silver Diammine Fluoride on Apatites. This project aims to develop a fundamental understanding at the nanostructural level of the factors that contribute to the enhanced mineralisation and mechanical properties of dentine and enamel following the treatment with silver diammine fluoride (SDF). A variety of advanced nanomechanical, tomographic and microscopic techniques will be used to characterise sound, carious and SDF treated tissue. The new biomechanical evidence on the underlying mechanisms, alternative protocols, delivery systems enable to optimise the treatment. The scientific insights into arresting/repairing damage processes will provide critical data for developing minimal intervention protocols for pediatric and geriatric populations.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101056
Funder
Australian Research Council
Funding Amount
$395,775.00
Summary
Realising the potential of hyperbolic programming. This project aims to develop and analyse new mathematical and algorithmic methods for polynomial optimisation and decision problems. In doing so it expects to generate knowledge and tools in mathematical optimisation that build on recent developments in the theory of hyperbolic polynomials. Expected outcomes include more scalable and/or reliable methods for polynomial optimisation and safety verification of dynamical systems, and theory explain ....Realising the potential of hyperbolic programming. This project aims to develop and analyse new mathematical and algorithmic methods for polynomial optimisation and decision problems. In doing so it expects to generate knowledge and tools in mathematical optimisation that build on recent developments in the theory of hyperbolic polynomials. Expected outcomes include more scalable and/or reliable methods for polynomial optimisation and safety verification of dynamical systems, and theory explaining the power and limitations of these methods when compared with existing approaches. Possible benefits include safer and more reliable complex engineered systems, such as the power grid or interacting autonomous vehicles, verified by methods built on those developed in the project.Read moreRead less
Novel multiscale fibre composites for cryogenic space technologies. This project aims to develop new composite materials technologies for cryogenic space applications. Multifunctional nanomaterials with negative thermal expansion properties will be developed to simultaneously reduce thermal stress and improve fracture toughness, suppressing microcracking of fibre composites observed in current materials at cryogenic temperatures. New interleaves will be developed to act as gas barriers and provi ....Novel multiscale fibre composites for cryogenic space technologies. This project aims to develop new composite materials technologies for cryogenic space applications. Multifunctional nanomaterials with negative thermal expansion properties will be developed to simultaneously reduce thermal stress and improve fracture toughness, suppressing microcracking of fibre composites observed in current materials at cryogenic temperatures. New interleaves will be developed to act as gas barriers and provide strength. The composites will provide a new lightweight solution for storing cryogenic propellants such as liquid hydrogen and oxygen, for the next generation re-usable spacecraft. The outcomes of this project will enable Australian companies to produce and export specialised, high-performance composite products.Read moreRead less