A stochastic geometric framework for Bayesian sensor array processing. This project develops a mathematical framework, and a new generation of techniques, for sensor array processing to address real-world problems with uncertainty in array parameters and number of signals. The outcomes will enhance the capability of sensors in many application areas including, radar, sonar, astronomy and wireless communications.
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
Distributed Estimation, Control and Optimisation for Networked Systems. This project aims to study large scale networked systems in major infrastructures including power networks, transportation networks, internet of things, and other cyber-physical systems. This project is expected to develop new methodology and algorithms for distributed estimation, control and optimisation of these systems. Distributed solutions are essential because traditional techniques which were designed for small system ....Distributed Estimation, Control and Optimisation for Networked Systems. This project aims to study large scale networked systems in major infrastructures including power networks, transportation networks, internet of things, and other cyber-physical systems. This project is expected to develop new methodology and algorithms for distributed estimation, control and optimisation of these systems. Distributed solutions are essential because traditional techniques which were designed for small systems are not suitable for efficient operations of large scale systems. Application examples include distributed state estimation for power networks, control of multi-agent systems and optimal scheduling of transportation networks. The outcomes of this project are vital to the understanding and management of these systems. Read moreRead less
Sensitivity Analysis of Networked Feedback Systems. This project is concerned with the analysis of networks of interacting dynamic feedback systems. This fundamental area of research underpins transportation networks, biomolecular signalling networks, economic systems, water supply, smart electricity grids, communications and a range of other applications. This work aims to address critical questions relating to robustness and sensitivity analysis questions in this context. This fundamental adva ....Sensitivity Analysis of Networked Feedback Systems. This project is concerned with the analysis of networks of interacting dynamic feedback systems. This fundamental area of research underpins transportation networks, biomolecular signalling networks, economic systems, water supply, smart electricity grids, communications and a range of other applications. This work aims to address critical questions relating to robustness and sensitivity analysis questions in this context. This fundamental advance in knowledge is expected to advance Australia's standing as an international authority in the area.Read moreRead less
Exploring new tools in nonlinear filtering and control. The conceptual advances with new design rules to be developed in the area of nonlinear filtering and control. Major benefits of this project will be its direct applications to state estimation and control problems in automobile, manufacturing, military hardware and medical device industries, and its increased capacity of contact research.
What learning is there in learning control? This project seeks to establish a meaningful definition and quantifiable measure of learning in the context of adaptive or learning control. The project is designed within the context of human motor skill learning, and assesses the speed of learning and the quality of learning (reflected by the accuracy of the motor task execution). The project plans to use measures to provide a mathematically precise meaning for the notion of learning. The outcome has ....What learning is there in learning control? This project seeks to establish a meaningful definition and quantifiable measure of learning in the context of adaptive or learning control. The project is designed within the context of human motor skill learning, and assesses the speed of learning and the quality of learning (reflected by the accuracy of the motor task execution). The project plans to use measures to provide a mathematically precise meaning for the notion of learning. The outcome has the potential to be applied to the design of technology-assisted training of motor skills, from the recovery of lost motor skills after trauma to the development of elite athletes.Read moreRead less