Towards a unified theory of constrained control and estimation. The project will investigate the implications of duality and other connections between constrained control and estimation. We believe that the research will result in a richer understanding of these problems. In particular, we envisage an impact in at least four areas: (i) Computational issues, i.e., development of more efficient algorithms for constrained problems. (ii) Geometry of constrained problems, by extending recent results ....Towards a unified theory of constrained control and estimation. The project will investigate the implications of duality and other connections between constrained control and estimation. We believe that the research will result in a richer understanding of these problems. In particular, we envisage an impact in at least four areas: (i) Computational issues, i.e., development of more efficient algorithms for constrained problems. (ii) Geometry of constrained problems, by extending recent results pertaining to constrained control to estimation problems. (iii) Problems with mixed constraints, for example, interval and finite set constraints. (iv) Fundamental limitations imposed by constraints to filtering and control problems.Read moreRead less
Parsimonious Quantization in Signal Processing and Control. In today's society there is an abundance of data. Indeed, it could be argued that we suffer from data 'overload'. Thus to turn 'data' into actions, the need for parsimony in signal processing and control arises. For that purpose, the data must be sampled (in time) and quantized (in space). Within this context, the current project is aimed at understanding aspects of sampled parsimonious quantization. The results have widespread practica ....Parsimonious Quantization in Signal Processing and Control. In today's society there is an abundance of data. Indeed, it could be argued that we suffer from data 'overload'. Thus to turn 'data' into actions, the need for parsimony in signal processing and control arises. For that purpose, the data must be sampled (in time) and quantized (in space). Within this context, the current project is aimed at understanding aspects of sampled parsimonious quantization. The results have widespread practical uses including digital cameras, video compression, audio quantization, control over communication networks, switching of electronic devices and many others.Read moreRead less
COMPLEX NETWORKS: DYNAMICS, OPTIMIZATION AND CONTROL. Complex networks such large power grids, the Internet, transportation networks and co-operation networks of all kinds provide challenges for frontier technologies particularly computing, communication and control. In particular, advanced societies have become dependent on large infrastructure networks to an extent beyond our capability to plan and control them. The recent spate of collapses in power grids and virus attacks on the Internet i ....COMPLEX NETWORKS: DYNAMICS, OPTIMIZATION AND CONTROL. Complex networks such large power grids, the Internet, transportation networks and co-operation networks of all kinds provide challenges for frontier technologies particularly computing, communication and control. In particular, advanced societies have become dependent on large infrastructure networks to an extent beyond our capability to plan and control them. The recent spate of collapses in power grids and virus attacks on the Internet illustrate the need for research on modelling, analysis of behaviour, planning and control in such networks. This project aims to establish research in this area for Australia's benefit.Read moreRead less
Dynamics and Security Control of Complex Networks. The research will yield basic techniques to analyse, design and operate complex networks so that security, as well as performance, is achieved. These techniques will be further developed towards particular applications including power grids and telecommunication networks. However, the emphasis is on providing basic ideas and techniques.
Constrained Receding Horizon Control of Nonlinear Systems. Most real world control problems involve the design of strategies that
achieve performance goals in the presence of constraints on the system variables. Receding horizon control is a strategy that addresses this problem by directly optimising performance under the appropriate constraints. This project will address theoretical and computational issues associated with this methodology. The expected outcomes include:
* New finitely p ....Constrained Receding Horizon Control of Nonlinear Systems. Most real world control problems involve the design of strategies that
achieve performance goals in the presence of constraints on the system variables. Receding horizon control is a strategy that addresses this problem by directly optimising performance under the appropriate constraints. This project will address theoretical and computational issues associated with this methodology. The expected outcomes include:
* New finitely parameterised solutions for nonlinear systems.
* Implementations of reduced computational complexity.
* New insights into analytical properties of the methodology.
These outcomes are expected to add to Australian scientific recognition and to bring significant economic benefit to Australian industry.
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lll-conditioned and constrained inverse problems in Signal Processing, Telecommunications and Control. Aims: To carry out fundamental research on methods for understanding and solving inverse problems in signal processin, telecommunications and control. To translate these fundamental results into practical outcomes of importance to Australian Industry.
Significance: Signal Processing, Telecommunications and Control are core technologies for all modern societies. The research proposed here ....lll-conditioned and constrained inverse problems in Signal Processing, Telecommunications and Control. Aims: To carry out fundamental research on methods for understanding and solving inverse problems in signal processin, telecommunications and control. To translate these fundamental results into practical outcomes of importance to Australian Industry.
Significance: Signal Processing, Telecommunications and Control are core technologies for all modern societies. The research proposed here will generate new methods for designing and understanding key algorithms in these areas. Particular emphasis will be placed on difficult problems involving ill-conditioned inverses or those having hard constraints that must be satisfied.
Expected Outcomes: A prime outcome will be fundamental research results at the highest international level. This will be accompanied by top level refereed publications and books. There will also be direct and tangible benefits to Australian industry.Read moreRead less
Dynamics of eigenvalue/eigenspace algorithms with applications to signal processing. Many problems in signal and systems lead naturally to an eigenvalue/eigenspace determination and tracking problem; for example (acoustic) echo-cancellation, crosstalk suppression in ADSL modems, direction of arrival determination with an array of sensors, linear system identification etc. Exploiting methods from global analysis and dynamical systems theory we will study the available algorithms for eigenspace de ....Dynamics of eigenvalue/eigenspace algorithms with applications to signal processing. Many problems in signal and systems lead naturally to an eigenvalue/eigenspace determination and tracking problem; for example (acoustic) echo-cancellation, crosstalk suppression in ADSL modems, direction of arrival determination with an array of sensors, linear system identification etc. Exploiting methods from global analysis and dynamical systems theory we will study the available algorithms for eigenspace determination to characterise their computational efficiency, accuracy and effectiveness in various data scenarios. The analysis will lead to improved designs for eigenvalue/eigenspace algorithms, as well as design tools to engineer algorithms to specific situations.Read moreRead less
High dimensional problems of integration and approximation. In many applications, notably financial mathematics, problems of
integration and approximation of functions in very high dimensions
are of great interest. By finding modern mathematical solutions to
these problems, we will therefore contribute to Australia's future
success in developing innovative technologies for industrial and
economic applications. By researching at an internationally
competitive level and by cooperating with i ....High dimensional problems of integration and approximation. In many applications, notably financial mathematics, problems of
integration and approximation of functions in very high dimensions
are of great interest. By finding modern mathematical solutions to
these problems, we will therefore contribute to Australia's future
success in developing innovative technologies for industrial and
economic applications. By researching at an internationally
competitive level and by cooperating with international experts, we
will have a share in further strengthening the excellent role of
Australian research institutions within the international scientific
community in mathematics and scientific computing.Read moreRead less
The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop si ....The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop significantly faster and more accurate algorithms for this time varying eigenvalue problem than currently exist. Very modern techniques will be employed to achieve this aim, and the potential benefits to Australian hi-tech industries are great.
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Sparse grid approximations and fitting using generalised combination techniques. Sparse grid techniques provide an effective tool to deal with the
computational curse of dimensionality which is a constant challenge in
modelling complex data. The proposed research is aimed at the
development and analysis of algorithms for data fitting with sparse
grids using variants of the combination technique. The outcome of the
research is a theory which will provide insights in the applicability,
limit ....Sparse grid approximations and fitting using generalised combination techniques. Sparse grid techniques provide an effective tool to deal with the
computational curse of dimensionality which is a constant challenge in
modelling complex data. The proposed research is aimed at the
development and analysis of algorithms for data fitting with sparse
grids using variants of the combination technique. The outcome of the
research is a theory which will provide insights in the applicability,
limitations and the convergence properties of the proposed
algorithms. The outcomes will be widely applicable in modelling of
large scale and complex data as is encountered in areas of
bioinformatics, physics and experimental studies of complex systems.
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