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
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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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
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
Robust Dynamical System Identification. Innovative robust system identification methods are a Frontier Technology for Transforming Australian Industries. Robust system identification will provide a technology for generating high fidelity models by the use of breakthrough science. With the majority of advanced industrial control systems reliant on accurate models significant savings could be made due to the implicit improvement in process control. Furthermore, system identification is a key enabl ....Robust Dynamical System Identification. Innovative robust system identification methods are a Frontier Technology for Transforming Australian Industries. Robust system identification will provide a technology for generating high fidelity models by the use of breakthrough science. With the majority of advanced industrial control systems reliant on accurate models significant savings could be made due to the implicit improvement in process control. Furthermore, system identification is a key enabling technology in most modern systems (e.g. in aerospace, manufacturing, mining, minerals processing and telecommunications) and is also important in the emerging areas of nanotechnology and systems biology.Read moreRead less