Real time optimisation by extremum seeking control and learning control. Optimal control technology provides the systematic design of systems that exhibit optimal behaviour, such as maximal productivity, best efficiency, minimal cost and best quality. Real time optimisation finds the solution of the optimal control in real time, relaxing requirements on the system knowledge. The proposed research will build on Australia's well-established strength in control and optimisation, and aim to establis ....Real time optimisation by extremum seeking control and learning control. Optimal control technology provides the systematic design of systems that exhibit optimal behaviour, such as maximal productivity, best efficiency, minimal cost and best quality. Real time optimisation finds the solution of the optimal control in real time, relaxing requirements on the system knowledge. The proposed research will build on Australia's well-established strength in control and optimisation, and aim to establish within Australia world-leading expertise in real time optimisation theories and applications. This will have direct benefits to the Australian economy through various engineering applications ranging from vehicle dynamics to emissions reduction to manufacturing process to efficiency improvement of power generation systems.Read moreRead less
Efficient Operation of Bioreactors using Nonlinear Dynamical Systems Theory. Current methods of determining optimal operating conditions in bioreactors have recently been shown to be inefficient, resulting in serious omissions of crucial parameter regions. We will use mathematical techniques from dynamical systems theory to establish a general framework by which bioreactor systems can be efficiently and systematically investigated to improve reactor performance. By communicating these results at ....Efficient Operation of Bioreactors using Nonlinear Dynamical Systems Theory. Current methods of determining optimal operating conditions in bioreactors have recently been shown to be inefficient, resulting in serious omissions of crucial parameter regions. We will use mathematical techniques from dynamical systems theory to establish a general framework by which bioreactor systems can be efficiently and systematically investigated to improve reactor performance. By communicating these results at relevant fora, we will increase the awareness within the Australian and international engineering communities of the advantages of modern mathematical techniques. Although this proposal focuses on bioreactors, the techniques can be easily adapted to improve the performances of other chemical processes.
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Extremum seeking control: analysis, design and applications. Optimal control is one of the central pillars in the field of automatic control, but is prevented from use in many engineering applications due to the computational complexity and system knowledge requirements typically associated with the technique. Extremum seeking promises the performance of an optimal approach, but with the benefit of real time implementation and very relaxed requirements on the system knowledge. Through improved u ....Extremum seeking control: analysis, design and applications. Optimal control is one of the central pillars in the field of automatic control, but is prevented from use in many engineering applications due to the computational complexity and system knowledge requirements typically associated with the technique. Extremum seeking promises the performance of an optimal approach, but with the benefit of real time implementation and very relaxed requirements on the system knowledge. Through improved understanding of extremum seeking algorithms, applications from vehicle dynamics to emissions reduction to manufacturing processes will benefit with greater levels of performance and robustness.Read moreRead less
Mining venture risk: novel econometric methods to integrate joint financial and geological uncertainty into dynamic risk forecasting measures. The mining industry is nationally important: it contributed $33,927M to Australia's GDP in 2002-3. This project's outcomes - sophisticated statistical and econometric tools - will significantly improve capability for forecasting overall risk to mining projects requiring vast upfront, irreversible investments, and contribute to its efficiency and internati ....Mining venture risk: novel econometric methods to integrate joint financial and geological uncertainty into dynamic risk forecasting measures. The mining industry is nationally important: it contributed $33,927M to Australia's GDP in 2002-3. This project's outcomes - sophisticated statistical and econometric tools - will significantly improve capability for forecasting overall risk to mining projects requiring vast upfront, irreversible investments, and contribute to its efficiency and international competitiveness. Innovative methods driven by data from complex financial and geological systems will integrate price volatility risk and orebody uncertainty in a real options framework, providing holistic, rigorous measurement of mining venture risk. Xstrata Queensland Ltd will strongly support and participate in research training of an identified candidate to deliver discoveries to the wider industry.Read moreRead less
New Approaches to the Analysis of Count Time Series. The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evo ....New Approaches to the Analysis of Count Time Series. The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evolution over time. In so doing, they enable both accurate inferences regarding the dynamic structure of the data to be drawn and accurate forecasts of future event counts to be produced.Read moreRead less