Optimum location of FACTS devices with advanced control scheme for improving the security of complex power grid. Prevention of blackouts is one of the highest priorities of the electricity industry. One of the fundamental reasons for the recent blackouts in long transmission network is inter-area oscillations. Queensland's long transmission network is a vital part of the Australian electricity grid and is vulnerable to inter-area oscillations. There is a need for a comprehensive approach to inve ....Optimum location of FACTS devices with advanced control scheme for improving the security of complex power grid. Prevention of blackouts is one of the highest priorities of the electricity industry. One of the fundamental reasons for the recent blackouts in long transmission network is inter-area oscillations. Queensland's long transmission network is a vital part of the Australian electricity grid and is vulnerable to inter-area oscillations. There is a need for a comprehensive approach to investigate the effect of inter-area oscillation that contributes to blackouts. Focussing the Queensland network, this project will provide a complete assessment tool for the optimum location of FACTS devices with modern and advanced control schemes in improving the security of complex interconnected power-grid. Read moreRead less
Fast Signal Processing and Control Algorithms for Complex Hierarchical Systems. Complex dynamical behaviour is inherent to many real-world systems including telecommunications networks, financial markets and biological systems. High performance signal processing and control algorithms for such large-scale, complex systems are computationally very expensive in general. An important class of large-scale Markovian models arising in many applications shows a remarkable hierarchical property, display ....Fast Signal Processing and Control Algorithms for Complex Hierarchical Systems. Complex dynamical behaviour is inherent to many real-world systems including telecommunications networks, financial markets and biological systems. High performance signal processing and control algorithms for such large-scale, complex systems are computationally very expensive in general. An important class of large-scale Markovian models arising in many applications shows a remarkable hierarchical property, displaying strong interactions within certain clusters of states and weak interactions among these clusters. By utilizing this property, the proposed project will design and analyze novel reduced-complexity signal processing and control algorithms with rigorous performance guarantees. In addition, this project will explore possibilities of making these algorithms hierarchical such that they are easy to implement through decentralization.Read moreRead less
Stochastic Sensor Scheduling in Statistical Signal Processing. In several statistical signal processing applications, due to computational or communication constraints, at each time instant one can use only a few out of several possible noisy (stochastic) sensors. The stochastic sensor scheduling problem deals with how to dynamically choose which group of sensors to pick at each time instant. This project involves research in sensor scheduling for widely used stochastic dynamical systems such as ....Stochastic Sensor Scheduling in Statistical Signal Processing. In several statistical signal processing applications, due to computational or communication constraints, at each time instant one can use only a few out of several possible noisy (stochastic) sensors. The stochastic sensor scheduling problem deals with how to dynamically choose which group of sensors to pick at each time instant. This project involves research in sensor scheduling for widely used stochastic dynamical systems such as Hidden Markov Models and Jump Markov Linear Systems. It focuses on the design and analysis of stochastic control algorithms such as dynamic programming and simulation based randomized methods. The research will lead to an integrated theory incorporating stochastic control, statistical signal processing and combinatorial optimization. We will also apply the resulting techniques to tracking maneuvering targets given noisy observations.Read moreRead less
Efficient Algorithms for Multiple Object Filtering using Stochastic Geometry. The outcomes of this project will enhance our ability to harness advances in sensing and computing technologies and develop automated systems which facilitate rapid and reliable detection and monitoring of potential threats in our air, sea, and land space. Such systems assist our defence personnel in the event of a threat to implement measured and effective responses, and ultimately enhance Australia's operational adva ....Efficient Algorithms for Multiple Object Filtering using Stochastic Geometry. The outcomes of this project will enhance our ability to harness advances in sensing and computing technologies and develop automated systems which facilitate rapid and reliable detection and monitoring of potential threats in our air, sea, and land space. Such systems assist our defence personnel in the event of a threat to implement measured and effective responses, and ultimately enhance Australia's operational advantage, in line with the national research priority of 'Safeguarding Australia' and its associated priority goals. The developed technologies also have significant commercial potential which benefit Australian industries in areas such as robotics, automotive safety and biomedical engineering.Read moreRead less
Algorithms for change detection based on finite sample system identification theory. Detection of abrupt changes has many important applications. One particular application that will be investigated is leak detection in irrigation channels. As agriculture accounts for about 80% of Australia's water usage, the timely detection of leaks means that corrective actions can be taken early which will lead to large water savings and significant environmental benefits. The developed methods can be design ....Algorithms for change detection based on finite sample system identification theory. Detection of abrupt changes has many important applications. One particular application that will be investigated is leak detection in irrigation channels. As agriculture accounts for about 80% of Australia's water usage, the timely detection of leaks means that corrective actions can be taken early which will lead to large water savings and significant environmental benefits. The developed methods can be designed with any false alarm rate. This is important since frequent false alarms lead to wasted resources and operators will stop using the system. The technology once developed can be transferred to many other application areas such as urban water supplies, pipelines for oil and gas, and the process and manufacturing industries.Read moreRead less
Design of Large-Scale Interconnected Dynamical Systems. Our aim is to develop a theory for the design, analysis and operation of large-scale interconnected systems. In recent years there has been an explosive growth in the implementation and use of large-scale systems due to the ready availability of interconnection technology. However, there is no satisfactory systematic theoretical basis for identifying and quantifying potential advantages or pitfalls of large-scale interconnections. Several a ....Design of Large-Scale Interconnected Dynamical Systems. Our aim is to develop a theory for the design, analysis and operation of large-scale interconnected systems. In recent years there has been an explosive growth in the implementation and use of large-scale systems due to the ready availability of interconnection technology. However, there is no satisfactory systematic theoretical basis for identifying and quantifying potential advantages or pitfalls of large-scale interconnections. Several aspects of interconnected systems will be considered. For example, can large-scale systems composed of dynamical sub-systems linked through communication channels be systematically designed? How does overall system behaviour vary with scale and subsystem dynamics? Such questions are largely open and their resolution lies at the heart of this project.Read moreRead less
Model quality evaluation from finite data sets. Models of dynamical systems are used in many areas of science and engineering. There will always be uncertainties associated with a model, and in this project we will develop a tool for assessing this uncertainty. Having a good description of the uncertainty will depending on the application, lead to better designs, more efficient operations, better decision making etc. One particular application area of this research is to quantify the uncertainti ....Model quality evaluation from finite data sets. Models of dynamical systems are used in many areas of science and engineering. There will always be uncertainties associated with a model, and in this project we will develop a tool for assessing this uncertainty. Having a good description of the uncertainty will depending on the application, lead to better designs, more efficient operations, better decision making etc. One particular application area of this research is to quantify the uncertainties in models of irrigation channels. This will allow us to design better systems for regulation of water levels and flows, leading to large water savings and significant environmental benefits.
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Model-Reduction Techniques for Control, Communication and Circuits. Model reduction is an important area of study in the analysis and design of dynamical systems. Its objective is to obtain a low-order model given a high-order system model such that the low-order model closely approximates the input-output behaviour of the original high-order system. Although theory and application of model reduction is well developed, there are many unresolved issues such as efficient model reduction techniq ....Model-Reduction Techniques for Control, Communication and Circuits. Model reduction is an important area of study in the analysis and design of dynamical systems. Its objective is to obtain a low-order model given a high-order system model such that the low-order model closely approximates the input-output behaviour of the original high-order system. Although theory and application of model reduction is well developed, there are many unresolved issues such as efficient model reduction techniques for large-scale circuit simulation and communication applications, frequency-weighted model reduction techniques for controller-design applications, and error bounds for the reduction techniques. The project aims to address these issues.Read moreRead less
New System Identification Techniques Utilising Misspecified Models. National benefits of the proposed research project will result from improvements in control due to a better, more complete understanding of the models obtained by the newly proposed system identification technique. The resulting effect on industrial practice will be an increase in efficiency, by reduced waste, lower pollution levels and increased throughput. Also, the techniques developed will be directly applicable to current r ....New System Identification Techniques Utilising Misspecified Models. National benefits of the proposed research project will result from improvements in control due to a better, more complete understanding of the models obtained by the newly proposed system identification technique. The resulting effect on industrial practice will be an increase in efficiency, by reduced waste, lower pollution levels and increased throughput. Also, the techniques developed will be directly applicable to current research in the areas of complex systems, such as smart structures and biological studies of the dynamic effects of drugs and hormones on genes.Read moreRead less
Robust Experiment Design for Dynamical System Identification. Innovative and new robust experiment design methodologies are a Frontier Technology for Transforming Australian Industries. By providing a solid foundation for generating high fidelity models, robust experiment design will, by the use of breakthrough science, facilitate the estimation of models in minimum time. Also, this will entail minimal disruption to the normal operation of the process under study. With the majority of advanced ....Robust Experiment Design for Dynamical System Identification. Innovative and new robust experiment design methodologies are a Frontier Technology for Transforming Australian Industries. By providing a solid foundation for generating high fidelity models, robust experiment design will, by the use of breakthrough science, facilitate the estimation of models in minimum time. Also, this will entail minimal disruption to the normal operation of the process under study. With the majority of advanced industrial process control systems reliant on accurate models significant savings could also be made due to the implicit improvement in process control.Read moreRead less