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
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
Finite-dimensional Sampled-data Control of Nonlinear Spatially Distributed Parameter Systems. Optical communication networks, smart materials and fluid flows, are all examples of systems whose behaviour can be significantly improved by automatic control. These are identified as some of the key technologies that will shape our future. This project will contribute to the fundamental science and engineering design of such diverse systems. Two postdoctoral fellows and one graduate student will be t ....Finite-dimensional Sampled-data Control of Nonlinear Spatially Distributed Parameter Systems. Optical communication networks, smart materials and fluid flows, are all examples of systems whose behaviour can be significantly improved by automatic control. These are identified as some of the key technologies that will shape our future. This project will contribute to the fundamental science and engineering design of such diverse systems. Two postdoctoral fellows and one graduate student will be trained in this important emerging field.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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New research directions in the area of sampled-data systems. Increased application of digital technology in a wide variety of control engineering applications has led to renewed interest in the study of sampled-data systems. With many applications ranging from nano-technology through to aerospace, robotics, bio-medicine and telecommunications, sampled-data systems form an integral part of many frontier technologies arising in engineering. In exploring and furthering these emerging technologies, ....New research directions in the area of sampled-data systems. Increased application of digital technology in a wide variety of control engineering applications has led to renewed interest in the study of sampled-data systems. With many applications ranging from nano-technology through to aerospace, robotics, bio-medicine and telecommunications, sampled-data systems form an integral part of many frontier technologies arising in engineering. In exploring and furthering these emerging technologies, this proposal aims to provide exciting breakthroughs in the theory of time and event driven sampled-data nonlinear systems. Equipped with these powerful new tools, we will address important analysis and design issues in this area, for example, for Networked Control Systems.Read moreRead less
Analysis and design of control systems with saturation and time-delay. Control engineering is an enabling technology without which most modern engineering systems, such as aircrafts or Internet, can not operate properly. Actuator saturation and time-delays are undesirable phenomena that often arise in control systems leading to poor performance and sometimes instability. For example, both of these phenomena arise in control of modern telecommunication systems, such as Active Queue Management in ....Analysis and design of control systems with saturation and time-delay. Control engineering is an enabling technology without which most modern engineering systems, such as aircrafts or Internet, can not operate properly. Actuator saturation and time-delays are undesirable phenomena that often arise in control systems leading to poor performance and sometimes instability. For example, both of these phenomena arise in control of modern telecommunication systems, such as Active Queue Management in TCP networks. The project aims at tackling these phenomena by using recently developed techniques in antiwindup for saturating actuators and by revisiting some classical methods for Smith predictor design for time-delayed systems.Read moreRead less
Towards an Information Theory for Communication-Limited Control Systems. In a number of emerging applications in communications, manufacturing and defence, various dynamical systems are measured and controlled by transmitting feedback over digital communication channels. In such situations, the often limited data rate available for transmissions can have a significant negative impact on the overall objectives. This proposal aims to develop techniques for analysing and designing such systems, and ....Towards an Information Theory for Communication-Limited Control Systems. In a number of emerging applications in communications, manufacturing and defence, various dynamical systems are measured and controlled by transmitting feedback over digital communication channels. In such situations, the often limited data rate available for transmissions can have a significant negative impact on the overall objectives. This proposal aims to develop techniques for analysing and designing such systems, and to delineate the fundamental limits to their performance. This has the potential to contribute to a greater understanding of the behaviour of many real systems which combine communications and control in feedback loops.Read moreRead less
Nonlinear systems with disturbances: analysis, controller design and tradeoffs. A range of classical asymptotic methods (averaging, singular perturbations and slowly varying techniques) have been recently generalized to deal with nonlinear systems with disturbances. The goal of this proposal is the activation of these methods in analysis, controller design and understanding the design tradeoffs of nonlinear system with disturbances. Application areas are in adaptive, vibrational and gain schedul ....Nonlinear systems with disturbances: analysis, controller design and tradeoffs. A range of classical asymptotic methods (averaging, singular perturbations and slowly varying techniques) have been recently generalized to deal with nonlinear systems with disturbances. The goal of this proposal is the activation of these methods in analysis, controller design and understanding the design tradeoffs of nonlinear system with disturbances. Application areas are in adaptive, vibrational and gain scheduling control.Read moreRead less