A New Approach to Sampled-Data Control Design for Nonlinear Systems. This project aims to exploit new sampling and sampled-data modelling insights to bridge the continuous/sampled-data gap in the control of nonlinear systems. The goal is to investigate the impact of these insights on the control design problem and provide a new class of digital control laws for continuous time non-linear systems.
Energy efficient sensing, computing and communication. This research will study trade-offs in resource use: bandwidth, power, and computational capacity of systems of sensors such as cameras, radars, and distributed sensor networks based on a statistical mechanical theory of information processing, leading to practical algorithms to optimize resource use in the design of such systems.
Renewable energy generation from flow-induced vibration. Much engineering effort has been expended to eliminate vibration of marine structures. This project seeks to provide the basis for the development of tidal energy harnessing, by deliberately amplifying and harnessing vibration. This technology offers the promise of capturing clean, zero-emissions energy, while presenting no risk to marine life.
Optimal control with decentralised information. This project will deliver optimisation-based tools to underpin systematic engineering approaches to the management of complex and networked systems arising in diverse areas. Optimal control for achieving guaranteed behaviour finds application in transport, resource management and distribution, telecommunications, and robotics and automation.
Estimation of Complex Networked Dynamic Systems. An essential part of science and engineering is the development of mathematical models to describe how observed quantities relate to one another. For example, such models have proven to be extremely powerful in predicting the value of financial instruments, in providing high performance control of robots, and in detecting faults or changes in petrochemical processing plants. Constructing these models based on measurements from the system itself is ....Estimation of Complex Networked Dynamic Systems. An essential part of science and engineering is the development of mathematical models to describe how observed quantities relate to one another. For example, such models have proven to be extremely powerful in predicting the value of financial instruments, in providing high performance control of robots, and in detecting faults or changes in petrochemical processing plants. Constructing these models based on measurements from the system itself is known as system identification. This project is directed at developing new system identification methods for situations that, on the one hand, have previously been considered unsolvable, and on the other, are acknowledged as being of high practical interest.Read moreRead less
Algebraic and geometric methods in switched control system analysis and design. The theory of switched control systems underpins complex network technologies that enable cleaner, more efficient and sustainable energy, transport and industry. The research aims to extend the fundamental knowledge base in systems and control, contributing to maintain the solid world-class reputation of Australia in the field.
Stability and performance analysis for uncertain time-varying interconnected systems. This project will deliver new mathematical tools for the study of interconnected systems. This will broaden the scope for rigorously certifying engineered systems and understanding interactions in the natural world. Potential application areas include telecommunications, transport, water distribution, smart-grids, neuroscience and cell biology.
Robust control of power electronics and drives: a synthesis of traditional and model predictive control approaches. This project aims to generate high-performance strategies for the control of power converters. Through the combination of traditional and modern approaches, the project will develop methods which are more reliable and give better energy efficiency than current state of the art techniques.
A general framework for the stability and robustness of dynamical systems. Stability and robustness are crucial properties of well-engineered dynamical systems. This project aims to unify several notions of stability and robustness and to expand these notions to the emerging area of hybrid systems, which includes next generation electricity distribution networks.
A stochastic geometric framework for Bayesian sensor array processing. This project develops a mathematical framework, and a new generation of techniques, for sensor array processing to address real-world problems with uncertainty in array parameters and number of signals. The outcomes will enhance the capability of sensors in many application areas including, radar, sonar, astronomy and wireless communications.