Microcantilevers for multifrequency atomic force microscopy. This project aims to design a microcantilever with high-performing sensors more sensitive and with better noise performance than the typical optical system used in commercial Atomic Force Microscopes (AFMs). The AFM, a nanotechnology instrument, uses a microcantilever (with an extremely shape probe) to interrogate a sample surface. It has made important discoveries in nanotechnology, life sciences, nanomachining, material science and d ....Microcantilevers for multifrequency atomic force microscopy. This project aims to design a microcantilever with high-performing sensors more sensitive and with better noise performance than the typical optical system used in commercial Atomic Force Microscopes (AFMs). The AFM, a nanotechnology instrument, uses a microcantilever (with an extremely shape probe) to interrogate a sample surface. It has made important discoveries in nanotechnology, life sciences, nanomachining, material science and data storage systems. Despite its success, the technique’s spatial resolution and quantitative measurements are limited. This project could lead to breakthrough technologies such as atomic force spectroscopy to study elastic modulus of nanostructures, and establish Australia's prominence in this emerging field.Read moreRead less
Complex dynamical systems: inferring form and function of interacting biological systems. Often in biology a large number of simple parts interacting according to simple rules can result in behaviour that is rich and varied. This project aims to develop the mathematics of complex systems theory to describe how such collections of simple interacting parts can form large complicated structures, and to deduce what dynamical behaviour can result.
System identification of microstructure in the brain using magnetic resonance. Magnetic Resonance Imaging technologies will be exploited to probe the microstructure of the brain, using powerful Bayesian optimisation techniques and innovative uses of magnetic resonance. The project will in particular develop non-invasive imaging methods to quantify iron content in the brain, important for research on dementia and Alzheimer's disease.
Improving transient performance for systems with multiple inputs/outputs. This project aims to develop and test new mathematical techniques for the improvement of transient performance in tracking control systems. The fundamental problem to be addressed will be the design of controllers to rapidly track constant and time varying target reference signals without overshooting or undershooting for multiple-input multiple-output systems/plants. These new methods aim to offer improved accuracy and sp ....Improving transient performance for systems with multiple inputs/outputs. This project aims to develop and test new mathematical techniques for the improvement of transient performance in tracking control systems. The fundamental problem to be addressed will be the design of controllers to rapidly track constant and time varying target reference signals without overshooting or undershooting for multiple-input multiple-output systems/plants. These new methods aim to offer improved accuracy and speed in many engineering applications.Read moreRead less
Functional state observers for large-scale interconnected systems. This project will produce conceptual advances with new design rules to develop robust and efficient functional state observers for interconnected systems. The outcomes will advance the theory of functional observers and improve the operation, efficiency and performance of critical infrastructure such as power grids, water and traffic networks.
Reliable and efficient algorithms for modelling dynamical systems from data. Mathematical and computational models are increasingly important in diverse areas of science and engineering including aircraft and automotive design, robotics, medical sensing, and biology. However, finding an accurate model remains a difficult task. This project will develop new methods to reliably find highly accurate models from recorded data.
A New Approach to High-Performance Control of Nonlinear Systems. The coming generation of robots are highly mobile and will interact significantly with their environment, each other, and human collaborators. However, this leads to highly coupled nonlinear dynamical behaviour, and achieving accurate and reliable control of these systems is pushing current control theory to breaking point. This project aims to develop a new approach to control of nonlinear systems based on contraction theory and c ....A New Approach to High-Performance Control of Nonlinear Systems. The coming generation of robots are highly mobile and will interact significantly with their environment, each other, and human collaborators. However, this leads to highly coupled nonlinear dynamical behaviour, and achieving accurate and reliable control of these systems is pushing current control theory to breaking point. This project aims to develop a new approach to control of nonlinear systems based on contraction theory and convex optimisation, extending the power of optimisation-based control from linear to non-linear systems. The project is expected to lead to new theoretical developments, constructive algorithms and software, and experimental demonstrations on a range of platforms including bipedal walking robots and underwater robots.Read moreRead less
A geometric theory for modern optimisation problems in control and estimation. Linear-quadratic and spectral factorisation problems play a crucial role in system and control theory as well as many important application areas. The success of the project will represent a significant advancement of state-of-the-art in these broad areas.
Extracting macroscopic variables and their dynamics in multiscale systems with metastable states. There are practical barriers to the simulation of complex systems such as molecular systems and the climate system because of the high-dimensionality of the models and the presence of multiscale dynamics. This project will lift these barriers by uncovering the most relevant variables and by creating innovative multiscale simulation algorithms.
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.