Distributed Estimation, Control and Optimisation for Networked Systems. This project aims to study large scale networked systems in major infrastructures including power networks, transportation networks, internet of things, and other cyber-physical systems. This project is expected to develop new methodology and algorithms for distributed estimation, control and optimisation of these systems. Distributed solutions are essential because traditional techniques which were designed for small system ....Distributed Estimation, Control and Optimisation for Networked Systems. This project aims to study large scale networked systems in major infrastructures including power networks, transportation networks, internet of things, and other cyber-physical systems. This project is expected to develop new methodology and algorithms for distributed estimation, control and optimisation of these systems. Distributed solutions are essential because traditional techniques which were designed for small systems are not suitable for efficient operations of large scale systems. Application examples include distributed state estimation for power networks, control of multi-agent systems and optimal scheduling of transportation networks. The outcomes of this project are vital to the understanding and management of these systems. Read moreRead less
Exploring new tools in nonlinear filtering and control. The conceptual advances with new design rules to be developed in the area of nonlinear filtering and control. Major benefits of this project will be its direct applications to state estimation and control problems in automobile, manufacturing, military hardware and medical device industries, and its increased capacity of contact research.
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.
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.
Robust control of mobile networked systems. The conceptual advances with new design rules are to be developed in the area of robust control of mobile networked systems. A major benefit of the research to be carried out in this project will be its direct application to industrial control problems in the defence, communications and robotics industries and to the management of the environment.
Efficient and high-precision system identification in quantum cybernetics. This project aims to develop new theories and algorithms to enhance system identification capabilities in quantum cybernetics from the perspective of systems and control. The project is anticipated to advance key knowledge and provide effective methods to enable identification of microsystems for wide applications arising in this emerging technology revolution. The intended outcomes are fundamental theories, and efficient ....Efficient and high-precision system identification in quantum cybernetics. This project aims to develop new theories and algorithms to enhance system identification capabilities in quantum cybernetics from the perspective of systems and control. The project is anticipated to advance key knowledge and provide effective methods to enable identification of microsystems for wide applications arising in this emerging technology revolution. The intended outcomes are fundamental theories, and efficient estimation methods for identifying these systems. This project will make important contributions to accelerating practical applications of new technology, and deliver new knowledge and skills for Australia's future industries, which will benefit Australia's economic growth.Read moreRead less
Topological Analysis and Control Design for Heterogeneous Multi-agent Systems. A multi-agent system refers to a cooperative group of autonomous agents for achieving certain collective behaviour such as flight formation and micro-robot synchronisation. The project aims to: study network topologies in biological systems and understand their applicability to the control of man-made multi-agent systems; and, develop a new theoretical framework and design methodology for control of heterogeneous mult ....Topological Analysis and Control Design for Heterogeneous Multi-agent Systems. A multi-agent system refers to a cooperative group of autonomous agents for achieving certain collective behaviour such as flight formation and micro-robot synchronisation. The project aims to: study network topologies in biological systems and understand their applicability to the control of man-made multi-agent systems; and, develop a new theoretical framework and design methodology for control of heterogeneous multi-agent systems. The expected outcomes include: understanding and application of biologically inspired network topologies for multi-agent systems; new control design methodology for heterogeneous multi-agent systems; and, new applications of multi-agent control in collective robotics and smart electricity grid.Read moreRead less
Safe, Plug and Play, Multi Agent Dynamic Systems. From driverless cars, to networks of nano satellites, and complex biological networks, the modern world has many examples of multi agent dynamic systems that need careful coordination and control to perform correctly. In many cases, these systems are built up using designs based on intuition, computer simulations and empirical testing. However, there is a clear need to advance the fundamental understandings of such systems: (i) Verifiable overall ....Safe, Plug and Play, Multi Agent Dynamic Systems. From driverless cars, to networks of nano satellites, and complex biological networks, the modern world has many examples of multi agent dynamic systems that need careful coordination and control to perform correctly. In many cases, these systems are built up using designs based on intuition, computer simulations and empirical testing. However, there is a clear need to advance the fundamental understandings of such systems: (i) Verifiable overall dynamic system properties need to be derived to give assurance of performance in situations not previously envisaged; (ii) It is also critical to understand stable system behaviours not just with fixed configurations, but with agile configurations such as splitting, merging, and morphingRead moreRead less
Distributed nonlinear control based on differential dissipativity. This project aims to investigate the process control methodologies crucial to smart manufacturing It aims to develop a distributed optimisation-based nonlinear control approach for plant-wide flexible manufacturing, which can achieve time-varying operational targets including production rates and product specifications to meet dynamic market demands. This includes a contraction-based nonlinear distributed control framework that e ....Distributed nonlinear control based on differential dissipativity. This project aims to investigate the process control methodologies crucial to smart manufacturing It aims to develop a distributed optimisation-based nonlinear control approach for plant-wide flexible manufacturing, which can achieve time-varying operational targets including production rates and product specifications to meet dynamic market demands. This includes a contraction-based nonlinear distributed control framework that ensures plant-wide stability at any feasible set-points or references and a distributed economic model predictive control approach that coordinates autonomous controllers to achieve plant-wide economic objectives in a self-organising manner. The outcomes of this project are expected to form a process control framework for next-generation smart plants.Read moreRead less
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.