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
Dissipativity based distributed model predictive control for complex industrial processes. This project will extend and improve the model predictive control technology, which is the most widely used advanced control approach in process industries. The results will potentially benefit the Australian mineral processing industry where many processes are geographically distributed, leading to more cost-effective operation.
Integrated Approach to Plantwide Fault Diagnosis and Fault-tolerant Control. This project aims to develop a new approach to detect and reduce the impact of faults in industrial plants. Operations of modern industrial processes increasingly depend on automatic control systems, which can make the plants susceptible to faults such as sensor/actuator failures. Based on the concept of dissipative systems, the project aims to develop a novel integrated approach to distributed fault diagnosis and fault ....Integrated Approach to Plantwide Fault Diagnosis and Fault-tolerant Control. This project aims to develop a new approach to detect and reduce the impact of faults in industrial plants. Operations of modern industrial processes increasingly depend on automatic control systems, which can make the plants susceptible to faults such as sensor/actuator failures. Based on the concept of dissipative systems, the project aims to develop a novel integrated approach to distributed fault diagnosis and fault-tolerant control for plant-wide processes. It aims to capture the key dynamic features of normal and abnormal processes by their dissipativity properties, and to use these to develop an efficient online fault diagnosis approach based on process input and output trajectories.Read moreRead less
A System Behavioral Approach to Big Data-driven Nonlinear Process Control. This project aims to develop a novel process control approach that utilises big process data to improve the cost-effectiveness of industrial processes. Existing monitoring systems in the industry have been collecting a tremendous amount of process operation data but little effort has been made to use the big process data to enhance process operations. Based on the system behavioural approach and dissipativity theory, inte ....A System Behavioral Approach to Big Data-driven Nonlinear Process Control. This project aims to develop a novel process control approach that utilises big process data to improve the cost-effectiveness of industrial processes. Existing monitoring systems in the industry have been collecting a tremendous amount of process operation data but little effort has been made to use the big process data to enhance process operations. Based on the system behavioural approach and dissipativity theory, integrated with machine learning techniques, this project expects to develop a novel framework for data-driven control using big process data. The outcomes are expected to benefit the Australian process industry, where many processes are controlled by inadequate logic controllers, by improving their operational efficiency.Read moreRead less
Data-based Control of Process Feature Dynamics through Latent Behaviours. This project aims to develop a novel data-based approach to control the feature dynamics of complex industrial processes. The dynamic features of desired process operations (leading to high energy and material efficiencies and good product quality) are often not directly measured but can be distilled from high-dimensional big process data. However, little effort has been made to develop process control approaches to achiev ....Data-based Control of Process Feature Dynamics through Latent Behaviours. This project aims to develop a novel data-based approach to control the feature dynamics of complex industrial processes. The dynamic features of desired process operations (leading to high energy and material efficiencies and good product quality) are often not directly measured but can be distilled from high-dimensional big process data. However, little effort has been made to develop process control approaches to achieve desired dynamic features. This project aims to develop such a data-based approach by controlling latent variable dynamics, using the behavioural systems framework integrated with big data analytics and artificial neural networks. The outcomes are expected to help build a cornerstone for future smart manufacturing.Read moreRead less
Feedback destabilising control of electro-osmotic flow for reducing fouling and enhancing productivity of membrane systems. This project aims to develop a new approach to improving the productivity of membrane systems. With over $9 billion worth of membrane-based desalination plants either in operation, under construction or being planned in Australia, the expected outcomes of this project will lead to significant social and economic benefit and provide greater water security.
Control of Distributed Energy Storage System using Vanadium Batteries. This project aims to develop a new control approach to distributed energy storage at stack, system and microgrid levels, utilising one of the most promising flow battery technologies - vanadium redox batteries. This is the first attempt of a storage centric approach that includes: an integrated approach to design and control of vanadium flow batteries with novel advanced power electronics technologies to achieve optimal charg ....Control of Distributed Energy Storage System using Vanadium Batteries. This project aims to develop a new control approach to distributed energy storage at stack, system and microgrid levels, utilising one of the most promising flow battery technologies - vanadium redox batteries. This is the first attempt of a storage centric approach that includes: an integrated approach to design and control of vanadium flow batteries with novel advanced power electronics technologies to achieve optimal charging/discharging conditions; and, a scalable distributed energy storage and power management approach incorporating energy pricing for storage dispatch that allows distributed autonomous controllers to achieve optimal local techno-economic performance and microgrid-wide efficiency and reliability.Read moreRead less
Numerical and experimental studies of the gas-particle flow and dust collection in electrostatic precipitation systems. This project will generate an integrated computer model to describe the gas-solid flow and dust collection in an ElectroStatic Precipitator (ESP). The model can be used to aid the design and control of ESP systems which are widely used for dust collection, leading to more competitive energy and related industries.
Discovery Early Career Researcher Award - Grant ID: DE120100960
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Simulation and characterisation of the packing of uniform non-spherical particles. The effect of particle shape on the packing of uniform particles is a fundamental problem in the study of granular materials and is also related to other important scientific problems. This project aims to solve this problem by an innovative computer simulation method, using virtual but insightful numerical results to build solid theories.
Commercial scale production of biocrude by hydrothermal liquefaction. The project aims to develop new understanding and tools to support commercial-scale production of biocrude from microalgae or biosolids and enable a breakthrough in cost-effective production of sustainable fuels. A novel hydrothermal liquefaction reactor has been developed that has strong potential to overcome the limitations of Muradel's existing demonstration reactor which, while world-leading, is uneconomical at commercial ....Commercial scale production of biocrude by hydrothermal liquefaction. The project aims to develop new understanding and tools to support commercial-scale production of biocrude from microalgae or biosolids and enable a breakthrough in cost-effective production of sustainable fuels. A novel hydrothermal liquefaction reactor has been developed that has strong potential to overcome the limitations of Muradel's existing demonstration reactor which, while world-leading, is uneconomical at commercial scale. The project aims to develop design tools to optimise the new reactor, comprising a chemical model of the complex, multi-component hydrothermal liquefaction reactions, a computational model of the mixing and heat transfer within it and a network model of the energy and exergy flows.Read moreRead less