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
Wavelet approaches for solving nonlinear dynamic systems in process engineering. The success of the proposed project will enable us to obtain more accurate numerical solutions for the nonlinear dynamical systems arising from process engineering. This ensures the potential for understanding and optimising industrial and engineering processes. Hence, a wide range of processing industries in Australia, such as agricultural chemicals, mineral processing, food, detergents, pharmaceuticals, ceramics ....Wavelet approaches for solving nonlinear dynamic systems in process engineering. The success of the proposed project will enable us to obtain more accurate numerical solutions for the nonlinear dynamical systems arising from process engineering. This ensures the potential for understanding and optimising industrial and engineering processes. Hence, a wide range of processing industries in Australia, such as agricultural chemicals, mineral processing, food, detergents, pharmaceuticals, ceramics and specialty chemicals will benefit from the results of this project. This will ensure globally competitive production and, therefore, greater contributions to the Australian economy.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
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
Dynamic Controllability Analysis for Plantwide Process Design and Control. World-wide chemical plants represent many billions of dollars of investment. Improvements to the process designs in terms of controllability would have the potential to provide large economic benefits, as it implies improved productivity, reduced operating costs and product variability. This proposed research will be a step towards integration of process design and control, which has been widely recognized as the key to t ....Dynamic Controllability Analysis for Plantwide Process Design and Control. World-wide chemical plants represent many billions of dollars of investment. Improvements to the process designs in terms of controllability would have the potential to provide large economic benefits, as it implies improved productivity, reduced operating costs and product variability. This proposed research will be a step towards integration of process design and control, which has been widely recognized as the key to this improvement. The outcomes from this project may be readily implemented in process design practice, and therefore have a direct impact to the Australian and world-wide process industries, helping to build a more efficient and environmental conscious Australian process industries.Read moreRead less
Economic Operability Assessment of Leaching Process at Kwinana Nickel Refinery. Process operability is concerned with systematic analysis and improvement of process performance in the face of variable operating conditions. This project will develop a rigorous methodology for analysis of process operability with respect to short-term and transient disturbances. The proposed technique will be applied to the Kwinana Nickel Refinery Leach section, in order to reduce the plant variability and increas ....Economic Operability Assessment of Leaching Process at Kwinana Nickel Refinery. Process operability is concerned with systematic analysis and improvement of process performance in the face of variable operating conditions. This project will develop a rigorous methodology for analysis of process operability with respect to short-term and transient disturbances. The proposed technique will be applied to the Kwinana Nickel Refinery Leach section, in order to reduce the plant variability and increase nickel throughput and plant availability. This can be considered as significant move by a process industry to embrace advanced theoretical developments and will act as a benchmark to promote future links between Australian industry and academia.Read moreRead less
Thermal management of methane fuelled planar solid oxide fuel cells. Solid oxide fuel cells (SOFCs) are novel devices for generating energy with extremely low emissions. This project will conduct novel experiments and numerical simulations to improve the efficiency of SOFCs. This will then allow wider adoption of this technology, thus reducing CO2 and other environmental emissions from our power generation systems.