Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: University of New South Wales Banner

Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: Description: ChSE_homebanner.jpg

 

PROCESS CONTROL GROUP

Welcome to the webpage of the Process Control Group at UNSW. Led by Prof Jie Bao, we work on process system engineering, including dynamic process modelling, control and analysis. Our research is focused on

·        advanced control theory development, including:

§  process control based on dissipativity theory;

§  distributed control;

§  integration of process design and control;

§  fault detection and tolerant control systems;

§  nonlinear control;

§  modelling and control of collective dynamics.

·        process control applications, including:

§  advanced control of membrane systems;

§  fault detection and control of aluminium reduction cells;

§  control of flow batteries;

§  control of coal handling and preparation processes.

PCG 2013

Staff members:

Group Leader:

Professor Jie Bao

Jie

 Professor Jie Bao is an expert in dissipativity/passivity based process control. He has been awarded more than $3.5M competitive research grants including 8 ARC DP/large grants, 1 CSIRO National Flagship Research Cluster Project and a number of industrial projects. He published extensively in major process control and chemical engineering journals. He is an Associate Editor of Journal of Process Control (an International Federation of Automatic Control affiliated journal).

 

School of Chemical Engineering

The University of New South Wales

UNSW SYDNEY NSW 2052

Australia

Telephone: +61 (2) 9385 6755

Facsimile: +61 (2) 9385 5966

Email: J.Bao@unsw.edu.au

Researchers:

Dr. Michael Tippett

Adjunct Lecturer

 

Tippett

Michael J. Tippett received a B.E. in Industrial Chemistry/B. Com. in Business Economics with first class Honours and the University Medal from the University of New South Wales (UNSW), Sydney, Australia in 2009.  He completed his PhD study in 2013 in the area of distributed control systems in the School of Chemical Engineering at UNSW.  His current research interests include:  distributed and decentralized control, adaptive control, model predictive control, dissipativity-based analysis and control and their applications to chemical processes.

 

 

Dr. Ruigang Wang

Research Associate

 

bio

Dr. Ruigang Wang received a B.E. in Automobile Engineering from Beihang University, Beijing, and an M.E. in Mechanical Engineering from Shanghai Jiaotong University, Shanghai, China,  in 2009 and 2012, respectively. He was awarded the PhD degree in Chemical Engineering in The University of New South Wales, Sydney, Australia, in 2017. His research interests include contraction theory, dissipativity theory, model predictive control, distributed control, fault detection and diagnosis..

 

 

Dr. Yuchen Yao

Research Associate

 

image1 

Yuchen Yao received a B.E. in Chemical Engineering with first class Honours from the University of New South Wales (UNSW), Sydney, Australia. He is expected to be rewarded his PhD in 2017 in the area of advanced control and monitoring in aluminium smelters from UNSW. His current research include data analysis, modelling, monitoring, fault detection and fault diagnosis of industrial processes.

Postgraduate Research Students

Research students

Candidature

Project

Qingyang Lei

PhD candidate

Dissipativity Based Fault Detection

Md Parvez Akter

PhD Candidate

Advanced Control of Distributed Energy Storage Systems

Steven (Yifeng) Li

PhD Candidate

Advanced Control of Vanadium Redox Batteries

Jing Shi

PhD Candidate

Advanced Control of Aluminium Smelting Cells

Yitao Yan

PhD candidate

Dissipativity Based Fault Tolerant Control

 

CURRENT/RECENT RESEARCH PROJECTS:

§  An Integrated Approach to Distributed Fault Diagnosis and Fault-tolerant Control for Plantwide Processes (ARC Discovery Project: DP160101810, 2016-2018)

Modern industrial processes are very complex, with distributed process units via a network of material and energy streams. Their operations increasingly depend on automatic control systems, which can make the plants susceptible to faults such as sensor/actuator failures. Occurrence of faults is increased by the common practice to operate processes close to their design constraints for economic considerations. This project will develop a new approach to detect and reduce the impact of these faults, which can cause significant economic, environment and safety problems.

Based on the concept of dissipative systems, this project aims to develop a novel integrated approach to distributed fault diagnosis and fault-tolerant control for plantwide processes. The key dynamic features of normal and abnormal processes are captured by their dissipativity properties, which are used to develop an efficient online fault diagnosis approach based on process input and output trajectories, without the use of state estimators or residual generators. Using the dissipativity framework, a distributed fault diagnosis approach will be developed to identify the locations and faults in a process network. A distributed fault tolerant control approach will be developed to ensure plantwide stability and performance.

Supported by the Australian Research Council. In collaboration with Profs. M. Skyllas-Kazacos, and V.G. Agelidis.

§  Control of Distributed Energy Storage System using Vanadium Batteries (ARC Discovery Project: DP150103100, 2015-2017)

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 (1) an integrated approach to design and control of Vanadium flow batteries with novel advanced power electronics technologies to achieve optimal charging/discharging conditions and (2) 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.

Supported by the Australian Research Council.

§  Dissipativity based Distributed Model Predictive Control for Complex Industrial Processes (ARC Discovery Project: DP130103330, 2013-2015)

Based on the behavioural approach to systems and dissipativity theory, this project aims to integrate nonlinear control theory with distributed optimization to develop a novel distributed predictive control approach for complex industrial processes. In this approach, the global objectives (i.e., the plantwide stability and performance) are converted into the local constraints of dissipativity conditions for non-cooperative optimization performed in the distributed controllers. The outcomes will include a framework and the fundamental control theory for distributed autonomous model predictive control that achieves improved scalability, flexibility and robustness compared with existing distributed predictive control approaches.

Supported by the Australian Research Council. In collaboration with Dr. Jinfeng Liu, University of Alberta.

§  Plantwide Control of Modern Chemical Processes from a Network Perspective (ARC Discovery Project: DP1093045, 2010-2012)

To achieve high economical efficiency, modern chemical plants are becoming increasingly complex, to an extent that cannot be effectively managed by existing process modelling and control techniques. By exploring the physical fundamentals in thermodynamics and their connections to control theory, this project aims to develop a new modelling and control approach that can be applied to complicated nonlinear processes. In this approach, processes over the entire plant are analysed and controlled from a network perspective using the dissipativity control theory. The outcomes of this project will form the cornerstones of a new process control paradigm that offers more robust and reliable process operation at any scale.

Supported by the Australian Research Council. In collaboration with Prof. Erik Ydstie, Carnegie Mellon University.

§  Advanced Control of Membrane Processes (ARC Discovery Project: DP110101643, 2011-2013)

Fouling reduces throughput and productivity of membrane systems and as such increases operating costs and reduces profitability of water treatment industries. This work aims to reduce membrane fouling by reducing the amount of solute at the membrane surface. This is achieved by implementing destabilizing electro-osmotic flow control. The significance of this project lies in linking feedback control of electro-osmotic effects with spacer design to maximize flow instabilities. This project will advance modelling of flow in membrane channels and develop a novel feedback flow control strategy that enhances mixing. The effectiveness and operability of the new fouling reduction approach on real-world membrane systems will be evaluated.  With over $9bn 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 economical benefit and provide greater water security.

Supported by the Australian Research Council. In collaboration with Prof. D.E. Wiley and Dr. Alessio Alexiadis, Washington University in St. Louis)

§  Anode Current Distribution Monitoring and Analysis (DUBAL, 2013-2015)
Supported by Dubai Aluminium Company. In collaboration with Prof. M. Skyllas-Kazacos and B. J. Welch.

§ Advanced Control of Aluminium Smelting Cells (CSIRO National Research Flagship Project, 2009-2012)

Primary production of aluminium is highly energy intensive, with energy costs representing 22-36% of operating costs in smelters. The Australian aluminium smelting industry consumed 29,500 GWh of electricity in 2007, 13% of final electricity consumption in Australia. The long term sustainability of the aluminium smelting industry depends on energy-efficient production technologies for global competitiveness. The aim of the project is to improve auto-diagnosis of the occurrence of the root-cause for abnormal process conditions in the smelting cells that adversely impact energy and environmental efficiencies. The expected outcomes include: (1) An adaptive model for the change in control signal and control algorithms with different abnormalities and at different operating line current levels; (2) A sequence of diagnostic sub-routines based on processing signals at different; (3) A schemes for alarms and guidelines for human interface interaction when needed.

Supported by CSIRO National Research Flagships Light Metal Flagship Cluster. In collaboration with Profs. B.J. Welch and M. Skyllas-Kazacos.

§  Advanced Dynamic Control for Paste Thickeners (ACARP Project: C21055, 2012-2013)

The objective of this project is to develop an online dynamic feedback control approach to improve the operation of paste thickeners through adopting modern control strategies (in particular, model predictive control) already successfully applied in the petro-chemical industry. This would be an ideal test case for applying advanced dynamic control for complete CHPPs or other variable dynamic processes such as flotation.

Supported by Australian Coal Association Research Program. In collaboration with Dr. Goezt Bickert, GBL Process Pty Ltd.