Jie BAO Associate Professor
	location	Room 909 F10
	telephone	9385 6755
	facsimile	9385 5966
	email	j.bao@unsw.edu.au
	School of Chemical Sciences and Engineering The University of New South Wales UNSW Sydney, NSW 2052 Australia

Qualifications	Ph.D. Chem. Eng., University of Queensland, 1998 MSc. E.E., Zhejiang University, 1993 BS. E.E., Zhejiang University, 1990
Employment	School of Chemical Engineering & Industrial Chemistry, UNSW, Senior Lecturer 2003 School of Chemical Engineering & Industrial Chemistry, UNSW, Lecturer 1999-2003 University of Alberta, Edmonton, Canada, Postdoctoral Research Fellow, 1998-1999 University of Queensland, Part-time tutor, 1994-1997 Control & Measurement Branch, ZUSTD Corp., Hangzhou, China, Assistant Engineer, 1993-1994
Research Interests	COMPUTER PROCESS CONTROL Integration of process design and control; Fault tolerant control systems; Process control based on the Passivity Theorem; Decentralized process control; Robust control; Process control applications. RESEARCH PROJECTS: 1. Decentralised Failure Tolerant Control (An ARC Large Project ) Based on the Passivity Theorem, this project will develop a new approach to fault-tolerant decentralised control for both linear and control-affine nonlinear processes in a unified framework. Decentralised control is the norm in process industries and as such this project will provide rigorous tools to improve the performance and reliability of such control systems. Analysis methods for decentralised unconditional stability are being investigated and design methods for fault-tolerant high performance controllers are being developed. Theoretical results will be evaluated by experimental case studies of control of a pilot distillation column and a mineral processing pilot plant. This research also provides novel performance analysis tools for decentralised control. Supported by Australian Research Council. (In collaboration with Prof. P.L. Lee, University of South Australia) 2. Dynamic Controllability Analysis for Plantwide Process Design and Control (An ARC Discovery Project) Based on the concept of passive systems, this project aims to develop a new quantitative measure for dynamic controllability for design of plantwide process systems. Integration of process design and control has been widely recognized as an effective approach to improving process performance to meet increased economic, safety and environmental demands. Controllability evaluation plays an important role in this approach. The outcome of this research will be an easy to use controllability analysis method for nonlinear plantwide multi-unit systems, which can be used in early stages of process design to explore better opportunities for process improvements. 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 may have a direct impact to the Australian and world-wide process industries, helping to build a more efficient and environmental conscious Australian process industries. (Supported by the Australian Research Council. In collaboration with Prof. P.L. Lee, University of South Australia) 3. Soft SensorDevelopment for Milling Processes Aided by Discrete Element Models (A FRG project) This project aims to develop a new soft sensor approach for milling processes using discrete element models. Monitoring and control of milling conditions is of considerable interest to industry as grinding is the most energy intensive process in mineral processing. However, direct monitoring of comminution processes is not feasible due to the hostile environment inside the mills. By using the discrete element models of milling processes, key process variables and operating conditions inside the mills are simulated. Using both multivariate statistical methods and the Gaussian process modelling technique, the simulation results are then used to train soft sensor models that can identify online the collision energy and the operating regions in terms of breakage, from surface vibration measured during the milling operation. Supported by a Faculty Research Grant, UNSW (In collaboration with Prof. A.B. Yu and Dr. R.Y. Yang) 4. Advanced Control of Membrane Processes (An ARC Discovery Project) This work aims to develop a dynamic process model and advanced control schemes for pressure driven membrane systems. Current methodologies, while functional, are conservative, narrow and slow and do not take advantage of process improvements achievable with tight active control. The expected outcomes include a validated model, control strategies that maximize productivity and minimize fouling during normal operation as well as during start-up and shut-down. Supported by Australian Research Council. (In collaboration with Prof. D.E. Wiley and Dr. D.J. Clements) RESEARCH FUNDING AWARDED: Studies on Failure-tolerant Decentralised Control based on the Passivity Theorem (Sole Chief Investigator) Australian Research Council (ARC) small grant 2000 Passivity-based Fault-tolerant Decentralized Control for Linear and Nonlinear Processes (First Chief Investigator) Australian Research Council (ARC) large grant 2001-2003 Enhancement of DCS-Centred Process Control Experimental Rig (First chief investigator) Research Infrastructure Block Grant 2000 An Integrated Approach to Modelling and Robust Process Control (Sole Chief Investigator) University Research Support Program (URSP 2002, FRG 2003) 2002-2003 Defining Fundamental Principles for the Design and Operation of Membrane Systems from Time-Varying Performance Analysis (Second Chief Investigator) Australian Research Council (ARC) Discovery Project 2003-2005 Dynamic Controllability Analysis for Plantwide Process Design and Control (First Chief Investigator) Australian Research Council (ARC) Discovery Project 2005-2007 Soft sensor development for milling processes aided by discrete element models (First Chief Investigator) Faculty Research Grant 2007 Interaction analysis and decoupling control of complex processes (Sole Chief Investigator) International Science Linkages: Australia-China Special Fund 2007-2009
Selected Publications	Books Bao, J. and Lee, P.L. (2007) Process Control: The Passive Systems Approach. Springer-Verlag London, ISBN: 978-1-84628-892-0 Journal Publications Yee, K.W., Wiley, D.E. and Bao, J. (2007) Whey protein concentrate production by continuous ultrafiltration: Operability under constant operating conditions. Journal of Membrane Science 290(1/2): 125–137 Chan, K.H. and Bao, J. (2007) Model Predictive Control of Hammerstein Systems with Multivariable Nonlinearities. Ind. & Eng. Chem. Res. 46 (1): 168-180. Rojas, O.J., Bao, J. and Lee, P.L. (2007) A Dynamic Operability Analysis Approach for Nonlinear Processes. J. Process Control 17 (2): 157–172. Alexiadis, A., Wiley, D.E., Fletcher, D.F. and Bao J. (2007) Laminar Flow Transitions in a 2D Channel with Circular Spacers. Ind. Eng. Chem. Res. 46 (16):5387 - 5396. Su, S.W., Bao, J. and Lee, P.L. (2006) A Hybrid Active-Passive Fault Tolerant Control Approach. Asia-Pac. J. Chem. Eng. 1 (1-2): 54-62. Rojas, O.J., Bao, J. and Lee, P.L. (2006) Linear control of nonlinear processes: the regions of steady-state attainability. Ind. & Eng. Chem. Res. 45 (22): 7552 -7565. Chan, K.H., Bao, J. and Whiten, W.J. (2006) Identification of MIMO Hammerstein Systems Using Cardinal Spline Functions. J. Process Control 16 (7): 659–670. Su, S.W., Bao, J. and Lee, P.L. (2006) Conditions on Input Disturbance Suppression for Multivariable Nonlinear Systems on the Basis of Feed Forward Passivity. International Journal of Systems Science 37 (4): 225–233. Yee, K.W., Wiley, D.E. and Bao, J. (2006) Steady state operability of whey ultrafiltration (UF) system. Desalination 199 (1-3): 497-498. Alexiadis, A., Bao, J., Fletcher, D.F., Wiley, D.E. and Clements, D.J. (2006) Dynamic response of a high pressure reverse osmosis membrane simulation to time dependent disturbances. Desalination 191 (1-3): 397–403. Su, S.W., Bao, J. and Lee, P.L. (2006) Decentralized Control for Multivariable Processes with Actuator Nonlinearities. Dev. Chem. Eng. Mineral Process. 14 (1/2): 163-172. Chan, K.H., Bao, J. and Whiten, W.J. (2005) A New Approach to Control of MIMO Processes with Static Nonlinearities Using an Extended IMC Framework. Comput. & Chem. Eng., 30 (2): 329–342. Zhang, W.Z., Bao, J. and Lee, P.L. (2005) Process Dynamic Controllability Analysis Based on All-Pass Factorization. Ind. & Eng. Chem. Res. 44 (18): 7175-7188. Alexiadis, A., Bao, J., Fletcher, D.F., Wiley, D.E. and Clements, D.J. (2005) Analysis of the Dynamic Response of a Reverse Osmosis Membrane to Time Dependent Transmembrane Pressure Variation. Ind. & Eng. Chem. Res. 44 (20): 7823-7834. Su, S.W., Bao, J. and Lee, P.L. (2005) Control of Multivariable Hammerstein Systems by Using Feedforward Passivation. Ind. & Eng. Chem. Res. 44 (4): 891-899 Su, S.W., Bao, J. and Lee, P.L. (2004) Analysis of Decentralized Integral Controllability for Nonlinear Systems. Comput. & Chem. Eng., 28 (9): 1781-1787. Bao, J., Zhang, W.Z. and Lee, P.L. (2003) Decentralized Fault-tolerant Control System Design for Unstable Processes. Chem. Eng. Sci., 58 (22): 5045-5054.Zhang, W.Z., Bao, J. and Lee, P.L. (2003) Control Structure Selection Based on Block Decentralized Integral Controllability. Ind. & Eng. Chem. Res. 42 (21): 5152-5156. Bao, J., Lee, P.L., Wang, F.Y. and Zhou, W.B. (2003) Robust Process Control Based on the Passivity Theorem. Dev. Chem. Eng. Mineral Process, 11 (3/4): 287-308. Bao, J., McLellan, P.J. and Forbes, J.F. (2002) A Passivity-based Analysis for Decentralized Integral Controllability. Automatica 38 (2): 243-247. Zhang, W.Z., Bao, J. and Lee, P.L. (2002) Decentralized Unconditional Stability Conditions Based on the Passivity Theorem for Multi-loop Control Systems. Ind. & Eng. Chem. Res. 41 (6): 1569-1578. Bao, J. W.Z. Zhang and Lee, P.L. (2002) Passivity-Based Decentralized Failure-Tolerant Control. Ind. & Eng. Chem. Res. 41 (23): 5702-5715. Bao, J., Lee, P.L., Wang, F.Y. , Zhou, W.B. and Samyudia, Y. (2000) A New Approach to Decentralized Control Using Passivity and Sector Stability Conditions. Chem. Eng. Commun. 182: 213-237. Bao, J., Forbes, J.F. and McLellan, P.J. (1999) Robust Multi-Loop PID Controller Design - A Successive Semi-Definite Programming Approach. Ind. & Eng. Chem. Res. 38 (9): 3407-3419. Bao, J., Lee, P.L., Wang, F.Y. and Zhou, W.B. (1998) New Robust Stability Criterion and Robust Controller Synthesis. Int. J. Robust Nonlinear Control, 8 (1): 49-59.
Teaching Areas	CEIC3070 Process Control (Lecturer in Charge) CEIC4070 Automation Science (Lecturer in Charge) CEIC6102/8102 Advanced Process Control (Lecturer in Charge) CHEN3021 Process Modelling and Analysis (Co-lecturer, Model analysis part) CHEN3068 Process Design and Safety (Co-lectuer, Process control design module) CHEN3080 Chemical Engineering Lab (Plate heat exchanger) ENGG1000 Engineering Design and Innovation (Project staff)