Conference (Flyer)
7-8 Dec 2017

Conference proceedings are available.

Workshop (Flyer)
5-6 Dec 2017


Keynote speakers

David Limebeer (University of Oxford, UK)

(PDF of presentation)


The use of orthogonal collocation methods in the solution of various optimal control problems relating to Formula One racing will be discussed. These methods can be used to optimise driver controls such as the steering, brakes and throttle, and optimise vehicle setup parameters such as the aerodynamic down force distributions, the suspension system and the engine maps. Of particular interest is the optimal usage of on-board energy recovery systems. The lecture will focus on the control of the hybrid kinetic-thermal energy recovery systems known as (ERS-K) and (ERS-H) that have been introduced into Formula One racing for the 2014 season. It is demonstrated that these systems, when properly controlled, can produce contemporary lap time using approximately two thirds of the fuel required by legacy (2013 and earlier) vehicles.

David J. N. Limebeer received the B.Sc. (Eng.) degree from the University of the Witwatersrand, Johannesburg, South Africa, in 1974, the M.Sc. (Eng.) and Ph.D. degrees from the University of Kwazulu-Natal, Durban, South Africa, in 1977 and 1980, respectively, and the D.Sc. (Eng.) degree from the University of London, London, U.K., in 1992. He was a Post-Doctoral Researcher at the University of Cambridge, Cambridge, U.K., from 1980 to 1984. In 1984 he joined the Department of Electrical and Electronic Engineering, Imperial College London, London, as a Lecturer. He was promoted to Reader in 1989, Professor in 1993, Head of the Control Group in 1996, and was Head of the Department of Electrical and Electronic Engineering from 1999 to 2009. In 2009, he became Professor of Control Engineering and a Professorial Fellow with New College Oxford, Oxford, U.K. His consultancy activities have been in a variety of vehicle-related matters, product liability litigation, and patent disputes in optical recording systems, drilling equipment, and high-speed packing machines. He is currently interested in a variety of problems in multibody mechanics and the dynamics of two- and four-wheeled road vehicles. His current research interests include a range of applied and theoretical problems in control systems and engineering dynamics, including robust control, optimal control, process control, and the control of aeroelastic phenomena in large structures. In 1992 he was elected Fellow of the Institute of Electrical and Electronic Engineers, “For contributions to multivariable systems theory.” He is also a fellow of the Institution of Engineering and Technology (1994), a fellow of the Royal Academy of Engineering (1997), and a fellow of the City and Guilds of London Institute (2002

Babatunde Ogunnaike (University of Delaware, US)

The mammalian organism maintains stable, efficient and “near-optimal” performance and homeostasis in the face of external and internal perturbations via distinct biological systems ranging from the large-scale physiological (nervous, endocrine, immune, circulatory, respiratory, etc.), to the cellular (growth and proliferation regulation, DNA damage repair, etc.), and the sub-cellular (gene expression, protein synthesis, metabolite regulation, etc). “Biological Control Systems,” a sub-topic of Control Theory, arises from a control engineering perspective of the function, organization, and coordination of these multi-scale biological systems and the control mechanisms that enable them to carry out their functions effectively.

In this presentation, we will provide an overview of how physiological life is made possible by control, and demonstrate the usefulness of a control engineering perspective of pathologies for diagnosis, design, and implementation of effective treatments. The concepts and principles will be illustrated using three specific examples with significant research and clinical implications: Ca++ Regulation; TGF-β and prostate cancer; and Platelet Deficiency Control.

The Ogunnaike group is interested in understanding the dynamic behavior of complex systems through mathematical modeling and analysis, and then exploiting this understanding for postulating novel designs and improved operation. Specific systems of interest range from polymer reactors, particulate processes and extruders, to biological processes at the cellular and physiological levels. Specific research topics include modeling and control of industrial processes (polymer reactors, extruders, distillation columns); the application of process analytical technology for control of pharmaceutical processes; modeling and control of hybrid renewable energy systems; biological control systems; and systems biology with application to neuronal responses and cancer.

Dr Ogunnaike is the author or co-author of more than 100 peer-reviewed publications, and four books including a widely used textbook, Process Dynamics, Modeling and Control, published in 1994 by Oxford University Press, and Random Phenomena: Fundamentals of Probability and Statistics for Engineers, published in 2009 by CRC Press. He is an Associate Editor of the journal Industrial and Engineering Chemistry Research. His awards include the American Institute of Chemical Engineers 1998 CAST Computing Practice Award, the 2004 University of Delaware’s College of Engineering Excellence in Teaching award, the 2007 ISA Eckman Award, and the 2008 AACC Control Engineering Practice award. He was named a fellow of the American Institute of Chemical Engineers (AIChE) in 2009, and elected to fellowship of the Nigerian Academy of Engineering in 2012, of the US National Academy of Inventors in 2014. He is a 2016 fellow of the American Association for the Advancement of Science (AAAS) and a 2017 fellow of International Federation of Automatic Control (IFAC). He was elected to the US National Academy of Engineering in 2012.

Bozenna Pasik-Duncan, (University of Kansas, US)

Stochastic adaptive control denotes the control of a partially known stochastic system. While stochastic models are developed from physical systems, typically some parameters of the model are unknown but the systems have to be controlled. Thus there is a problem of stochastic adaptive control. A solution to it consists of parameter estimation and control. The noise processes for the models include some that have been empirically identified in cognition, that is, fractional Brownian motions. Stochastic control and stochastic adaptive control problems are described for systems with a noise modeled by fractional Brownian motions and other stochastic processes. Applications of stochastic adaptive control include telecommunication, biomedicine, and finance. One can also view education in the STEM subjects as a problem of adaptive control. The learning process is stochastic and there are some well-defined objectives. A major question is how to achieve success for such a problem. The methods from theoretical aspects of stochastic adaptive control have been also applied to the educational processes in STEM.

Bozenna Pasik-Duncan received her Master’s degree in Mathematics from the University of Warsaw in 1970, and Ph.D. and D.Sc. (Habilitation) degrees from the Warsaw School of Economics (SGH) in Poland in 1978 and 1986, respectively. Before moving to the University of Kansas (KU) in 1984, she was a faculty member of the Department of Mathematics at SGH. At KU she is a Professor of Mathematics, a Courtesy Professor of both Electrical Engineering and Computer Science (EECS) and Aerospace Engineering (AE), and an Information & Telecommunication Technology Center (ITTC) Investigator, a Chancellors Club Teaching Professor, and a member of the KU Women’s Hall of Fame. She is a Fellow of IEEE, a Fellow of IFAC, a recipient of the IEEE Third Millennium Medal, and IEEE Control Systems Society (CSS) Distinguished Member Award. She has served in many capacities in several societies including IEEE CSS Vice President, IEEE CSS BoG member, and Program Director of SIAM Activity Group on Control and Systems Theory. Her current service includes Deputy Chair of the CSS TC on Control Education, Chair of the AACC Education Committee, a member of the IFAC TB as the Education Liaison, 2017 Chair of IEEE WIE Committee, a member of the IEEE CSS BoG and IEEE SSIT BoG, and a member of the SIAM Activity Group on Control and Systems Theory Conference Steering Committee.

She is founder of Women in Control (WIC), first chair of IEEE CSS Standing Committee on WIC and member of WIC Advisory Board, founder and faculty advisor of Association for Women in Mathematics (AWM) Student Chapter at KU, founder and coordinator of the MAM/ Outreach Program at KU, and founder and chair of Stochastic Adaptive Control Seminar at KU. She is an Associate Editor of several Journals, and an author and co-author of over 200 technical papers and book chapters. Her research interests are primarily in stochastic systems and stochastic adaptive control, and in STEM education. She has been an organizer and co-organizer of many workshops and control conferences. She is a recipient of many awards including IREX Fellow, NSF Career Advancement Award, KU Women of Distinction, Service to Kansas, H.O.P.E., Kemper, L. Hay, Morrison, Price, Polish Ministry of Higher Education Award, and recently received the 2016 IEEE EAB Meritorious Achievement Award in Continuing Education.

Guanrong Chen (City University of Hong Kong, Hong Kong)

(PDF of Presentation)

In this talk, we discuss the complete state controllability of networked higher-dimensional linear time-invariant dynamical systems interconnected by directed and weighted higher-dimensional channels. We show how the network topology, node-system dynamics, external pinning control inputs, and inner interactions affect the controllability of such a complex dynamical network. We present precise necessary and sufficient conditions for the network controllability in a general setting, as well as in some special configurations with more subtitle analysis.

Professor Chen has been a Chair Professor and the Director of the Centre for Chaos and Complex Networks at the City University of Hong Kong since 2000, prior to that he was a tenured Full Professor at the University of Houston, Texas, USA. He was awarded the 2011 Euler Gold Medal, Russia, and conferred Honorary Doctorates by the Saint Petersburg State University, Russia in 2011 and by the University of Le Havre, France in 2014. He is a Fellow of the IEEE (1997), a Member of the Academy of Europe (2014), and a Fellow of The World Academy of Sciences (2015). He is a Highly Cited Researcher in Engineering as well as in Mathematics according to Thomson Reuters.

Thokozani Majozi (University of the Witwatersrand, South Africa)

(PDF of Presentation)

The lecture provides background on optimization and its applications in process systems engineering. A particular emphasis is placed on time dependent processes, the so-called batch chemical processes. These operations remain elusive to traditional optimization techniques, due to their structural complexity. In essence, it has been proven that these operations are NP-Hard, thereby rendering a search for global optimality largely impractical for real-life problems. This has led to most researchers resorting to heuristic, stochastic and evolutionary optimization techniques.

In its ultimate analysis, the lecture dwells on two areas in which process systems engineering has been applied with great success. The first area involves synthesis, design and optimization of batch chemical facilities using a robust scheduling framework. The second area pertains to optimization of integrated water and membrane network systems. These systems are characterised by intensive energy requirements as they seek to minimize overall freshwater use and wastewater generation. Consequently, the idea is to simultaneously optimize these inherently complex systems in terms of both energy and water requirements.

Thokozani Majozi is a full professor in the School of Chemical and Metallurgical Engineering at Wits University where he also holds the NRF/DST Chair in Sustainable Process Engineering. His main research interest is batch chemical process integration, where he has made significant scientific contributions that have earned him international recognition. Some of these contributions have been adopted by industry. Prior to joining Wits, he spent almost 10 years at the University of Pretoria, initially as an associate professor and later as a full professor of chemical engineering. He was also an associate professor in computer science at the University of Pannonia in Hungary from 2005 to 2009. He spent his early years of his professional career as a chemical engineer working for Unilever, Dow AgroSciences and Sasol Technology. Majozi completed his PhD in Process Integration at the University of Manchester Institute of Science and Technology in the United Kingdom. He is a member of Academy of Sciences of South Africa and a Fellow for the African Academy of Sciences. He has received numerous awards for his research including the Burianec Memorial Award (Italy), S2A3 British Association Medal (Silver) and the South African Institution of Chemical Engineers Bill Neal-May Gold Medal. He is also twice a recipient of the NSTF Award and twice the recipient of the NRF President’s Award. Majozi is author and co-author of more than 150 scientific publications, including 3 books in Batch Chemical Process Integration published by Springer and CRC Press.  .

Tianyou Chai (Northeastern University, China)

China has abundance of mineral resources such as magnesite, hematite and bauxite, which constitute a key component of its economy. The relatively low grade, and the widely varying and complex compositions of the raw extracts, however, pose difficult processing challenges including specialized equipment with excessive energy demands. The energy intensive furnaces together with widely uncertain features of the extracts form hybrid complexities of the system, where the existing modeling, optimization and control methods have met only limited success. Currently, the mineral processing plants generally employ manual control and are known to impose greater demands on the energy, while yielding unreasonable waste and poor operational efficiency. The recently developed Cyber-Physical System (CPS) provides a new key for us to address these challenges. The idea is to make the control system of energy intensive equipment into a CPS, which will lead to a smart optimization control system.

This talk presents the syntheses and implementation of a smart optimization control system for energy-intensive equipment under the framework of CPS. The proposed smart optimization control system consists of three main functions: (i) process control; (ii) setpoint optimization control; and (iii) fault diagnosis and self-recovery control. The key in realizing the above functions is the algorithm structure which is able to integrate control, optimization, fault diagnosis and self-recovery control together seamlessly.  This talk introduces the algorithm structure for integrated implementation of setpoint optimization control, process control and fault diagnosis and self-recovery control.

Hardware and software platform of smart optimization control system for energy-intensive equipment is then briefly introduced, which adopts embedded control system, wireless network and industrial cloud. It not only realizes the functions of computer control system using DCS (PLS), optimization computer and fault diagnosis computer, but also achieves the functions of mobile and remote monitoring for industrial process.

Then, using fused magnesium furnace as an example, a hybrid simulation system for smart optimization control system for energy-intensive equipment developed by our team is introduced. The results of simulation experiments show the effectiveness of the proposed method that integrates the process control, setpoint optimization control and fault diagnosis and self-recovery control in the framework of CPS.

The industrial application of the proposed smart optimization control system is also discussed. It has been successfully applied to the largest magnesia production enterprise in China, resulting in great returns. Finally, future research on the smart optimization control system is outlined.

Tianyou Chai was born in Lanzhou, Gansu Province, China. He received the B.A. degree in automation from Northeastern University of Electric Power, Jilin, China in 1980, the M.S. and Ph.D. degrees in control theory and engineering in 1983 and 1985, respectively, from Northeastern University, China.

Since 1985, he has been with the Center of Automation at Northeastern University, where he became a Professor in 1988 and a chair professor in 2004. He serves as a director of The National Engineering and Technology Research Center of Metallurgical Automation since 1997; director of Key Laboratory of Integrated Automation of Process Industry, Ministry of Education since 2003; director of Department of Information and Science of National Natural Science Foundation of China since 2010; chair of Expert Advisory Committee of National Natural Science Foundation of China since 2011;  director of The State Key Laboratory of Synthetical Automation for Process Industries since 2011; Chair of Academic committee of Northeastern University since 2011. In 2003, he was elected as a member of Chinese Academy of Engineering.

He is a Fellow of IFAC and IEEE. He has served as Member of Technical Board of IFAC and Chairman of Coordinating Committee on Manufacturing and Instrumentation of IFAC from 1996 to 1999, a member of Chinese National Disciplinary Appraisal Group since 1992, and a Vice-Director of Committee of Experts of Advanced Manufacturing and Automation in National 863 High-Tech Program from 2001-2006.

His main research interests are in modeling, control, optimization and integrated automation of complex industrial processes. He has served extensively as a consultant to industry and government. He has authored or coauthored 3 books, more than 460 technical articles including 180 peer reviewed international journal papers and 280 international conference papers. He received several best paper awards. His paper titled Hybrid intelligent control for optimal operation of shaft furnace roasting process was selected as one of three best papers for the Control Engineering Practice Paper Prize for 2011-2013. He holds 14 patents. He has been invited to deliver 52 plenary speeches on international conferences including 22 in IFAC and IEEE hosted conferences.
He has developed control technologies with applications to various industrial processes. For his contributions, he has won 4 prestigious awards of National Science and Technology Progress and National Technological Innovation from China, the 2002 Technological Science Progress Award from Ho Leung Ho Lee Foundation, the 2007 Industry Award for Excellence in Transitional Control Research from IEEE Multiple-conference on Systems and Control and the 2010 Yang Jia-Chi Science and Technology Award from Chinese Association of Automation.