Hong Wang

Hong Wang

Senior Distinguished R&D Staff, Fellow of IET, InstMC, IEEE and AIAA, Professor (EM) - University of Manchester (UK)

Dr Hong Wang received the BSc degree in Electrical Engineering from Huainan Institute of Mining Engineering (Huainan Mei Tan Xue Yuan) in 1982, and master and doctorate degrees with distinguished grade in process control and power plant engineering from the Huazhong University of Science and Technology (Huazhong Gong Xue Yuan, a top 10 Chinese University), Wuhan, China, in 1984 and 1987, respectively. He moved to UK in 1988 and was a postdoc Research Fellow with Salford University (Salford, UK), Brunel University (Uxbridge, UK) and Southampton University (Southampton, UK) before joining the University of Manchester Institute of Science and Technology (UMIST), Manchester, U.K., in 1992 as a lecturer in process control. He was then promoted to senior lecturer and reader in 1997 and 1999, respectively at UMIST. Wang was a Chair Professor in Process Control of complex industrial systems at the University of Manchester (a top 25 university in world ranking) from 2002 to 2016, where he was the deputy head of the Paper Science Department 1997 - 2002, director of the UMIST Control Systems Centre between 2004 - 2007 (which is the birthplace of Modern Control Theory established in 1966). He was University Senate member and a member of general assembly for many years during his time in Manchester.

Between 2016 – 2018, he was with Pacific Northwest National Laboratory, US Department of Energy (PNNL, Richland, WA, USA) as a Laboratory Fellow  and Chief Scientist (https://www.pnnl.gov/people/hong-wang ) , and was the co-leader and chief scientist for the Control of Complex Systems Initiative (https://www.pnnl.gov/people/hong-wang).

Professor Hong Wang joined Oak Ridge National Lab at corporate fellow grade (Comp Title/Job) in January 2019.  He is currently leading several projects from four offices in US Department of Energy on transportation systems (VTO), hydropower systems (WPTO), power grid control (OE) and manufacturing systems (AMO).

Research Contributions:

Professor Hong Wang's control research interests include stochastic distribution control, fault detection and diagnosis, nonlinear control, and data-based modeling for complex systems including industrial processes and transportation systems. Brief descriptions are as follows:    

1) Stochastic distribution control theory and stochastic optimization: Professor Hong Wang originated the theory on stochastic distribution control (SDC) in 1996, where the main purpose of control input design is to make the shape of the output probability density functions to follow a targeted function for general non-Gaussian dynamic systems. This has been regarded as a novel stochastic control theory that has found a wide spectrum of applications in general modeling, data mining, filtering design and optimization for uncertain systems. This theory also provides effective tools for solving decision-making problems for systems subjected to uncertainties, and how the impact from uncertainties can be minimized during the decision -making phase (https://onlinelibrary.wiley.com/doi/full/10.1002/oca.2755).

Indeed, Wang has initiated the shaping of probability density function of cost function and constraints in stochastic optimization - which pioneers a total solution to generic stochastic optimization problems, where the decision variables are selected to control the cost function PDF to make it as narrow and as left as possible - leading to a robust and reliable optimization effect in comparison with the existing stochastic optimization which only minimum the mean of the cost function.  His book chapter titled "Decision-Making for Complex Systems Subjected to Uncertainties — A Probability Density Function Control Approach" will appear in the forthcoming SpringerLink book titled " Handbook of Reinforcement Learning and Control" in 2021 following his invited paper published at 2018 IEEE 14th International Conference on Control and Automation (ICCA) titled "Objective pdf-shaping-based economic dispatch for power systems with intermittent generation sources via simultaneous mean and variance minimization".

2) Neural Networks: Professor Wang has been working on the field of neural network based adaptive learning control systems since 1993, where at first he developed direct adaptive neural network (NN) controls for generic unknown nonlinear systems using multiple layer perceptron (MLP) neural network to learning the unknown dynamics of the system, and using online learnt NN models to obtain the NN controller with rigorous closed loop system performance analysis. Motivated by the challenges that most unknown systems are subjected to random uncertainties, he further originated the work on stochastic distribution control (SDC), where the B-spline NN was used to learn output probability density functions (PDF) and the NN weights are learnt via a state space dynamic structure that aims at controlling the output PDF of the system rather than just controlling the output mean and variance commonly used in traditional stochastic control theory. This allows  effectively decoupling the time- and space-domain variables in obtaining practically real-time implementable output PDF control through learning. Wang’s theory on SDC has been successfully applied to several industrial processes including paper-making processes (Arjo-Wiggins, Iggesund Paper Board, Georgia Pacific, etc) and blast furnace in steel making , where significant impact on the system optimized operation has been achieved. Indeed, before moving to USA in 2016, Hong Wang had been working on advanced adaptive control and intelligent controls using artificial neural networks and neuro-fuzzy tools for unknown nonlinear systems with applications on several practical systems such as hydropower generation and pH controls in chemical plant, where hydro-turbine speed control and generator excitation control have been developed. He has published more than 100 journal papers and a book (Advanced Adaptive Control, Pergamon Press, 1996) in these area. 

3) Fault diagnosis and tolerant controls: Professor Hong Wang has also been working on fault diagnosis and tolerant controls since 1989. He originated the theory of using adaptive control tuning mechanism to perform fast fault diagnosis for dynamic systems (https://ieeexplore.ieee.org/abstract/document/508919), and the collaborative fault tolerant control for complex dynamic systems composed of multi-agent subsystems. This area of research has led to his plenary talk at the 2018 IFAC Safeprocess Conference in Warsaw (which is the largest conference on process safety taking place once every three years per organized by the International Federation of Automatic Control (IFAC)), and contribution of a chapter titled "Stochastic Fault Detection" for  the Encyclopedia of Systems and Control.

4) {max, +} Algebra Based System integration and Human-in-loop systems: In 2010, he originated the use of {max, +} algebra for the integrated modelling of complex systems (https://ieeexplore.ieee.org/abstract/document/6160654) and discovered the square root impact principle that provides consolidated foundation for the mathematical understanding of integration between industrialization and advanced information Technology (IT). Along this new research direction, he has developed novel quantitative description of human-in-loop systems using Brain to Computer Interface (BCI) techniques and has received best paper awards on this. When he was with the University of Manchester, he acted as one of the themes leader for the first ever biggest mathematic initiative funded by the UK research council (EPSRC) titled "Centre for Interdisciplinary Computational and Dynamical Analysis" on Analysis of Adaptive Systems and Control - developing hybrid system modeling and control using tropical algebra. The initiative represents research collaboration among Manchester Math, Computing (where the world first computer was born) and Control systems.            

5) Nonlinear Control and Robotics: Professor Wang developed a unified framework based control design for generic nonlinear systems with known dynamics, where it has been shown that a time-varying control with flexible structure can be used to control any nonlinear systems with the required adaptive tuning of control parameters (H. Wang, Y. Wang and P Kabore, Time-varying controller for known nonlinear dynamic systems with guaranteed stability, International Journal of Systems Sciences, Vol. 33, pp. 931 – 938, 2002).  In addition, he has also unified Lyapunov stability analysis with optimal control by taking the objective function as a Lyapunov function candidate - this allows simultaneous optimization with guaranteed stability for closed loop control systems.  The work has been applied to the design of robotic systems, where new tracking criteria (tracking error probability density functions and entropy) has been developed to obtain better tracking control of robotic systems with respect to their trajectories.

6) Modelling and Control for Transportation Systems: Since moved to USA in Feb 2016, Hong Wang has started and focused his research on transportation system modelling and control. In terms of transportation research funded by the US Department of Energy (under SMART Mobility and ARPA - E nextCar projects), Hong Wang has initiated the following work

  •  Using stochastic distribution controls to realize the control of multiple intersections for a networked traffic flow, where the idea is to develop signal timing controls that ensure the uniform distribution of traffic flows over the concerned urban area so as to achieve smooth traffic flow with minimized energy consumption.            
  • At vehicle level, Hong Wang has developed some novel integrated powertrain and aftertreatment controls that use vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) information to optimally tune the controller parameters using functional optimization theory so as to reduce the fuel consumption.


Publication Summary

Professor Hong Wang has the following publication profile:

  • Hong Wang has published more than 200 refereed journal papers in international/national journals (e. g., IEEE Transaction on Automatic Control, IFAC Automatica, IEEE Transactions on Neural Networks and Learning Systems, Int. J.  Contr, ASME, Trans M&C, Int. J.  Sys. Science and IEE/IMEchE Journals, etc);
  • He has also been invited to publish 18 journal papers; 
  • Hong Wang has presented 44 invited/plenary papers and 170 refereed papers in international congresses/conferences (i. e., IFACs, ACCs, CDCs, IEEE CCAs and IMAC, etc); 
  • Hong Wang has published 7 books (one by HUST Press Ltd in 1988,  one by  Pergamon Press in 1995, the other by Pira international in 1997 and two by Springer-Verlag in 2000 and 2010, respectively) and contributed to 6 book chapters ; 
  • Hong Wang has been invited to give seminars to more than 60 universities/industrial companies,  where with all expenses paid.
  •  https://www.ornl.gov/news/predicting-unpredictable-hong-wang-applies-no…

Major Prizes/Awards: Professor Hong Wang has received 10 prizes and awards for his work in these areas, including 

  • Jasper Mardon Memorial Prize for significant contribution to the science and technology development in paper-making at PITA Annual Conference, Bradford, 2006 (UK) - top prize in the international paper industry community;
  • Best paper prize at the International Conference on Control 2006, Glasgow (UK);
  • Finalist for the International Federation of Automatic Control (IFAC) World Congress Application Paper Prize, Cape Town, 2014, the conference had 2000 attendees and is the largest international control event once every three years in international automatic control community;
  • Best theory paper award for World Congress on Intelligent Control and Automation,  2014;
  • Best paper award from The Tenth International Conference on Advances in Vehicular Systems, Technologies and Applications, France, 2021;


1982: BSc from Huainan University of Mining Engineering (Huainan Meitan Xue Yuan) - Huainan, P R China

1984: MSc from Huazhong University of Science and Technology - Wuhan, P R China

1987: Distinguished PhD, Huazhong University of Science and Technology (Huazhong Gong Xue Yuan) - Wuhan, P R China

2024 IEEE Fellow Committee Member

International Activities:

Professor Hong Wang is a fellow of IEE (now IET), fellow of Institute of Measurement and Control, fellow of IEEE and Fellow of AIAA.

He was the associate editor for leading control journals

1) IEEE Transactions on Automatic Control (2002 - 2004),

2) IEEE Transactions on Control Systems Technology (2013 - 2019) and

3) IEEE Transactions on Automation Science and Engineering (2013 - 2019).

4) IEEE Transactions on Neural Networks and Learning Systems (2022 - ).

Hong Wang is an editorial board member for other 7 international journals, and is the member of the following 3 technical committees of International Federation of Automatic Control (IFAC).

  • Stochastic Systems Technical Committee;
  • Adaptive and Learning Systems Technical Committee
  • Fault Detection, Supervision & Safety of Technical Processes-SAFEPROCESS Technical Committee

Over the past decades he has been actively involved in international activities such as chair/co-chairs of international conferences and IPC member for many conferences. 

Wang was the member of the executive committee for the UK Automatic Control Council (UKACC) and the honorary treasurer for UKACC when he was in UK, and member of EPSRC (NSF equivalent) college member. He was the general conference chair for the international conference on Control'2008, which is the largest conference series of UKACC taking place once every two years. He was also the program chair for the 2014 World Congress on Intelligent Control and Automation which attracted more than 1000 attendees worldwide.

Hong Wang was a member of Advanced Controls working group of the Paper Industry Technical Association (UK)

1) Hong Wang is a Professor emeritus of the University of Manchester (UK) - a life-time title (https://www.eee.manchester.ac.uk/about/people/academic-and-research-sta… and https://research.manchester.ac.uk/en/persons/hong-wang).        

2) Adjunct Professor with the School of Civil and Environmental Engineering at the University of Washington (Seattle),  

3) Adjunct Professor with the School of Civil and Environmental Engineering at the University of Hawaii at Manoa (Honolulu)