Stochastic Distribution Control and Its Applications
Abstract: Complex systems seen either in general engineering practice or economics are subjected to ever increased uncertainties that are mostly represented as random variables or parameters, and the characteristics of random variables are represented by their probability density functions (PDFs). Controlling their PDFs means to shape their stochastic distributions and in general it would provide a full treatment for system analysis and operational control and optimization. This leads to the development of stochastic distribution control (SDC) systems theory in the past decades, where the original aim of the controller design is to realize a shape control of the distributions of certain random variables in their PDFs sense for some engineering processes. Indeed, once the PDFs of these random variables or parameters are used to describe their distribution characters, the control task is to obtain control signals so that the output PDFs of stochastic systems are made to follow their target PDFs.
The subject of SDC was initially originated for non-Gaussian stochastic control systems design but has found a wide spectrum of applications in general systems in terms of data-driven modeling, analysis, signal processing (filtering), data mining via multivariable statistics, decision-making (optimization) for systems subjected to uncertainties and even in economics. In this context, SDC constitutes an effective primer tool for complex system analysis, control and operational optimizations.
In this talk, a detailed survey of the developments on the research of SDC systems will be made together with their wide spectrum applications and future perspectives.
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- Starts 07 August 2025 07:00 AM UTC
- Ends 20 August 2025 06:59 AM UTC
- No Admission Charge
Speakers
Prof. Wang of Oak Ridge National Laboratory and University of Manchester
Stochastic Distribution Control and Its Applications
Biography:
Professor HONG WANG (FIEEE, FIET, FInstMC, FAAIA and FAIAA) received his BSc, MS and PhD from Huainan Mining Institute and the Huazhong University of Science and Technology, China, in 1982, 1984 and 1987, respectively. He is a research fellow at Salford, Brunel, and Southampton Universities before joining the University of Manchester Institute of Science and Technology (UMIST), UK, in 1992. Wang is a chair professor in process control from 2002 to 2016, and he is the deputy head of the Paper Science Department and director of the UMIST Control Systems Centre (which is established in 1966 and is the birthplace of modern control theory) between 2004 and 2007. He is a member of the University Senate and General Assembly. Between 2016 and 2018, he is with Pacific Northwest National Laboratory as a lab fellow and chief scientist and is the co-leader for the Control of Complex Systems (https://controls.pnnl.gov/). Wang joined Oak Ridge National Laboratory in January 2019 and is also an Emeritus Professor with the University of Manchester in UK.
Prof. Wang originated stochastic distribution control and his research focuses on stochastic distribution control, fault diagnosis and tolerant control, and intelligent controls with applications to transportation systems. He has published 6 books and 200+ journal papers, and has received numerous awards for his contribution in the above area. He is a member of IEEE Fellow Committee for 2024 and 2025, and was associate editor for IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, and IEEE Transactions on Automation Science and Engineering. He is also a member of three IFAC committees.
Agenda
11:30AM-12:30PM Presentation
12:30PM-1:00PM Q&A