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SUMMARY:Hierarchical / Distributed Control of Complex Process Networks
DTSTART:20170623T101500
DTEND:20170623T111500
DTSTAMP:20260407T103018Z
UID:29a057267366fdabcf9d9789b6fe9062897f9c4b9b80b18bafbfae6c
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Prodromos Daoutidis\, University of Minnesota\, USA\nAb
 stract :\n\nThe talk will focus on the control of integrated large-scale p
 lants\, a classic open problem in process control.\n \nThe first part of 
 the talk will focus on the dynamics and control of networks with large rat
 es of material and / or energy recovery and recycle\, compared to input/ou
 tput flows.  Such networks exhibit dynamics over multiple time scales\, w
 ith individual units evolving in a fast time scale with weak connections\,
  which become significant over slower time scales giving rise to a slow ev
 olution of the entire process network. A model reduction method based on s
 ingular perturbations will be described which allows obtaining a hierarchy
  of low-order nonlinear models valid in the different time scales. A graph
  reduction analogue of this method which can be fully automated will also 
 be described. This multi-time-scale analysis lends itself naturally to a h
 ierarchical control framework\, whereby network-level control objectives c
 an be effectively addressed at a slow\, supervisory level.\n \nThe second
  part of the talk will address generic integrated process networks with no
  material or energy flow segregation. A natural paradigm for addressing th
 is problem is the one of distributed control\, in which coordinated contro
 llers tackle operational objectives of different sections of the plant. A 
 key underlying problem is the optimal decomposition of the integrated syst
 em into the distributed control architecture. A new approach to this probl
 em inspired from network science will be described. It relies on identifyi
 ng “communities” of system variables whose members interact strongly a
 mong them\, yet are weakly coupled to the rest of the network members.  A
  modularity measure defined on suitable graphs is used to quantify strengt
 h of interactions\; maximization of modularity leads to optimal decomposit
 ions.  Such decompositions will be shown to lead to significant reduction
  in the computational cost of distributed optimization-based control while
  retaining satisfactory performance compared to centralized control.  The
  role of communities in sparsity-promoting control of networks will also b
 e elucidated.\n\nBio :\n\nProdromos Daoutidis is a College of Science and 
 Engineering Distinguished Professor and Executive Officer in the Departmen
 t of Chemical Engineering and Materials Science at the University of Minne
 sota. He received a Diploma degree in Chemical Engineering (1987) from the
  Aristotle University of Thessaloniki\, M.S.E. degrees in Chemical Enginee
 ring (1988) and Electrical Engineering: Systems (1991) from the University
  of Michigan\, and a Ph.D. degree in Chemical Engineering (1991) from the 
 University of Michigan. He has been on the faculty at Minnesota since 1992
 \, having served as Director of Graduate Studies in Chemical Engineering (
 1998-2004) and Chair of the Physical Sciences Policy and Review Council (2
 000-03)\, while he has also held a position as Professor at the Aristotle 
 University of Thessaloniki (2004-06). He is the recipient of several resea
 rch and teaching awards and recognitions\, including the NSF CAREER Award\
 , the PSE Model Based Innovation Prize\, the Best Paper Prize from the Jou
 rnal of Process Control\, the Ted Peterson Award of the CAST Division of A
 IChE\, the George Taylor Career Development Award\, the McKnight Land Gran
 t Professorship\, the Ray D. Johnson / Mayon Plastics Professorship and th
 e Shell Chair at the University of Minnesota. He has also been a Humphrey 
 Institute Policy Fellow. He has served as Program Coordinator in Areas 10B
  and 10D of the CAST Division of AIChE\, and as AIChE Director in AACC\, a
 nd is currently serving as CAST Programming Chair. He is the Associate Edi
 tor for Process Systems Engineering in the AIChE Journal\, and an Associat
 e Editor in the Journal of Process Control. He has co-authored 5 books\, 2
 50 refereed papers\, and has supervised to completion 26 PhD students and 
 post-docs\, 10 of which have gone into academic positions. His research in
 terests are in design and control of energy systems\, process and plant-wi
 de control\, control of nonlinear and distributed parameter systems\, mode
 l reduction\, dynamics and control of chemical and biological systems\, a
 nd control of advanced materials processing.\n 
LOCATION:ME C2 405 https://plan.epfl.ch/?room=MEC2405
STATUS:CONFIRMED
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