BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:A distributed model predictive control algorithm: ideas\, extensio
 ns\, and applications
DTSTART:20150508T101500
DTSTAMP:20260408T060350Z
UID:d5f9df3fc833b75ff576bd5fc7bef645efd25a9151def30b492d510f
CATEGORIES:Conferences - Seminars
DESCRIPTION:Riccardo Scattolini\nThe development of Distributed Model Pred
 ictive Control (DMPC) algorithms has recently received a major attention. 
 In the first part of this talk\, the main approaches proposed so far are b
 riefly summarized. Then\, the main ideas underlying the development of a D
 MPC method for the regulation of  linear systems and based on a robustnes
 s approach are presented. The algorithm is also extended to cope with the 
 tracking problem and a number of examples are presented to show its proper
 ties and applicability.\nBio: Riccardo Scattolini was born in Milano\, Ita
 ly\, in 1956. He received the Laurea degree in electronic engineering from
  the Politecnico di Milano\, Italy\, in 1979. He is Professor of automatic
  control with the Politecnico di Milano. From 1984 to 1985\, he was a Visi
 ting Researcher at the Department of Engineering Science\, Oxford Universi
 ty\, U.K. He also spent one year working in industry on the simulation and
  control of chemical plants. His current research interests include modeli
 ng\, identification\, simulation and control of industrial plants and dist
 ribution networks\, with emphasis on distributed model predictive control 
 of large-scale systems. Prof. Scattolini received the Heaviside Premium fr
 om the Institution of Electrical Engineers\, U.K.\, in 1991. He is current
 ly Associate Editor of Automatica and of the International Journal of Adap
 tive Control and Signal Processing.
LOCATION:ME C2 405 http://plan.epfl.ch/?zoom=20&recenter_y=5864084.17342&r
 ecenter_x=730960.62257&layerNodes=fonds\,batiments\,labels\,information\,p
 arkings_publics\,arrets_metro\,transports_publics&floor=2&q=me_c2%20405
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR