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UID:0-523@aerospace.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20150511T163000

DTEND;TZID=Asia/Jerusalem:20150511T173000

DTSTAMP:20230603T193147Z

URL:https://aerospace.technion.ac.il/events/a-new-concept-reaching-the-bes
 t-achievable-control-by-decomposing-the-sensitivity-function-part-2/

SUMMARY:A New Concept Reaching the Best Achievable Control by Decomposing t
 he Sensitivity Function - Part 2
DESCRIPTION:Lecturer:Prof. L. Keviczky\n Faculty:\n Institute:Department of
  Automation and Applied Informatics\, Budapest University of Technology\, 
 and Economics (BUTE) and Computer and Automation Research Institute (CARI)
  of the Hungarian Academy of Sciences (HAS)\n Location:Classroom 165\, gro
 und floor\, Library\, Aerospace Eng.\n Zoom: \n Abstract: \n Details: \n O
 ptimization of the design loss\nThe optimization of the design loss result
 s in selecting the fastest reference models under the amplitude constraint
 s of the actuators. It is possible to develop an iterative redesign techni
 que for the selection of best reachable reference model. It is very rare t
 hen we have an analytical solution for this optimization\, instead repeate
 d simulation runs results in the best reference model. The optimization pr
 ocess is presented by several simulation examples.\nOptimization of the re
 alizability loss\nFor the optimization of the realizability loss new (ener
 gy and supremum) norms E2 and E͚ are applied instead of the classical nor
 ms H2 and H͚. Unfortunately these last norms are not applicable for such 
 – mostly integrating – regulator classes\, which are important for ind
 ustrial applications. The norms E2 and E͚ are certain generalizations of 
 the classical norms H2 and H͚. The optimization of E2 can be usually solv
 ed by the application of certain Diophantine equations. The optimization o
 f E͚ can be usually solved by the iterative solution of a nonlinear equat
 ion system. Several simple examples are shown to ease the understanding of
  the high level mathematical procedures.\nOptimization of the modeling los
 s\nThe modeling loss considers the process identification in two parallel 
 closed loops\, where one is the original and the other is based on the ava
 ilable model. The optimization of the modeling loss results in a special b
 inary form of the reference signal\, where the switching condition can be 
 computed via a specially formed filter. It is interesting that the optimal
  reference signal excitation concentrates the frequency weights around the
  cutting frequency. Simple but convincing simulation runs are presented to
  prove the much higher efficiency of the optimal identification comparing 
 to other excitation signals.
CATEGORIES:Seminars
LOCATION:Classroom 165\, ground floor\, Library\, Aerospace Eng.

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DTSTART:20150327T030000

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