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SUMMARY:Extremum Seeking Control and its Application to Process and Reacti
 on Systems: a Survey.
DTSTART:20110325T101500
DTSTAMP:20260415T191332Z
UID:d26e877cd66399b0455874f1f93dbe1bf55748a9afee90af805da0df
CATEGORIES:Conferences - Seminars
DESCRIPTION:Pr. D. Dochain\, Center for Systems Eng. and Applied Mechanics
 \, Universite Catholique de Louvain\, Belgium\nMost adaptive control schem
 es documented in the literature are developed for regulation to known set-
 points or tracking known reference trajectories. Yet in some applications 
 the control objective could be to optimize an objective function\, which c
 an be a function of unknown parameters\, or to select the desired states t
 o keep a performance function at its extremum value. Extremum seeking cont
 rol is one of the methods to handle these kinds of optimization problems. 
 Extremum seeking control allows the solution of the optimization problem a
 s a control problem with the advantages related to sensitivity reduction a
 nd disturbance rejection. In the past few years\, Krstic et al. have prese
 nted several schemes for extremum-seeking control of nonlinear systems. Fi
 rst the system is perturbed using an external excitation signal in order t
 o numerically compute the gradient. \nAlthough this technique has been pro
 ven useful for some applications\, the lack of guaranteed transient perfor
 mance of the black-box schemes remains a significant drawback in its appli
 cation. Alternatively an adapted model of the system is used for analytica
 l evaluation of the gradient. The extremum seeking framework proposed by G
 uay and Zhang assumes that the objective function is explicitly known as a
  function of the system states and uncertain parameters from the system dy
 namic equations. Parametric uncertainties make the on-line reconstruction 
 of the true cost impossible such that only an estimated value based on par
 ameter estimates is available. The control objective is to simultaneously 
 identify and regulate the system to the lowest cost operating point\, whic
 h depends on the uncertain parameters. The main advantage of this approach
  is that one can guarantee some degree of transient performance while achi
 eving the optimization objectives when a reasonable functional approximati
 on of the objective function is available. The objective of this seminar i
 s to present a survey on extremum seeking control methods and their applic
 ations to process and reaction systems. Two important classes of extremum 
 seeking control approaches are considered: perturbation-based and model-ba
 sed methods.
LOCATION:MEC2405
STATUS:CONFIRMED
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