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Authors
E. Ikonen; E. Gomez-Ramirez; K. Najim

Digital Object Identifier (DOI)
10.3182/20060830-2-SF-4903.00033

Page Numbers:
185-190

Index Terms
Monte Carlo method,optimal control,optimization problems,particle filtering,population-based search

Abstract
This paper deals with the open-loop tracking control of batch and repetitive chemical reactors on the basis of a genealogical decision trees (GDT). GDT are a population-based random search technique for solving trajectory tracking problems. The idea behind the GDT consists of associating Gaussian distributions to the norms of the control actions and the tracking errors. This stochastic search model can be interpreted as a simple genetic particle evolution model with a natural birth and death interpretation. It converges in probability. Numerical examples dealing with temperature control of two simulated reactors illustrate the feasibility and the e ?ciency of this control algorithm. An extension to regulation based on on-line state information is briefly outlined.

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