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Open-loop regulation and tracking control based on a genealogical decision tree
Authors:K Najim  E Ikonen  P Del Moral
Affiliation:(1) Process Control Laboratory, E.N.S.I.A.C.E.T., 118, route de Narbonne, 31077 Toulouse Cedex 4, France;(2) Systems Engineering Laboratory, Department of Process and Environmental Engineering, University of Oulu, P.O.Box 4300, 90014 Oulu, Finland;(3) Laboratoire J.-A. Dieudonné, Université de Nice—Sophia Antipolis, Parc Valrose, 06108 Nice Cedex 02, France
Abstract:The goal of this paper is to design a new control algorithm for open-loop control of complex systems. This control approach is based on a genealogical decision tree for both regulation and tracking control problems. The idea behind this control strategy consists of associating Gaussian distributions to both 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 on probability. A numerical example dealing with the control of a fluidized bed combustion power plant illustrates the feasibility and the performance of this control algorithm.K. Najim was partially supported by UK EPSRC Research cluster project, grant no. GR/S63779/. E. Ikonen was supported by the Academy of Finland, projects nos. 48545 and 203231.
Keywords:Monte Carlo method  Optimal control  Optimization problems  Particle filtering  Population based search  Power plants
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