Application of genealogical decision trees for open-loop tracking control
| Authors: | Ikonen Enso, University of Oulu, Finland
Najim Kaddour, E.N.S.I.A.C.E.T., France
Del Moral Pierre, Laboratoire de Statistics et Probabilities, Toulouse, France |
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| Topic: | 2.3 Non-Linear Control Systems |
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| Session: | Output Regulation and Tracking |
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| Keywords: | Monte Carlo method, optimal control, optimization problems, population-based search |
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Abstract
A new approach based on a genealogical decision tree is suggested for solving an open-loop tracking problem. The algorithm associates Gaussian distributions to both the norms of the control actions and the tracking errors. It solves the optimization problem sequentially, using random resampling from a population of solutions. 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. Two numerical examples, dealing with rapid thermal processing and robotics, illustrate the feasibility and the performance of this control algorithm.
