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UBC Theses and Dissertations

Genetic algorithms in system identification and control Kristinsson, Kristinn

Abstract

Current online identification techniques are recursive and involve local search techniques. In this thesis, we show how genetic algorithms, a parallel, global search technique emulating natural genetic operators can be used to estimate the poles and zeros of a dynamical system. We also design an adaptive controller based on the estimates. The algorithms are shown to be useful for continuous time parameter identifications and to be able to identify directly physical parameters of a system. Simulations and an experiment show the technique to be satisfactory and to provide unbiased estimates in presence of colored noise.

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