Genetic algorithms in system identification

Abstract

Current online identification techniques are recursive and local search techniques. In the present work, it is shown 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. An adaptive controller is designed on the basis of the estimates. Simulations and an experiment show the technique to be satisfactory and to provide unbiased estimates in the presence of colored noise.<>