OPTIMIZATION OF FEEDBACK CONTROL OF CHAOS BY EVOLUTIONARY ALGHORITHMS

This contribution deals with an investigation on optimization of the feedback control of chaos based on method of an artificial intelligence, namely the evolutionary algorithms. The main aim of this work is to show that evolutionary algorithms are capable of optimization of deterministic chaos control. The optimizations were realized in several ways, each one for another set of control parameters or another cost function. Two evolutionary algorithms were used: differential evolution and SOMA (Self-Organizing Migrating Algorithm). For both algorithms each simulation was repeated several times to show and check robustness of used methods.