Performance comparison of evolutionary algorithms in the task of optimization of chaos control

Abstract

This work deals with optimization of the control of chaos by means of the evolutionary algorithms. The main aim of this work is to show that evolutionary algorithms are capable of optimization of chaos control leading to satisfactory results and mainly to compare their performance in this task. As a model of deterministic chaotic system, the one dimensional Logistic equation was used. The evolutionary algorithms, SOMA (Self-Organizing Migrating Algorithm) and DE (Differential Evolution) were used in several versions. For each version, simulations were repeated 50 times to show and check robustness of the used method and constructed cost function. Within this work the results of optimized chaos control for both evolutionary algorithms are compared in statistical overview.