Parameter estimation for chaotic systems based on hybrid differential evolution algorithm

Abstract

Parameter estimation for chaotic systems is one of the important issues in chaotic control and synchronization. Through establishing an appropriate fitness function, the parameter estimation problem is formulated as a multi-dimensional functional optimization problem, which can be solved by using hybrid differential evolution (HDE) algorithm. A numerical simulation on the Lorenz system is conducted and the results demonstrate the effectiveness and robustness of the proposed algorithm, which is shown to be an effective method of parameter estimation for chaotic systems.