Parameter estimation for chaotic systems based on improved boundary chicken swarm optimization

Abstract

Estimating unknown parameters for chaotic system is a key problem in the field of chaos control and synchronization. Through constructing an appropriate fitness function, parameter estimation of chaotic system could be converted to a multidimensional parameter optimization problem. In this paper, a new method base on improved boundary chicken swarm optimization (IBCSO) algorithm is proposed for solving the problem of parameter estimation in chaotic system. However, to the best of our knowledge, there is no published research work on chicken swarm optimization for parameters estimation of chaotic system. Computer simulation based on Lorenz system and comparisons with chicken swarm optimization, particle swarm optimization, and genetic algorithm shows the effectiveness and feasibility of the proposed method.