Parameter estimation for chaotic system based on particle swarm optimization
基于改进粒子群优化算法的混沌系统参数估计方法

It's of vital importance to estimate the unknown parameters of chaos systems in chaos control and synchronization. We firstly improve the newly developed particle swarm optimization (PSO) in view of the population initialization and objective function treatment. Then we use the improved algorithms for parameter estimation and on-line estimation of chaotic system for its global searching ability. Experiments show that the improved method has better adaptability, reliability and high precision is robust to noise. It is proved to be a successful approach in parameter estimation for chaotic systems.