离散混沌系统参数估计的生物地理学优化算法（英文）

Parameter estimation for discrete chaotic systems with biogeography-based optimization

基于混沌控制的方法,建立了离散混沌系统参数估计问题的非线性方程组模型.将此方程组模型转化为多峰连续函数优化问题并设计相应的生物地理学优化算法进行求解.通过对两个典型的离散混沌系统进行仿真实验,数值结果表明该方法具有测量数据少、参数估计精度高的优点.

A biogeography-based optimization scheme was proposed for parameter estimation in discrete chaotic systems from time series, and the constant feedback based method for controlling chaos was adopt- ed to address the estimation problem. The major advantages of this method are that it needs a minimal number of time series data and is applicable to chaotic systems of any dimension. The parameters and the feedback strengths of two test systems can be successfully identified using the proposed scheme. To explore the noise immunity, the influence of certain levels of noise on the time series was tested. Numerical simulations for Logistic and H6non chaotic system identification showed the effectiveness of the proposed method.