基于混合差分进化算法的混沌系统参数估计

Parameter estimation for chaotic systems based on hybrid differential evolution algorithm

混沌系统参数估计是混沌系统控制与同步的关键问题.通过构造一个适当的适应度函数,将混沌系统的参数估计问题转化为一个多维优化问题,然后利用混合差分进化算法的全局搜索能力求解该优化问题.以典型的Lorenz混沌系统为例进行了数值仿真,结果表明了混合差分进化算法的有效性和鲁棒性,是一种有效的混沌系统参数估计方法.

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.