基于并行混沌搜索的非线性系统参数估计

Estimation of Nonlinear System Using Parallel Chaotic Search Method

提出了一种并行混沌搜索结合模式搜索法的混合优化算法,并应用于非线性系统参数估计。该算法采用并行混沌搜索机制,多个混沌变量同时映射一个优化变量。为了提高搜索速度,在每一次并行混沌搜索之后,由模式搜索法对并行混沌搜索结果再次寻优。该优化算法具有混沌优化的全局搜索能力,而模式搜索法则加快了局部寻优性能。该算法应用于三种不同非线性系统中,仿真结果表明其是一种有效的参数估计方法,参数估计精度优。

For parameter estimation of nonlinear system, this paper proposed a hybrid optimization algorithm integrating parallel chaotic search algorithm （PCS） with pattern search method （PS）. In this hybrid optimization algorithm, a PCS was analyzed where each variable was mapped to several chaotic variables. During each iteration of chaotic search, pattern search method （PS） was employed as a local search for PCS. The proposed hybrid algorithm had the global search ability of chaotic search as well as local search ability of pattern search method. Here three different model of nonlinear system is estimated by the proposed hybrid algorithm and simulations demonstrated that it is an effective way for nonlinear system parameter estimation with global optimal.