粒子群算法在励磁参数实测辨识中的应用

Application of PSO for Parameter Identification of Exciting System Based on Measured Data

针对采用频域分析和最小二乘拟合对复杂模型进行辨识时比较困难的缺点,文章提出了一种采用粒子群算法进行励磁系统参数拟合辨识的方法,该方法直接采用幅频特性和相频特性来定义适应度函数,实现过程简单。实际算例表明,提出的方法对简单模型和复杂模型都可以得到较好的辨识效果。

Considering that it is difficult for frequency domain method and least square method to identify parameters of complicate models, a parameter identification method forexciting system based on PSO（Partide Swarm Optimization）is proposed, which defines Fitness Function by directly using amplitude-frequency characteristic and phase-frequency characteristic of element. The example based on measured data shows that the proposed method can get better identification results both under simple model and complicate model.