【摘要】 引入个体位置变异的方法对标准粒子群算法进行了改进,并将其应用于火电厂主蒸汽压力系统,进行传递函数的参数辨识。改进后的算法丰富了种群的多样性,提高了搜索的速度。将改进后的基于个体位置变异的粒子群算法和标准粒子群算法进行辨识对比实验,结果表明,改进后的算法能有效降低辨识误差,同时明显缩减运行时间。更多还原

【Abstract】 The method of individual position variation is introduced to improve the performance of PSO, and it is applied to the parameter identification of the transfer function of the main steam pressure system of a power plant. The improved algorithm enriches the diversity of the population and improves the search speed of the algorithm. The improved MPSO is compared with the PSO, the results show that using the improved MPSO can effectively reduce the identification error and significantly reduce the running time.更多还原