基于微粒群算法的非线性系统模型参数估计

PSO Algorithm for Parameter Estimation in Nonlinear System Model

微粒群优化(PSO)算法是一种进化算法,包含的概念简单。本文不同于传统的非线性模型参数估计方法,将微粒群优化算法应用于非线性系统模型(NSM)的参数估计,并通过重油热解三集总模型参数估计进行PSO算法效果测试。实验结果表明:微粒群算法为非线性系统模型参数估计提供了一种新方法。

In this paper, instead of traditional parameter estimation algorithms, the PSO algorithm is applied to the parameter estimation of nonlinear system model （NSM）. The effectiveness of the PSO algorithm is tested by simulation experiments on the parameter estimation of the NSM for heavy oil thermal cracking . The simulation results show that the PSO approach provides an attractive method for the estimation of parameters of NSM.