摘要
热工系统中的很多生产环节是非线性时滞系统,其辨识问题一直是制约热工系统发展的关键问题。Hammerstein-Wiener模型是Hammerstein模型和Wiener模型的复合模型,可以较好地表达生产系统的动态特性和静态特性。将HammersteinWiener模型辨识方法应用于热工系统的辨识中,非线性部分用多项式表示,线性部分用差分方程表示。用粒子群算法将模型的辨识问题转化为参数空间上的寻优问题,求得该模型的待定参数在参数空间上的最优解。一系列仿真的结果表明,基于粒子群算法的Hammerstein-Wiener模型在热工系统的辨识中有深远的实践意义。
In thermal system,many production links are nonlinear and time-delay,so the identification of them is main restrictive factor for thermal system.Hammerstein-Wiener model is a composite model of Hammerstein model and Wiener model,which can better express the dynamic characteristics and static characteristics of the production processes.It has been used for the identification of the production link in thermal system in this paper,the nonlinear parts were represented by polynomials,and the linear part was represented by a difference equation.Particle Swarm Optimization algorithm has been used to transform the identification problem to the optimization problem in the parameter space,and then get the optimal solution of the model.The simulation experiments show that the Particle Swarm Optimization （PSO） algorithm based Hammerstein-Wiener model has profound significance for the identification of thermal system.
出处
《计算机仿真》
CSCD
北大核心
2013年第9期394-397,共4页
Computer Simulation
关键词
热工系统
辨识
粒子群算法
Thermal system
Identification
Particle swarm optimization （PSO） algorithm
