Application of gain scheduling for modeling the nonlinear dynamic characteristics of NOx emissions from utility boilers

论文类型：

期刊论文

第一作者：

Kong, Liang

通讯作者：

Ding, YJ (reprint author), Tsinghua Univ, Dept Thermal Engn, Beijing 100084, Peoples R China.

合写作者：

Wu, Zhansong,Zhang, Yi,Yuan, Lichuan,Ding, Yanjun

发表时间：

2009-03-01

发表刊物：

KOREAN JOURNAL OF CHEMICAL ENGINEERING

收录刊物：

SCIE

文献类型：

J

卷号：

26

期号：

2

页面范围：

534-541

ISSN号：

0256-1115

关键字：

Utility Boiler; Gain Scheduling; NOx Emissions; Nonlinear Dynamic Model

摘要：

A hierarchical gain scheduling (HGS) approach is proposed to model the nonlinear dynamics of NOx emissions of a utility boiler. At the lower level of HGS, a nonlinear static model is used to schedule the static parameters of local linear dynamic models (LDMs), such as static gains and static operating conditions. According to upper level scheduling variables, a multi-model method is used to calculate the predictive output based on lower-level LDMs. Both static and dynamic experiments are carried out at a 360 MW pulverized coal-fired boiler. Based on these data, a nonlinear static model using artificial neural network (ANN) and a series of linear dynamic models are obtained. Then,, the performance of the HGS model is compared to the common multi-model in predicting NOx emissions, and experimental results indicate that the proposed HGS model is much better than the multi-model in predicting NOx emissions in the dynamic process.