Nonlinear Modelling of Alstom Gasifier Using Wiener Model

摘要：

A novel nonlinear modelling approach has been developed and implemented on Alstom gasifier using Wiener model. The linear element of the Wiener model was identified by a combined subspace state space method, which integrated MOESP (Multivariable Output-Error State Space) and N4SID (Numerical algorithms for subspace state space system identification) method in the estimation of system matrices. Then a single layer neural network was chosen as the nonlinearity of the model. The proposed model identification method was used to model AIstom gasifier with strong nonlinearity and mnltivariable couples. The results compared to a combined linear subspace identification method demonstrate that the nonlinear method proposed in this paper behave better approximation.

关键词： modelling subspace wiener model neural networks state space methods

作者: Wang Xin Zhao Liang Lu Jianhong Xiang Wenguo

作者单位: School of Energy and Environment, Southeast University, SEU, Nanjing, 210096, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 1974-1978

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）