DocumentCode :
3192863
Title :
Nonlinear Modelling of Alstom Gasifier Using Wiener Model
Author :
Xin, Wang ; Liang, Zhao ; Jianhong, Lu ; Wenguo, Xiang
Author_Institution :
Sch. of Energy & Environ., Southeast Univ., Nanjing, China
Volume :
2
fYear :
2010
fDate :
11-12 May 2010
Firstpage :
804
Lastpage :
808
Abstract :
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 Alstom gasifier with strong nonlinearity and multivariable couples. The results compared to a combined linear subspace identification method demonstrate that the nonlinear method proposed in this paper behave better approximation.
Keywords :
matrix algebra; multivariable systems; neural nets; nonlinear control systems; state-space methods; stochastic processes; Alstom Gasifier; Wiener model; matrices estimation; multivariable output error state space; neural network; nonlinear modelling; numerical algorithms; subspace identification method; Automation; Couplings; Kernel; Mathematical model; Neural networks; State estimation; State-space methods; Stochastic processes; System identification; Vectors; modelling; neural networks; state space methods; subspace; wiener model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
Type :
conf
DOI :
10.1109/ICICTA.2010.80
Filename :
5522746
Link To Document :
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