DocumentCode :
1979681
Title :
System identification for steam distillation pilot plant: Comparison between linear and nonlinear models
Author :
Md Shariff, Haslizamri ; Marzaki, Mohd Hezri ; Tajjudin, Mazidah ; Rahiman, M.H.F.
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol., Shah Alam, Malaysia
fYear :
2013
fDate :
19-20 Aug. 2013
Firstpage :
263
Lastpage :
268
Abstract :
This paper is proposed to model the steam temperature in steam distillation pilot plant using system identification. Random Gaussian Signal (RGS) has been implemented to this system to perturb the input of the system. The linear and nonlinear Auto Regressive with Exogenous input (ARX) models structure is used to estimate and validate the model output of steam distillation pilot plant. Both models will be compared to study the performance and flexibility. The validation test is performed by using auto-correlation function (ACF), cross-correlation function (CCF) and model fit to validate the estimated both ARX models.
Keywords :
Gaussian distribution; autoregressive processes; distillation equipment; nonlinear control systems; ACF; ARX model structure; CCF; auto regressive with exogenous input; autocorrelation function; cross-correlation function; nonlinear models; random Gaussian signal; steam distillation pilot plant; steam temperature; system identification; Correlation; Data models; Estimation; Mathematical model; Nonlinear systems; System identification; Temperature measurement; Gaussian Random Signal (RGS); auto-correlation function (ACF); cross-correlation function (CCF); linear auto regressive with exogenous input (ARX); nonlinear auto regressive with exogenous input (NARX);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Engineering and Technology (ICSET), 2013 IEEE 3rd International Conference on
Conference_Location :
Shah Alam
Print_ISBN :
978-1-4799-1028-1
Type :
conf
DOI :
10.1109/ICSEngT.2013.6650182
Filename :
6650182
Link To Document :
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