Estimation of nonlinear ARX model for steam distillation process by wavenet estimator

N. Ismail, Nazurah Tajjudin, M. Rahiman, M. Taib
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引用次数: 2

Abstract

This paper presents estimation on nonlinear ARX model for steam distillation process by wavenet estimator. A set of input-output data samples was collected at a sampling rate of 0.1 second from an essential oil extraction pilot plant by using steam distillation technique. PRBS input signal delivered to the heating element of the plant while the output was the steam temperature. By applying interlacing technique the data was split into 2 equal size subsets of data. One set of data was used for model estimation and the other one was used for model validation. During the estimation, we applied Nonlinear ARX based on wavenet estimator with different unit i.e. unit 1, unit 2, unit 3 and unit 8 in order to see their performances. We also modeled linear ARX for performance comparison. The comparison was done in term of the agreement between measured data and those models based on wavenet with different unit and the result has shown that the nonlinear ARX based on wavenet estimator with 3 units has outperformed the other models. For future work, the result obtained from estimation is contributed for extended application such as Hammerstein-Wiener model.
蒸汽蒸馏过程非线性ARX模型的波网络估计
本文提出了用小波估计器对蒸汽蒸馏过程的非线性ARX模型进行估计。采用蒸汽蒸馏技术,以0.1秒的采样速率采集了一组精油提取中试装置的输入-输出数据样本。PRBS输入信号传递给电厂加热元件,输出为蒸汽温度。采用隔行技术将数据分割成2个大小相等的数据子集。一组数据用于模型估计,另一组数据用于模型验证。在估计过程中,我们使用了基于非线性ARX的不同单元的波网估计器,即单元1、单元2、单元3和单元8,以观察它们的性能。我们还为性能比较建立了线性ARX模型。对比了实测数据与基于不同单元的小波网络模型的一致性,结果表明,基于3单元小波网络估计器的非线性ARX模型优于其他模型。在今后的工作中,估计得到的结果为Hammerstein-Wiener模型等扩展应用做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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