|本期目录/Table of Contents|

[1]张治涛,曾 静*.基于EKF与UKF的乙苯化工过程状态估计性能评估[J].工业仪表与自动化装置,2021,(06):52-57.[doi:10.19950/j.cnki.cn61-1121/th.2021.06.010]
　ZHANG Zhitao,ZENG Jing*.Performance evaluation of ethylbenzene chemical process state estimation based on EKF and UKF[J].Industrial Instrumentation & Automation,2021,(06):52-57.[doi:10.19950/j.cnki.cn61-1121/th.2021.06.010]
点击复制

基于EKF与UKF的乙苯化工过程状态估计性能评估

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2021年06期
页码:
52-57
栏目:
出版日期:
2021-12-15

文章信息/Info

Title:
Performance evaluation of ethylbenzene chemical process state estimation based on EKF and UKF
作者:
张治涛; 曾 静*
(沈阳化工大学 信息工程学院，辽宁 沈阳 110142)
Author(s):
ZHANG Zhitao; ZENG Jing*
(School of Information Engineering, Shenyang University of Chemical Technology, Liaoning, Shenyang 110142，China)
关键词:
状态估计; 乙苯化工过程; 扩展卡尔曼滤波; 无迹卡尔曼滤波
Keywords:
state estimation; ethylbenzene chemical process; Extended Kalman Filter; Unscented Kalman Filter
分类号:
TP273
DOI:
10.19950/j.cnki.cn61-1121/th.2021.06.010
文献标志码:
A
摘要:
当动态系统内部状态无法直接测量时，状态估计是获取内部状态数据有效的解决方法。该文基于扩展卡尔曼滤波器和无迹卡尔曼滤波器对乙苯化工过程中的状态估计进行了分析比较研究，依靠少量测量数据估计出了乙苯化工过程系统中的25个状态值。经过MATLAB一系列仿真实验验证了两种估计器的有效性，分析了在高斯噪声下，两种滤波器的性能与时间复杂度。结果表明：无迹卡尔曼滤波器能够提供更好的状态估计性能，两者都能够处理较大的输入扰动，无迹卡尔曼滤波器在状态估计计算时长上更具优势。
Abstract:
When the internal state of dynamic system cannot be measured directly, state estimation is an effective method to obtain internal state data.In this paper, state estimation in ethylbenzene chemical process is analyzed and compared on the basis of Extended Kalman Filter and Unscented Kalman Filter. Twenty-five state values in ethylbenzene chemical process system are estimated based on a few measurement data.Through a series of MATLAB simulation experiments, the effectiveness of the two estimators is verified, and the performance and time complexity of the two filters under Gaussian noise are analyzed.The results show that Unscented Kalman Filter can provide better performance of state estimation, both can deal with larger input perturbations, and Unscented Kalman Filter has more advantages in the computation time of state estimation.

参考文献/References:

[1]LEE W J , FROMENT G F . Ethylbenzene Dehydrogenation into Styrene: Kinetic Modeling and Reactor Simulation[J]. Industrial & Engineering Chemistry Research, 2008, 47(23):9183–9194. [2]KHLEBNIKOVA E , BEKKER A , IVASHKINA E , et al. Thermodynamic Analysis of Benzene Alkylation with Ethylene[J]. Procedia Chemistry, 2015, 15:42-48.

[3]孙洪敏.乙苯生产技术及市场分析[J].石油化工技术与经济, 2019,35(05):18-23.
[4]Devyani, Varshney, Sachin, et al. Batch and Moving Horizon Estimation for Systems subjected to Non-additive Stochastic Disturbances - ScienceDirect[J]. IFAC-PapersOnLine, 2019, 52(1):16-21.
[5]Hr P , Valluru J , Patwardhan S C , et al. Simultaneous State and Parameter Estimation using Receding-horizon Nonlinear Kalman Filter[J].2018.
[6]Xu X , Huang B , Dubljevic S . Optimal continuous-time state estimation for linear finite and infinite-dimensional chemical process systems with state constraints[J]. Journal of Process Control, 2015.
[7]金学波.Kalman滤波器理论与应用：基于MATLAB实线[M].北京:科学出版社,2016:35-46.
[8]Mehdi, Gholizadeh, Alireza, et al. Fault detection and identification using combination of EKF and neuro-fuzzy network applied to a chemical process (CSTR)[J]. Pattern Analysis & Applications, 2019, 22(2):359–373.
[9]黄小平,王岩.卡尔曼滤波及其应用[M].北京：电子工业出版社，2015：77-84.
[10]胡士强,敬忠良.粒子滤波算法综述[J].控制与决策,2005(04):361-365+371.
[11]LIU J , CHEN X , PEA D M D L , et al. Sequential and iterative architectures for distributed model predictive control of nonlinear process systems[J]. AIChE Journal, 2010,56(8):2137-2149.

相似文献/References:

备注/Memo

备注/Memo:
收稿日期: 2021-07-09
基金项目：国家自然科学基金(61503257)
作者简介：张治涛，男，山东德州人，硕士研究生，非线性系统的状态估计。
通信作者：曾静，副教授/博士，主要研究领域：非线性系统的状态估计及预测控制。
更新日期/Last Update: 1900-01-01