Pair your accounts.

Export articles to Mendeley

Get article recommendations from ACS based on references in your Mendeley library.

Pair your accounts.

Export articles to Mendeley

Get article recommendations from ACS based on references in your Mendeley library.

You’ve supercharged your research process with ACS and Mendeley!

STEP 1:
Click to create an ACS ID

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

MENDELEY PAIRING EXPIRED
Your Mendeley pairing has expired. Please reconnect
ACS Publications. Most Trusted. Most Cited. Most Read
Constrained Nonlinear Estimation for Industrial Process Fouling

OR SEARCH CITATIONS

My Activity
Publications

Figure 1Loading Img
Download Hi-Res ImageDownload to MS-PowerPointCite This:Ind. Eng. Chem. Res. 2010, 49, 17, 7824-7831
    Article

    Constrained Nonlinear Estimation for Industrial Process Fouling
    Click to copy article linkArticle link copied!

    View Author Information
    Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, and Baytown Chemical Plant, ExxonMobil Chemical Company, 5000 Bayway Drive, Baytown, Texas 77520
    * To whom correspondence should be addressed. Tel.: 678-575-9940. E-mail: [email protected]
    †The University of Texas at Austin.
    ‡ExxonMobil Chemical Company.
    Other Access Options

    Industrial & Engineering Chemistry Research

    Cite this: Ind. Eng. Chem. Res. 2010, 49, 17, 7824–7831
    Click to copy citationCitation copied!
    https://doi.org/10.1021/ie9018116
    Published May 19, 2010
    Copyright © 2010 American Chemical Society
    Request reuse permissions

    Abstract

    Click to copy section linkSection link copied!

    Industrial process monitoring tools require robust and efficient estimation techniques that maintain a high service factor by remaining online during abnormal operating conditions, such as during loss of measurements, changes in control status, or maintenance. Constraints incorporate additional process knowledge into estimation by bounding estimated disturbances within feasibility limits thereby providing robustness to faulty measurements or conditions that violate process models. Moving horizon estimation (MHE) and unscented Kalman filtering (UKF) are two estimation techniques that permit incorporation of constraints prior to evaluating the a priori estimate. This paper evaluates both constrained nonlinear estimators versus the extended Kalman filter (EKF) using industrial process data provided by ExxonMobil Chemical Company. Results provide short-term insight into the fouling process, and parameter estimates produced by UKF and MHE are shown to be more accurate than EKF.

    Copyright © 2010 American Chemical Society

    Subjects

    what are subjects

    Read this article

    To access this article, please review the available access options below.

    Get instant access

    Purchase Access

    Read this article for 48 hours. Check out below using your ACS ID or as a guest.

    Recommended

    Access through Your Institution

    You may have access to this article through your institution.

    Your institution does not have access to this content. Add or change your institution or let them know you’d like them to include access.

    Cited By

    Click to copy section linkSection link copied!

    This article is cited by 27 publications.

    1. Chandra Sekhar Somayajula, Debangsu Bhattacharyya, Shanshan Hu, Xingbo Liu. Hot Corrosion Monitoring in Boilers Using a Nonlinear Estimator and Electrochemical Noise-Based Corrosion Sensors. Industrial & Engineering Chemistry Research 2024, 63 (1) , 394-409. https://doi.org/10.1021/acs.iecr.3c03542
    2. Franklin D. Rincón, G. A. Carrillo Le Roux, and Fernando V. Lima . The Autocovariance Least-Squares Method for Batch Processes: Application to Experimental Chemical Systems. Industrial & Engineering Chemistry Research 2014, 53 (46) , 18005-18015. https://doi.org/10.1021/ie501982b
    3. Nazila Yaghini and Piet D. Iedema. Molecular Weight and Branching Distribution Modeling in Radical Polymerization with Transfer to Polymer and Scission Under Gel Conditions and Allowing for Multiradicals. Macromolecules 2014, 47 (15) , 4851-4863. https://doi.org/10.1021/ma501094a
    4. Andressa Apio, Gustavo B. Martinelli, Luciane F. Trierweiler, Marcelo Farenzena, Jorge O. Trierweiler. Fouling monitoring of a heat exchanger network of an actual crude oil distillation unit by constrained extended Kalman filter with smoothing. Chemical Engineering Communications 2023, 210 (12) , 2229-2248. https://doi.org/10.1080/00986445.2023.2202316
    5. Fernando Arrais Romero Dias Lima, Ruan de Rezende Faria, Rodrigo Curvelo, Matheus Calheiros Fernandes Cadorini, César Augusto García Echeverry, Maurício Bezerra de Souza, Argimiro Resende Secchi. Influence of Estimators and Numerical Approaches on the Implementation of NMPCs. Processes 2023, 11 (4) , 1102. https://doi.org/10.3390/pr11041102
    6. Enso Ikonen, Markus Neuvonen, Istvan Selek, Mikko Salo, Mika Liukkonen. On-line estimation of circulating fluidized bed boiler fuel composition. 2022, 136-141. https://doi.org/10.1109/Control55989.2022.9781460
    7. Alexander Thebelt, Johannes Wiebe, Jan Kronqvist, Calvin Tsay, Ruth Misener. Maximizing information from chemical engineering data sets: Applications to machine learning. Chemical Engineering Science 2022, 252 , 117469. https://doi.org/10.1016/j.ces.2022.117469
    8. Leila Samandari Masooleh, Jeffrey E. Arbogast, Warren D. Seider, Ulku Oktem, Masoud Soroush. Distributed state estimation in large-scale processes decomposed into observable subsystems using community detection. Computers & Chemical Engineering 2022, 156 , 107544. https://doi.org/10.1016/j.compchemeng.2021.107544
    9. Jiawei Xu, Rong Yang, Xingqun Zhan. Performance Evaluation of Robust GPS Signal Tracking with Moving Horizon Estimation in Urban Environment. 2021, 403-418. https://doi.org/10.1007/978-981-33-6060-0_28
    10. Ronald Alexander, Gilson Campani, San Dinh, Fernando V. Lima. Challenges and Opportunities on Nonlinear State Estimation of Chemical and Biochemical Processes. Processes 2020, 8 (11) , 1462. https://doi.org/10.3390/pr8111462
    11. Junho Park, R. Abraham Martin, Jeffrey D. Kelly, John D. Hedengren. Benchmark temperature microcontroller for process dynamics and control. Computers & Chemical Engineering 2020, 135 , 106736. https://doi.org/10.1016/j.compchemeng.2020.106736
    12. Angang Chen, Zhengyun Ren, Zhiping Fan, Xue Feng. Two-Layered Model Predictive Control Strategy of the Cut Tobacco Drying Process. IEEE Access 2020, 8 , 155697-155709. https://doi.org/10.1109/ACCESS.2020.3018476
    13. Angang Chen, Zhengyun Ren, Zhiping Fan, Xue Feng. Dead Band Zone Model Predictive Control of Cut Tobacco Drying Process. IEEE Access 2020, 8 , 157781-157792. https://doi.org/10.1109/ACCESS.2020.3020469
    14. Brigham Hansen, Brandon Tolbert, Cory Vernon, John D. Hedengren. Model predictive automatic control of sucker rod pump system with simulation case study. Computers & Chemical Engineering 2019, 121 , 265-284. https://doi.org/10.1016/j.compchemeng.2018.08.018
    15. Xudong Zhang, Dietmar Göhlich, Chenrui Fu. Comparative Study of Two Dynamics-Model-Based Estimation Algorithms for Distributed Drive Electric Vehicles. Applied Sciences 2017, 7 (9) , 898. https://doi.org/10.3390/app7090898
    16. John D. Hedengren, Ammon N. Eaton. Overview of estimation methods for industrial dynamic systems. Optimization and Engineering 2017, 18 (1) , 155-178. https://doi.org/10.1007/s11081-015-9295-9
    17. Hamoudi Abdallah, Kouadri Benatman. Stator winding inter‐turn short‐circuit detection in induction motors by parameter identification. IET Electric Power Applications 2017, 11 (2) , 272-288. https://doi.org/10.1049/iet-epa.2016.0432
    18. Jose L. Mojica, Damon Petersen, Brigham Hansen, Kody M. Powell, John D. Hedengren. Optimal combined long-term facility design and short-term operational strategy for CHP capacity investments. Energy 2017, 118 , 97-115. https://doi.org/10.1016/j.energy.2016.12.009
    19. Misagh Ebrahimpour, Bruno F. Santoro. Moving horizon estimation of lumped load and occupancy in smart buildings. 2016, 468-473. https://doi.org/10.1109/CCA.2016.7587874
    20. Seyed Mostafa Safdarnejad, Jonathan R. Gallacher, John D. Hedengren. Dynamic parameter estimation and optimization for batch distillation. Computers & Chemical Engineering 2016, 86 , 18-32. https://doi.org/10.1016/j.compchemeng.2015.12.001
    21. Kody Powell, Ammon Eaton, John Hedengren, Thomas Edgar. A Continuous Formulation for Logical Decisions in Differential Algebraic Systems using Mathematical Programs with Complementarity Constraints. Processes 2016, 4 (1) , 7. https://doi.org/10.3390/pr4010007
    22. Benjamin Noack, Marcus Baum, Uwe D. Hanebeck. State estimation for ellipsoidally constrained dynamic systems with set-membership pseudo measurements. 2015, 297-302. https://doi.org/10.1109/MFI.2015.7295824
    23. Nicholas Lewis, John Hedengren, Eric Haseltine. Hybrid Dynamic Optimization Methods for Systems Biology with Efficient Sensitivities. Processes 2015, 3 (3) , 701-729. https://doi.org/10.3390/pr3030701
    24. John D. Hedengren, Reza Asgharzadeh Shishavan, Kody M. Powell, Thomas F. Edgar. Nonlinear modeling, estimation and predictive control in APMonitor. Computers & Chemical Engineering 2014, 70 , 133-148. https://doi.org/10.1016/j.compchemeng.2014.04.013
    25. Franklin D. Rincón, Marcelo Esposito, Pedro Henrique Hermes de Araújo, Fernando V. Lima, Galo A. C. Le Roux. Robust Calorimetric Estimation of Semi-Continuous and Batch Emulsion Polymerization Systems with Covariance Estimation. Macromolecular Reaction Engineering 2014, 8 (6) , 456-466. https://doi.org/10.1002/mren.201300151
    26. Victor M. Zavala. Inference of building occupancy signals using moving horizon estimation and Fourier regularization. Journal of Process Control 2014, 24 (6) , 714-722. https://doi.org/10.1016/j.jprocont.2013.09.020
    27. Hong Jang, Su-Hang Choi, Jay Hyung Lee. A Survey on State Estimation of Nonlinear Systems. Journal of Institute of Control, Robotics and Systems 2014, 20 (3) , 277-288. https://doi.org/10.5302/J.ICROS.2014.14.9015
    Download PDF
    Go to Industrial & Engineering Chemistry Research
    Get e-Alerts
    Get e-Alerts

    Industrial & Engineering Chemistry Research

    Cite this: Ind. Eng. Chem. Res. 2010, 49, 17, 7824–7831
    Click to copy citationCitation copied!
    https://doi.org/10.1021/ie9018116
    Published May 19, 2010
    Copyright © 2010 American Chemical Society
    Request reuse permissions

    Article Views

    1036

    Altmetric

    -

    Citations

    27
    Learn about these metrics

    Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

    Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

    The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.