Machine learning-based predictive control using on-line model linearization: Application to an experimental electrochemical reactor

Luo, Junwei; Çıtmacı, Berkay; Jang, Joon Baek; Abdullah, Fahim; Morales-Guio, Carlos G.; Christofides, Panagiotis D.

doi:10.1016/j.cherd.2023.08.017

Title: Machine learning-based predictive control using on-line model linearization: Application to an experimental electrochemical reactor

Journal Article · 31 August 2023 · Chemical Engineering Research and Design

DOI: https://doi.org/10.1016/j.cherd.2023.08.017 · OSTI ID:2369039

; Çıtmacı, Berkay; Jang, Joon Baek;

; Morales-Guio, Carlos G.; Christofides, Panagiotis D.

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Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: EE0007613

OSTI ID:: 2369039

Journal Information:: Chemical Engineering Research and Design, Journal Name: Chemical Engineering Research and Design Journal Issue: C Vol. 197; ISSN 0263-8762

Publisher:: ElsevierCopyright Statement

Country of Publication:: United Kingdom

Language:: English

References (52)

Gastight rotating cylinder electrode: Toward decoupling mass transport and intrinsic kinetics in electrocatalysis Jang, Joonbaek; Rüscher, Martina; Winzely, Maximilian AIChE Journal, Vol. 68, Issue 5 https://doi.org/10.1002/aic.17605	journal	January 2022
Modeling and predictive control of nonlinear processes using transfer learning method Xiao, Ming; Hu, Cheng; Wu, Zhe AIChE Journal, Vol. 69, Issue 7 https://doi.org/10.1002/aic.18076	journal	March 2023
High Selectivity for Ethylene from Carbon Dioxide Reduction over Copper Nanocube Electrocatalysts Roberts, F. Sloan; Kuhl, Kendra P.; Nilsson, Anders Angewandte Chemie, Vol. 127, Issue 17 https://doi.org/10.1002/ange.201412214	journal	February 2015
Stability and Degradation Mechanisms of Copper‐Based Catalysts for Electrochemical CO ₂ Reduction Popović, Stefan; Smiljanić, Milutin; Jovanovič, Primož Angewandte Chemie, Vol. 132, Issue 35 https://doi.org/10.1002/ange.202000617	journal	June 2020
Support-vector networks Cortes, Corinna; Vapnik, Vladimir Machine Learning, Vol. 20, Issue 3 https://doi.org/10.1007/BF00994018	journal	September 1995
A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition Williams, Matthew O.; Kevrekidis, Ioannis G.; Rowley, Clarence W. Journal of Nonlinear Science, Vol. 25, Issue 6 https://doi.org/10.1007/s00332-015-9258-5	journal	June 2015
Model predictive control: Review of the three decades of development Lee, Jay H. International Journal of Control, Automation and Systems, Vol. 9, Issue 3 https://doi.org/10.1007/s12555-011-0300-6	journal	June 2011
Modelling of impact of water quality on infiltration rate of soil by random forest regression Singh, Balraj; Sihag, Parveen; Singh, Karan Modeling Earth Systems and Environment, Vol. 3, Issue 3 https://doi.org/10.1007/s40808-017-0347-3	journal	July 2017
Industrial applications of model based predictive control Richalet, J. Automatica, Vol. 29, Issue 5 https://doi.org/10.1016/0005-1098(93)90049-Y	journal	September 1993
A finite-difference method for linearization in nonlinear estimation algorithms Schei, Tor Steinar Automatica, Vol. 33, Issue 11 https://doi.org/10.1016/S0005-1098(97)00127-1	journal	November 1997
A survey of industrial model predictive control technology Qin, S. Joe; Badgwell, Thomas A. Control Engineering Practice, Vol. 11, Issue 7, p. 733-764 https://doi.org/10.1016/S0967-0661(02)00186-7	journal	July 2003
Machine-learning-based model predictive control with instantaneous linearization – A case study on an air-conditioning and mechanical ventilation system Yang, Shiyu; Wan, Man Pun Applied Energy, Vol. 306 https://doi.org/10.1016/j.apenergy.2021.118041	journal	January 2022
Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control Korda, Milan; Mezić, Igor Automatica, Vol. 93 https://doi.org/10.1016/j.automatica.2018.03.046	journal	July 2018
Machine learning-based adaptive model identification of systems: Application to a chemical process Bhadriraju, Bhavana; Narasingam, Abhinav; Kwon, Joseph Sang-Il Chemical Engineering Research and Design, Vol. 152 https://doi.org/10.1016/j.cherd.2019.09.009	journal	December 2019
Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor Çıtmacı, Berkay; Luo, Junwei; Jang, Joon Baek Chemical Engineering Research and Design, Vol. 185 https://doi.org/10.1016/j.cherd.2022.06.044	journal	September 2022
Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor Çıtmacı, Berkay; Luo, Junwei; Jang, Joon Baek Chemical Engineering Research and Design, Vol. 191 https://doi.org/10.1016/j.cherd.2023.02.003	journal	March 2023
A tutorial review of neural network modeling approaches for model predictive control Ren, Yi Ming; Alhajeri, Mohammed S.; Luo, Junwei Computers & Chemical Engineering, Vol. 165 https://doi.org/10.1016/j.compchemeng.2022.107956	journal	September 2022
Support vector regression model predictive control on a HVAC plant Xi, Xue-Cheng; Poo, Aun-Neow; Chou, Siaw-Kiang Control Engineering Practice, Vol. 15, Issue 8 https://doi.org/10.1016/j.conengprac.2006.10.010	journal	August 2007
Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and Threats Dobbelaere, Maarten R.; Plehiers, Pieter P.; Van de Vijver, Ruben Engineering, Vol. 7, Issue 9 https://doi.org/10.1016/j.eng.2021.03.019	journal	September 2021
Smart manufacturing inspired approach to research, development, and scale-up of electrified chemical manufacturing systems Richard, Derek; Jang, Joonbaek; Çıtmacı, Berkay iScience, Vol. 26, Issue 6 https://doi.org/10.1016/j.isci.2023.106966	journal	June 2023
Development of model predictive control system using an artificial neural network: A case study with a distillation column Shin, Yeonju; Smith, Robin; Hwang, Sungwon Journal of Cleaner Production, Vol. 277 https://doi.org/10.1016/j.jclepro.2020.124124	journal	December 2020
Cascade CO2 electroreduction enables efficient carbonate-free production of ethylene Ozden, Adnan; Wang, Yuhang; Li, Fengwang Joule, Vol. 5, Issue 3 https://doi.org/10.1016/j.joule.2021.01.007	journal	March 2021
Spectral analysis of nonlinear flows Rowley, Clarence W.; MeziĆ, Igor; Bagheri, Shervin Journal of Fluid Mechanics, Vol. 641 https://doi.org/10.1017/S0022112009992059	journal	November 2009
Dynamic mode decomposition of numerical and experimental data Schmid, Peter J. Journal of Fluid Mechanics, Vol. 656 https://doi.org/10.1017/S0022112010001217	journal	July 2010
Progress and Perspectives of Electrochemical CO ₂ Reduction on Copper in Aqueous Electrolyte Nitopi, Stephanie; Bertheussen, Erlend; Scott, Soren B. Chemical Reviews, Vol. 119, Issue 12 https://doi.org/10.1021/acs.chemrev.8b00705	journal	April 2019
Electroreduction of CO₂/CO to C₂ Products: Process Modeling, Downstream Separation, System Integration, and Economic Analysis Ramdin, Mahinder; De Mot, Bert; Morrison, Andrew R. T. Industrial & Engineering Chemistry Research, Vol. 60, Issue 49 https://doi.org/10.1021/acs.iecr.1c03592	journal	November 2021
Implementable Stability Guaranteed Lyapunov-Based Data-Driven Model Predictive Control with Evolving Gaussian Process Zhang, Tongqiang; Li, Shaoyuan; Zheng, Yi Industrial & Engineering Chemistry Research, Vol. 61, Issue 39 https://doi.org/10.1021/acs.iecr.2c01963	journal	September 2022
Carbonation in Low-Temperature CO₂ Electrolyzers: Causes, Consequences, and Solutions Ramdin, Mahinder; Moultos, Othonas A.; van den Broeke, Leo J. P. Industrial & Engineering Chemistry Research, Vol. 62, Issue 18 https://doi.org/10.1021/acs.iecr.3c00118	journal	April 2023
Conversion of Reactive Carbon Solutions into CO at Low Voltage and High Carbon Efficiency Zhang, Zishuai; Lees, Eric W.; Ren, Shaoxuan ACS Central Science, Vol. 8, Issue 6 https://doi.org/10.1021/acscentsci.2c00329	journal	May 2022
Trace-Level Cobalt Dopants Enhance CO₂ Electroreduction and Ethylene Formation on Copper Kim, Beomil; Tan, Ying Chuan; Ryu, Yeonkyeong ACS Energy Letters, Vol. 8, Issue 8 https://doi.org/10.1021/acsenergylett.3c00418	journal	July 2023
Eliminating the need for anodic gas separation in CO2 electroreduction systems via liquid-to-liquid anodic upgrading Xie, Ke; Ozden, Adnan; Miao, Rui Kai Nature Communications, Vol. 13, Issue 1 https://doi.org/10.1038/s41467-022-30677-x	journal	June 2022
Coupling electrochemical CO2 conversion with CO2 capture Sullivan, Ian; Goryachev, Andrey; Digdaya, Ibadillah A. Nature Catalysis, Vol. 4, Issue 11 https://doi.org/10.1038/s41929-021-00699-7	journal	November 2021
Selective production of ethylene glycol at high rate via cascade catalysis Fan, Lei; Zhao, Yilin; Chen, Lei Nature Catalysis, Vol. 6, Issue 7 https://doi.org/10.1038/s41929-023-00977-6	journal	June 2023
Hamiltonian Systems and Transformation in Hilbert Space Koopman, B. O. Proceedings of the National Academy of Sciences, Vol. 17, Issue 5 https://doi.org/10.1073/pnas.17.5.315	journal	May 1931
Dynamical Systems of Continuous Spectra Koopman, B. O.; Neumann, J. v. Proceedings of the National Academy of Sciences, Vol. 18, Issue 3 https://doi.org/10.1073/pnas.18.3.255	journal	March 1932
Linearization of Recurrent-Neural-Network- Based Models for Predictive Control of Nano-Positioning Systems Using Data-Driven Koopman Operators Xie, Shengwen; Ren, Juan IEEE Access, Vol. 8 https://doi.org/10.1109/ACCESS.2020.3013935	journal	January 2020
A Data-Driven Koopman Model Predictive Control Framework for Nonlinear Partial Differential Equations Arbabi, Hassan; Korda, Milan; Mezic, Igor 2018 IEEE Conference on Decision and Control (CDC) https://doi.org/10.1109/CDC.2018.8619720	conference	December 2018
Adaptive Model Predictive Control with Successive Linearization for Distillate Composition Control in Batch Distillation Mendis, Pramuditha; Wickramasinghe, Chathuranga; Narayana, Mahinsasa 2019 Moratuwa Engineering Research Conference (MERCon) https://doi.org/10.1109/MERCon.2019.8818777	conference	July 2019
Design and simulation of model predictive control for multivariable distillation column Chavan, Samruddhi; Birnale, Namrata; Deshpande, Amruta S. 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) https://doi.org/10.1109/RTEICT42901.2018.9012517	conference	May 2018
Cautious Model Predictive Control Using Gaussian Process Regression Hewing, Lukas; Kabzan, Juraj; Zeilinger, Melanie N. IEEE Transactions on Control Systems Technology, Vol. 28, Issue 6 https://doi.org/10.1109/TCST.2019.2949757	journal	November 2020
Balancing-Aware Charging Strategy for Series-Connected Lithium-Ion Cells: A Nonlinear Model Predictive Control Approach Pozzi, Andrea; Zambelli, Massimo; Ferrara, Antonella IEEE Transactions on Control Systems Technology, Vol. 28, Issue 5 https://doi.org/10.1109/TCST.2020.2995308	journal	September 2020
Neural Network-Based Model Predictive Control of a Paste Thickener Over an Industrial Internet Platform Nunez, Felipe; Langarica, Saul; Diaz, Pablo IEEE Transactions on Industrial Informatics, Vol. 16, Issue 4 https://doi.org/10.1109/TII.2019.2953275	journal	April 2020
Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network Han, Hong-Gui; Zhang, Lu; Hou, Ying IEEE Transactions on Neural Networks and Learning Systems, Vol. 27, Issue 2 https://doi.org/10.1109/TNNLS.2015.2465174	journal	February 2016
What would it take for renewably powered electrosynthesis to displace petrochemical processes? De Luna, Phil; Hahn, Christopher; Higgins, Drew Science, Vol. 364, Issue 6438 https://doi.org/10.1126/science.aav3506	journal	April 2019
Dynamic Mode Decomposition with Control Proctor, Joshua L.; Brunton, Steven L.; Kutz, J. Nathan SIAM Journal on Applied Dynamical Systems, Vol. 15, Issue 1 https://doi.org/10.1137/15M1013857	journal	January 2016
Generalizing Koopman Theory to Allow for Inputs and Control Proctor, Joshua L.; Brunton, Steven L.; Kutz, J. Nathan SIAM Journal on Applied Dynamical Systems, Vol. 17, Issue 1 https://doi.org/10.1137/16M1062296	journal	January 2018
Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator Arbabi, Hassan; Mezić, Igor SIAM Journal on Applied Dynamical Systems, Vol. 16, Issue 4 https://doi.org/10.1137/17M1125236	journal	January 2017
A Review of Piecewise Linearization Methods Lin, Ming-Hua; Carlsson, John Gunnar; Ge, Dongdong Mathematical Problems in Engineering, Vol. 2013 https://doi.org/10.1155/2013/101376	journal	January 2013
Regularization Theory and Neural Networks Architectures Girosi, Federico; Jones, Michael; Poggio, Tomaso Neural Computation, Vol. 7, Issue 2 https://doi.org/10.1162/neco.1995.7.2.219	journal	March 1995
Long Short-Term Memory Hochreiter, Sepp; Schmidhuber, Jürgen Neural Computation, Vol. 9, Issue 8 https://doi.org/10.1162/neco.1997.9.8.1735	journal	November 1997
Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control Brunton, Steven L.; Brunton, Bingni W.; Proctor, Joshua L. PLOS ONE, Vol. 11, Issue 2 https://doi.org/10.1371/journal.pone.0150171	journal	February 2016
Deep Transfer Learning for Approximate Model Predictive Control Munoz, Samuel Arce; Park, Junho; Stewart, Cristina M. Processes, Vol. 11, Issue 1 https://doi.org/10.3390/pr11010197	journal	January 2023

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