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David Rincon
David Rincon
Chemical and Biomolecular Engineering, UCLA
Verified email at g.ucla.edu
Title
Cited by
Cited by
Year
Machine learning‐based predictive control of nonlinear processes. Part I: Theory
Z Wu, A Tran, D Rincon, PD Christofides
AIChE Journal 65 (11), e16729, 2019
1242019
Machine‐learning‐based predictive control of nonlinear processes. Part II: Computational implementation
Z Wu, A Tran, D Rincon, PD Christofides
AIChE Journal 65 (11), e16734, 2019
752019
Process structure-based recurrent neural network modeling for model predictive control of nonlinear processes
Z Wu, D Rincon, PD Christofides
Journal of Process Control 89, 74-84, 2020
572020
Real-time adaptive machine-learning-based predictive control of nonlinear processes
Z Wu, D Rincon, PD Christofides
Industrial & Engineering Chemistry Research 59 (6), 2275-2290, 2019
552019
Real-Time Optimization and Control of Nonlinear Processes Using Machine Learning
Z Zhang, Z Wu, D Rincon, PD Christofides
Mathematics 7 (10), 890, 2019
512019
Machine learning modeling and predictive control of nonlinear processes using noisy data
Z Wu, D Rincon, J Luo, PD Christofides
AIChE Journal 67 (4), e17164, 2021
202021
Machine Learning‐Based Distributed Model Predictive Control of Nonlinear Processes
S Chen, Z Wu, D Rincon, PD Christofides
AIChE Journal, e17013, 2020
202020
Operational safety of chemical processes via Safeness-Index based MPC: Two large-scale case studies
Z Zhang, Z Wu, D Rincon, C Garcia, PD Christofides
Computers & Chemical Engineering 125, 204-215, 2019
192019
Machine learning-based predictive control using noisy data: evaluating performance and robustness via a large-scale process simulator
Z Wu, J Luo, D Rincon, PD Christofides
Chemical Engineering Research and Design 168, 275-287, 2021
182021
Calorimetric estimation employing the unscented Kalman filter for a batch emulsion polymerization reactor
FD Rincón, M Esposito, PHH de Araújo, C Sayer, GAC Le Roux
Macromolecular Reaction Engineering 7 (1), 24-35, 2013
182013
Machine-learning-based state estimation and predictive control of nonlinear processes
MS Alhajeri, Z Wu, D Rincon, F Albalawi, PD Christofides
Chemical Engineering Research and Design 167, 268-280, 2021
172021
Statistical Machine Learning in Model Predictive Control of Nonlinear Processes
Z Wu, D Rincon, Q Gu, PD Christofides
Mathematics 9 (16), 1912, 2021
172021
Post cyber-attack state reconstruction for nonlinear processes using machine learning
Z Wu, S Chen, D Rincon, PD Christofides
Chemical Engineering Research and Design 159, 248-261, 2020
132020
A novel ARX-based approach for the steady-state identification analysis of industrial depropanizer column datasets
FD Rincón, GAC Le Roux, FV Lima
Processes 3 (2), 257-285, 2015
122015
Robust Calorimetric Estimation of Semi‐C ontinuous and Batch Emulsion Polymerization Systems with Covariance Estimation
FD Rincon, M Esposito, PHH de Araújo, FV Lima, GAC Le Roux
Macromolecular Reaction Engineering 8 (6), 456-466, 2014
122014
Nonlinear model predictive control of a climatization system using rigorous nonlinear model
BF Santoro, D Rincón, VC da Silva, DF Mendoza
Computers & Chemical Engineering 125, 365-379, 2019
112019
Real-time machine learning for operational safety of nonlinear processes via barrier-function based predictive control
Z Wu, D Rincon, PD Christofides
Chemical Engineering Research and Design 155, 88-97, 2020
72020
The autocovariance least-squares method for batch processes: application to experimental chemical systems
FD Rincón, GAC Le Roux, FV Lima
Industrial & Engineering Chemistry Research 53 (46), 18005-18015, 2014
52014
Operational Safety of an Ammonia Process Network Via Model Predictive Control
Z Zhang, D Rincon, Z Wu, C Garcia, PD Christofides
2019 AIChE Annual Meeting, 2019
42019
Operational safety via model predictive control: The Torrance refinery accident revisited
Z Zhang, Z Wu, D Rincon, PD Christofides
Chemical Engineering Research and Design 149, 138-146, 2019
42019
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