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 | 263 | 2019 |
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 | 141 | 2019 |
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 | 133 | 2020 |
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 | 106 | 2019 |
Real-Time Optimization and Control of Nonlinear Processes Using Machine Learning Z Zhang, Z Wu, D Rincon, PD Christofides Mathematics 7 (10), 890, 2019 | 88 | 2019 |
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 | 57 | 2021 |
Statistical Machine Learning in Model Predictive Control of Nonlinear Processes Z Wu, D Rincon, Q Gu, PD Christofides Mathematics 9 (16), 1912, 2021 | 54 | 2021 |
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 | 51 | 2021 |
Machine Learning‐Based Distributed Model Predictive Control of Nonlinear Processes S Chen, Z Wu, D Rincon, PD Christofides AIChE Journal, e17013, 2020 | 48 | 2020 |
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 | 40 | 2021 |
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 | 29 | 2020 |
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 | 26 | 2019 |
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 | 22 | 2013 |
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 | 13 | 2015 |
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 | 13 | 2014 |
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 | 12 | 2019 |
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 | 10 | 2020 |
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 | 10 | 2014 |
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 | 9 | 2019 |
Operational safety of an ammonia process network via model predictive control Z Zhang, Z Wu, D Rincon, PD Christofides Chemical Engineering Research and Design 146, 277-289, 2019 | 9 | 2019 |