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 | 199 | 2019 |
CFD modeling and control of a steam methane reforming reactor L Lao, A Aguirre, A Tran, Z Wu, H Durand, PD Christofides Chemical Engineering Science 148, 78-92, 2016 | 110 | 2016 |
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 | 106 | 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 | 99 | 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 | 86 | 2019 |
Control lyapunov-barrier function-based model predictive control of nonlinear systems Z Wu, F Albalawi, Z Zhang, J Zhang, H Durand, PD Christofides Automatica 109, 108508, 2019 | 77 | 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 | 71 | 2019 |
Detecting and handling cyber-attacks in model predictive control of chemical processes Z Wu, F Albalawi, J Zhang, Z Zhang, H Durand, PD Christofides Mathematics 6 (10), 173, 2018 | 59 | 2018 |
Economic machine-learning-based predictive control of nonlinear systems Z Wu, PD Christofides Mathematics 7 (6), 494, 2019 | 54 | 2019 |
A tutorial review of neural network modeling approaches for model predictive control YM Ren, MS Alhajeri, J Luo, S Chen, F Abdullah, Z Wu, PD Christofides Computers & Chemical Engineering, 107956, 2022 | 42 | 2022 |
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 | 42 | 2021 |
On integration of feedback control and safety systems: Analyzing two chemical process applications Z Zhang, Z Wu, H Durand, F Albalawi, PD Christofides Chemical Engineering Research and Design 132, 616-626, 2018 | 42 | 2018 |
Machine learning modeling and predictive control of the batch crystallization process Y Zheng, X Wang, Z Wu Industrial & Engineering Chemistry Research 61 (16), 5578-5592, 2022 | 39 | 2022 |
Statistical machine learning in model predictive control of nonlinear processes Z Wu, D Rincon, Q Gu, PD Christofides Mathematics 9 (16), 1912, 2021 | 39 | 2021 |
Model predictive control of phthalic anhydride synthesis in a fixed-bed catalytic reactor via machine learning modeling Z Wu, A Tran, YM Ren, CS Barnes, S Chen, PD Christofides Chemical Engineering Research and Design 145, 173-183, 2019 | 37 | 2019 |
A cyber‐secure control‐detector architecture for nonlinear processes S Chen, Z Wu, PD Christofides AIChE Journal 66 (5), e16907, 2020 | 36 | 2020 |
Machine learning‐based distributed model predictive control of nonlinear processes S Chen, Z Wu, D Rincon, PD Christofides AIChE Journal 66 (11), e17013, 2020 | 34 | 2020 |
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 | 32 | 2021 |
Safe economic model predictive control of nonlinear systems Z Wu, H Durand, PD Christofides Systems & Control Letters 118, 69-76, 2018 | 32 | 2018 |
Cyber-attack detection and resilient operation of nonlinear processes under economic model predictive control S Chen, Z Wu, PD Christofides Computers & Chemical Engineering 136, 106806, 2020 | 31 | 2020 |