| 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 | 231 | 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 | 122 | 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 | 122 | 2016 |
| 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 | 120 | 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 | 95 | 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 | 93 | 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 | 82 | 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 165, 107956, 2022 | 72 | 2022 |
| 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 | 64 | 2018 |
| Economic machine-learning-based predictive control of nonlinear systems Z Wu, PD Christofides Mathematics 7 (6), 494, 2019 | 59 | 2019 |
| 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 | 51 | 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 | 51 | 2021 |
| Statistical machine learning in model predictive control of nonlinear processes Z Wu, D Rincon, Q Gu, PD Christofides Mathematics 9 (16), 1912, 2021 | 44 | 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 | 43 | 2018 |
| 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 | 42 | 2021 |
| Machine learning‐based distributed model predictive control of nonlinear processes S Chen, Z Wu, D Rincon, PD Christofides AIChE Journal 66 (11), e17013, 2020 | 42 | 2020 |
| A cyber‐secure control‐detector architecture for nonlinear processes S Chen, Z Wu, PD Christofides AIChE Journal 66 (5), e16907, 2020 | 41 | 2020 |
| Process structure-based recurrent neural network modeling for predictive control: A comparative study MS Alhajeri, J Luo, Z Wu, F Albalawi, PD Christofides Chemical Engineering Research and Design 179, 77-89, 2022 | 40 | 2022 |
| 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 | 40 | 2019 |
| 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 | 34 | 2020 |
Panagiotis D. ChristofidesWilliam D. Van Vorst Distinguished Professor and Department Chair of Chemical Engineering, UCLA在 seas.ucla.edu 的电子邮件经过验证
