Note: you can find some open-source codes developed in our papers. Please kindly cite them if you find the codes useful. Thank you.
1. Explicit model predictive control for machine-learning-based MPC | Link: https://github.com/Wenlong-Codes/ExplicitML-MPC
- Wang, W., Y. Wang, Y. Tian, and Z. Wu. “Explicit Machine Learning-Based Model Predictive Control of Nonlinear Processes via Multi-Parametric Programming“, Comp. & Chem. Eng., 186, 108689, 2024.
2. Machine-learning-based model predictive control | Link: https://github.com/GuoQWu/RNN-based-MPC
- Wu, Z., A. Tran, D. Rincon and P. D. Christofides, “Machine Learning-Based Predictive Control of Nonlinear Processes. Part I: Theory,” AIChE J., 65, e16729, 2019.
- Wu, Z., A. Tran, D. Rincon and P. D. Christofides, “Machine Learning-Based Predictive Control of Nonlinear Processes. Part II: Computational Implementation,” AIChE J., 65, e16734, 2019.
3. Physics-informed machine learning for modeling chemical processes | Link: https://github.com/Keerthana-Vellayappan/Demonstration-of-Physics-Informed-Machine-Learning-Model
- Zheng, Y., C. Hu, X, Wang, and Z. Wu, “Physics-Informed Recurrent Neural Network Modeling for Predictive Control of Nonlinear Processes“, J. Proc. Contr., 128, 103005, 2023.