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Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation.

E. del Rio-Chanona, P. Petsagkourakis, E. Bradford, J. Graciano, and B. Chachuat. Comput. Chem. Eng., (2021)

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Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes.P. Petsagkourakis, B. Chachuat, and E. del Rio-Chanona. CDC, page 6734-6741. IEEE, (2021)Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation.E. del Rio-Chanona, P. Petsagkourakis, E. Bradford, J. Graciano, and B. Chachuat. Comput. Chem. Eng., (2021)Safe chance constrained reinforcement learning for batch process control.M. Mowbray, P. Petsagkourakis, E. del Rio-Chanona, and D. Zhang. Comput. Chem. Eng., (2022)Stability Analysis of Piecewise Affine Systems with Multi-model Model Predictive Control.P. Petsagkourakis, W. Heath, and C. Theodoropoulos. CoRR, (2018)Safe model-based design of experiments using Gaussian processes.P. Petsagkourakis, and F. Galvanin. Comput. Chem. Eng., (2021)Reinforcement learning for batch bioprocess optimization.P. Petsagkourakis, I. Sandoval, E. Bradford, D. Zhang, and E. del Rio-Chanona. Comput. Chem. Eng., (2020)Input-Output Stability of Barrier-Based Model Predictive Control.P. Petsagkourakis, W. Heath, J. Carrasco, and C. Theodoropoulos. CoRR, (2019)Constrained model-free reinforcement learning for process optimization.E. Pan, P. Petsagkourakis, M. Mowbray, D. Zhang, and E. del Rio-Chanona. Comput. Chem. Eng., (2021)

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Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation.

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Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation.