| Reinforcement Learning for Batch Bioprocess Optimization P Petsagkourakis, IO Sandoval, E Bradford, D Zhang, ... Computers & Chemical Engineering 133 (106649), 2020 | 108 | 2020 |
| Hybrid physics‐based and data‐driven modeling for bioprocess online simulation and optimization D Zhang, EA Del Rio‐Chanona, P Petsagkourakis, J Wagner Biotechnology and bioengineering 116 (11), 2919-2930, 2019 | 71 | 2019 |
| Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation EA del Rio Chanona, P Petsagkourakis, E Bradford, JEA Graciano, ... Computers & Chemical Engineering 147, 107249, 2021 | 32 | 2021 |
| Constrained model-free reinforcement learning for process optimization E Pan, P Petsagkourakis, M Mowbray, D Zhang, EA del Rio-Chanona Computers & Chemical Engineering 154, 107462, 2021 | 24 | 2021 |
| Chance constrained policy optimization for process control and optimization P Petsagkourakis, IO Sandoval, E Bradford, F Galvanin, D Zhang, ... Journal of Process Control 111, 35-45, 2022 | 22 | 2022 |
| Stability analysis of piecewise affine systems with multi-model predictive control P Petsagkourakis, WP Heath, C Theodoropoulos Automatica 111, 108539, 2020 | 20 | 2020 |
| Safe chance constrained reinforcement learning for batch process control M Mowbray, P Petsagkourakis, EA del Rio-Chanona, D Zhang Computers & chemical engineering 157, 107630, 2022 | 18 | 2022 |
| Robust stability of barrier-based model predictive control P Petsagkourakis, WP Heath, J Carrasco, C Theodoropoulos IEEE Transactions on Automatic Control 66 (4), 1879-1886, 2020 | 16* | 2020 |
| Data-driven optimization for process systems engineering applications D van de Berg, T Savage, P Petsagkourakis, D Zhang, N Shah, ... Chemical Engineering Science 248, 117135, 2022 | 13 | 2022 |
| Kinetic and hybrid modeling for yeast astaxanthin production under uncertainty F Vega‐Ramon, X Zhu, TR Savage, P Petsagkourakis, K Jing, D Zhang Biotechnology and Bioengineering 118 (12), 4854-4866, 2021 | 11 | 2021 |
| Constrained reinforcement learning for dynamic optimization under uncertainty P Petsagkourakis, IO Sandoval, E Bradford, D Zhang, ... IFAC-PapersOnLine 53 (2), 11264-11270, 2020 | 10 | 2020 |
| Safe model-based design of experiments using Gaussian processes P Petsagkourakis, F Galvanin Computers & Chemical Engineering 151, 107339, 2021 | 8 | 2021 |
| Reinforcement learning for batch-to-batch bioprocess optimisation P Petsagkourakis, IO Sandoval, E Bradford, D Zhang, ... Computer Aided Chemical Engineering 46, 919-924, 2019 | 8 | 2019 |
| Data-driven distributionally robust mpc using the wasserstein metric Z Zhong, EA del Rio-Chanona, P Petsagkourakis arXiv preprint arXiv:2105.08414, 2021 | 7 | 2021 |
| Integrating process design and control using reinforcement learning S Sachio, M Mowbray, MM Papathanasiou, EA del Rio-Chanona, ... Chemical Engineering Research and Design 183, 160-169, 2022 | 6 | 2022 |
| Data driven reduced order nonlinear multiparametric mpc for large scale systems P Petsagkourakis, C Theodoropoulos Computer Aided Chemical Engineering 43, 1249-1254, 2018 | 6 | 2018 |
| Simultaneous process design and control optimization using reinforcement learning S Sachio, E Antonio, P Petsagkourakis IFAC-PapersOnLine 54 (3), 510-515, 2021 | 4 | 2021 |
| Robust stability analysis for barrier-based equation-free multi-linear model predictive control P Petsagkourakis, WP Heath, C Theodoropoulos Chemical Engineering Research and Design 144, 237-246, 2019 | 4 | 2019 |
| Stability analysis of piecewise affine systems with multi-model model predictive control P Petsagkourakis, WP Heath, C Theodoropoulos arXiv preprint arXiv:1808.00307, 2018 | 3 | 2018 |
| Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes P Petsagkourakis, B Chachuat, EA del Rio-Chanona 2021 60th IEEE Conference on Decision and Control (CDC), 6734-6741, 2021 | 2 | 2021 |
Ehecatl Antonio del Río ChanonaSargent Centre for Process Systems Engineering, Imperial College LondonDirección de correo verificada de imperial.ac.uk
