Imperial College London
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DrMariaPapathanasiou

Faculty of Engineering, Department of Chemical Engineering

Senior Lecturer
 
 
 
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Contact

 

maria.papathanasiou11

 
 
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Location

 

RODH.501DRoderic Hill BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Sachio:2022:10.1016/j.cherd.2021.10.032,
author = {Sachio, S and Mowbray, M and Papathanasiou, MM and del, Rio-Chanona EA and Petsagkourakis, P},
doi = {10.1016/j.cherd.2021.10.032},
journal = {Chemical Engineering Research and Design},
pages = {160--169},
title = {Integrating process design and control using reinforcement learning},
url = {http://dx.doi.org/10.1016/j.cherd.2021.10.032},
volume = {183},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - To create efficient-high performing processes, one must find an optimal design with its corresponding controller that ensures optimal operation in the presence of uncertainty. When comparing different process designs, for the comparison to be meaningful, each design must involve its optimal operation. Therefore, to optimize a process’ design, one must address design and control simultaneously. For this, one can formulate a bilevel optimization problem, with the design as the outer problem in the form of a mixed-integer nonlinear program (MINLP) and a stochastic optimal control as the inner problem. This is intractable by most approaches. In this paper we propose to compute the optimal control using reinforcement learning, and then embed this controller into the design problem. This allows to decouple the solution procedure, while having the same optimal result as if solving the bilevel problem. The approach is tested in two case studies and the performance of the controller is evaluated. The case studies indicate that the proposed approach outperforms current state-of-the-art simultaneous design and control strategies. This opens a new avenue to address simultaneous design and control of engineering systems.
AU  - Sachio,S
AU  - Mowbray,M
AU  - Papathanasiou,MM
AU  - del,Rio-Chanona EA
AU  - Petsagkourakis,P
DO  - 10.1016/j.cherd.2021.10.032
EP  - 169
PY  - 2022///
SN  - 0263-8762
SP  - 160
TI  - Integrating process design and control using reinforcement learning
T2  - Chemical Engineering Research and Design
UR  - http://dx.doi.org/10.1016/j.cherd.2021.10.032
VL  - 183
ER  -
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