Zobrazeno 1 - 10
of 271
pro vyhledávání: '"Chachuat, Benoît"'
Autor:
Lawrence, Nathan P., Damarla, Seshu Kumar, Kim, Jong Woo, Tulsyan, Aditya, Amjad, Faraz, Wang, Kai, Chachuat, Benoit, Lee, Jong Min, Huang, Biao, Gopaluni, R. Bhushan
Publikováno v:
Control Engineering Practice 2024
With the rise of deep learning, there has been renewed interest within the process industries to utilize data on large-scale nonlinear sensing and control problems. We identify key statistical and machine learning techniques that have seen practical
Externí odkaz:
http://arxiv.org/abs/2401.13836
Autor:
Gopaluni, R. Bhushan, Tulsyan, Aditya, Chachuat, Benoit, Huang, Biao, Lee, Jong Min, Amjad, Faraz, Damarla, Seshu Kumar, Kim, Jong Woo, Lawrence, Nathan P.
Over the last ten years, we have seen a significant increase in industrial data, tremendous improvement in computational power, and major theoretical advances in machine learning. This opens up an opportunity to use modern machine learning tools on l
Externí odkaz:
http://arxiv.org/abs/2209.11123
Autor:
Triantafyllou, Niki, Lyons, Ben, Bernardi, Andrea, Chachuat, Benoit, Kontoravdi, Cleo, Papathanasiou, Maria M.
Publikováno v:
In Computers and Chemical Engineering October 2024 189
This paper proposes a new class of real-time optimization schemes to overcome system-model mismatch of uncertain processes. This work's novelty lies in integrating derivative-free optimization schemes and multi-fidelity Gaussian processes within a Ba
Externí odkaz:
http://arxiv.org/abs/2111.05589
Publikováno v:
In IFAC PapersOnLine 2024 58(14):157-162
Publikováno v:
In IFAC PapersOnLine 2024 58(14):658-663
Publikováno v:
In IFAC PapersOnLine 2024 58(14):216-221
Autor:
del Rio-Chanona, Ehecatl Antonio, Petsagkourakis, Panagiotis, Bradford, Eric, Graciano, Jose Eduardo Alves, Chachuat, Benoit
This paper investigates a new class of modifier-adaptation schemes to overcome plant-model mismatch in real-time optimization of uncertain processes. The main contribution lies in the integration of concepts from the areas of Bayesian optimization an
Externí odkaz:
http://arxiv.org/abs/2009.08819
Autor:
Kusumo, Kennedy P., Gomoescu, Lucian, Paulen, Radoslav, Munoz, Salvador Garcia, Pantelides, Constantinos C., Shah, Nilay, Chachuat, Benoit
Publikováno v:
Ind. Eng. Chem. Res. 2020, 59, 6
Quality by design in pharmaceutical manufacturing hinges on computational methods and tools that are capable of accurate quantitative prediction of the design space. This paper investigates Bayesian approaches to design space characterization, which
Externí odkaz:
http://arxiv.org/abs/2008.05917
Publikováno v:
In Sustainable Production and Consumption December 2023 43:124-139