Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Martand Singhal"'
Publikováno v:
IFAC-PapersOnLine. 51:833-838
Optimal operating conditions for a process plant are typically obtained via model based optimization. However, due to modeling errors, the operating conditions found are often sub-optimal or, worse, they can violate critical process constraints. Henc
Publikováno v:
IFAC-PapersOnLine. 50:5718-5723
The modifier-adaptation methodology enables real-time optimization (RTO) of plant operation in the presence of considerable plant-model mismatch. It requires the estimation of plant gradients. Obtaining these gradients is expensive as it involves pot
Publikováno v:
Computers & Chemical Engineering. 98:61-69
In the context of real-time optimization, modifier-adaptation schemes use estimates of the plant gradients to achieve plant optimality despite plant-model mismatch. Plant feasibility is guaranteed upon convergence, but not at the successive operating
Publikováno v:
IFAC-PapersOnLine. 49:412-417
Recently, different real-time optimization (RTO) schemes that guarantee feasibility of all RTO iterates and monotonic convergence to the optimal plant operating point have been proposed. However, simulations reveal that these schemes converge very sl
Publikováno v:
Computers & Chemical Engineering. 132:106524
In the presence of plant-model mismatch, the estimation of plant gradients is key to the performance of measurement-based iterative optimization schemes. However, gradient estimation requires time-consuming experiments, wherein the plant is sequentia
Publikováno v:
IFAC-PapersOnLine. 48:176-181
This paper deals with the real-time optimization of uncertain plants and proposes an approach based on surrogate models to reach the plant optimum when the plant cost gradient is imperfectly known. It is shown that, for processes with only box constr
Autor:
Martand Singhal, Ravindra D. Gudi
Publikováno v:
IFAC Proceedings Volumes. 45:81-86
Optimal operation of batch processes in the presence of uncertainty has been an area of significant research interest. The use of online measurements as a source of information offers scope to mitigate the effects of uncertainty and attain optimal op
Iterative real-time optimization schemes that employ modifier adaptation add bias and gradient correction terms to the model that is used for optimization. These affine corrections lead to meeting the first-order necessary conditions of optimality of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::308f46511ceefe4c1e2e41afc5558d3f
https://infoscience.epfl.ch/record/261925
https://infoscience.epfl.ch/record/261925
Modifier adaptation is a real-time optimization (RTO) methodology that uses plant gradient estimates to correct model gradients, thereby driving the plant to optimality. However, obtaining accurate gradient estimates requires costly plant experiments
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b8230ed7bd27b5d8a0a314738714a67
https://infoscience.epfl.ch/record/258267
https://infoscience.epfl.ch/record/258267
Publikováno v:
ECC
Many real-time optimization schemes maximize process performance by performing a model-based optimization. However, due to plant-model mismatch, the model-based solution is often suboptimal. In modifier adaptation, measurements are used to correct th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c5fccf05669ff5ec713d1b1033f79e9
https://infoscience.epfl.ch/record/266384
https://infoscience.epfl.ch/record/266384