Economic nonlinear model predictive control using hybrid mechanistic data-driven models for optimal operation in real-time electricity markets: In-silico application to air separation processes

Research article (Journal of Process Control, 2019) · cited 40× · AI/ML
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Economic nonlinear model predictive control using hybrid mechanistic data-driven models for optimal operation in real-time electricity markets: In-silico application to air separation processes

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Economic nonlinear model predictive control using hybrid mechanistic data-driven models for optimal operation in real-time electricity markets: In-silico application to air separation processes is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Economic nonlinear model predictive control using hybrid mechanistic data-driven models for optimal operation in real-time electricity markets: In-silico application to air separation processes. Retrieved May 24, 2026, from https://4ort.xyz/entity/economic-nonlinear-model-predictive-control-using-hybrid-mechanistic-data-driven-models-for-optimal-operation-in-real-ti
MLA “Economic nonlinear model predictive control using hybrid mechanistic data-driven models for optimal operation in real-time electricity markets: In-silico application to air separation processes.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/economic-nonlinear-model-predictive-control-using-hybrid-mechanistic-data-driven-models-for-optimal-operation-in-real-ti.
BibTeX @misc{4ortxyz_economic-nonlinear-model-predictive-control-using-hybrid-mechanistic-data-driven-models-for-optimal-operation-in-real-ti_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Economic nonlinear model predictive control using hybrid mechanistic data-driven models for optimal operation in real-time electricity markets: In-silico application to air separation processes}}, year = {2026}, url = {https://4ort.xyz/entity/economic-nonlinear-model-predictive-control-using-hybrid-mechanistic-data-driven-models-for-optimal-operation-in-real-ti}, note = {Accessed: 2026-05-24}}
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