Zobrazeno 1 - 10
of 10 274
pro vyhledávání: '"A. Alamo"'
Chance constraints ensure the satisfaction of constraints under uncertainty with a desired probability. This scheme is unfortunately sensitive to assumptions of the probability distribution of the uncertainty, which are difficult to verify. The uncer
Externí odkaz:
http://arxiv.org/abs/2409.01177
Publikováno v:
Diabetology & Metabolic Syndrome, Vol 15, Iss 1, Pp 1-1 (2023)
Externí odkaz:
https://doaj.org/article/55b02fd6a2c44402bacf244e1d042626
The main benefit of model predictive control (MPC) is its ability to steer the system to a given reference without violating the constraints while minimizing some objective. Furthermore, a suitably designed MPC controller guarantees asymptotic stabil
Externí odkaz:
http://arxiv.org/abs/2406.16496
Autor:
Krupa, Pablo, Köhler, Johannes, Ferramosca, Antonio, Alvarado, Ignacio, Zeilinger, Melanie N., Alamo, Teodoro, Limon, Daniel
This paper provides a comprehensive tutorial on a family of Model Predictive Control (MPC) formulations, known as MPC for tracking, which are characterized by including an artificial reference as part of the decision variables in the optimization pro
Externí odkaz:
http://arxiv.org/abs/2406.06157
The number and dynamic nature of web and mobile applications presents significant challenges for assessing their compliance with data protection laws. In this context, symbolic and statistical Natural Language Processing (NLP) techniques have been em
Externí odkaz:
http://arxiv.org/abs/2405.20900
Publikováno v:
Diabetology & Metabolic Syndrome, Vol 11, Iss 1, Pp 1-12 (2019)
Abstract The combined harmful effects of cigarette smoking and hyperglycemia can accelerate vascular damage in patients with diabetes who smoke, as is well known. Can smoking cause diabetes? What are the effects of smoking on macro and microvascular
Externí odkaz:
https://doaj.org/article/43e561c8143e4154abb8cd9bfd991da5
Conformal predictions make it possible to define reliable and robust learning algorithms. But they are essentially a method for evaluating whether an algorithm is good enough to be used in practice. To define a reliable learning framework for classif
Externí odkaz:
http://arxiv.org/abs/2403.10368
Autor:
Roh, Heejung, Kim, Dong-Ha, Cho, Yeongsu, Jo, Young-Moo, del Alamo, Jesús A., Kulik, Heather J., Dincă, Mircea, Gumyusenge, Aristide
Metal-organic frameworks (MOFs) are promising materials for gas sensing but are often limited to single-use detection. We demonstrate a hybridization strategy synergistically deploying conductive MOFs (cMOFs) and conductive polymers (cPs) as two comp
Externí odkaz:
http://arxiv.org/abs/2403.08914
Publikováno v:
in IEEE Control Systems Letters, vol. 8, pp. 1499-1504, 2024
Model Predictive Control (MPC) is a popular control approach due to its ability to consider constraints, including input and state restrictions, while minimizing a cost function. However, in practice, these constraints can result in feasibility issue
Externí odkaz:
http://arxiv.org/abs/2403.04601
The main objective of tracking control is to steer the tracking error, that is the difference between the reference and the output, to zero while the plant's operation limits are satisfied. This requires that some assumptions on the evolution of the
Externí odkaz:
http://arxiv.org/abs/2403.02973