Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Sven Brüggemann"'
Autor:
Sven Brüggemann, Theodore Chan, Gabriel Wardi, Jess Mandel, John Fontanesi, Robert R. Bitmead
Publikováno v:
Informatics in Medicine Unlocked, Vol 24, Iss , Pp 100618- (2021)
The SARS-CoV-2 (COVID-19) pandemic has placed unprecedented demands on entire health systems and driven them to their capacity, so that health care professionals have been confronted with the difficult problem of ensuring appropriate staffing and res
Externí odkaz:
https://doaj.org/article/131ff9ec0b7f4eca8dff55e0bc4f9b14
Autor:
Corrado Possieri, Sven Brüggemann
Publikováno v:
IEEE Control Systems Letters 5 (2021): 1267–1272. doi:10.1109/LCSYS.2020.3032083
info:cnr-pdr/source/autori:Bruggemann, Sven; Possieri, Corrado/titolo:On the Use of Difference of Log-Sum-Exp Neural Networks to Solve Data-Driven Model Predictive Control Tracking Problems/doi:10.1109%2FLCSYS.2020.3032083/rivista:IEEE Control Systems Letters/anno:2021/pagina_da:1267/pagina_a:1272/intervallo_pagine:1267–1272/volume:5
ACC
Proceedings of the American Control Conference 2021-May (2021): 448–453. doi:10.23919/ACC50511.2021.9483344
info:cnr-pdr/source/autori:Bruggemann, Sven; Possieri, Corrado/titolo:On the Use of Difference of Log-Sum-Exp Neural Networks to Solve Data-Driven Model Predictive Control Tracking Problems/doi:10.23919%2FACC50511.2021.9483344/rivista:Proceedings of the American Control Conference/anno:2021/pagina_da:448/pagina_a:453/intervallo_pagine:448–453/volume:2021-May
info:cnr-pdr/source/autori:Bruggemann, Sven; Possieri, Corrado/titolo:On the Use of Difference of Log-Sum-Exp Neural Networks to Solve Data-Driven Model Predictive Control Tracking Problems/doi:10.1109%2FLCSYS.2020.3032083/rivista:IEEE Control Systems Letters/anno:2021/pagina_da:1267/pagina_a:1272/intervallo_pagine:1267–1272/volume:5
ACC
Proceedings of the American Control Conference 2021-May (2021): 448–453. doi:10.23919/ACC50511.2021.9483344
info:cnr-pdr/source/autori:Bruggemann, Sven; Possieri, Corrado/titolo:On the Use of Difference of Log-Sum-Exp Neural Networks to Solve Data-Driven Model Predictive Control Tracking Problems/doi:10.23919%2FACC50511.2021.9483344/rivista:Proceedings of the American Control Conference/anno:2021/pagina_da:448/pagina_a:453/intervallo_pagine:448–453/volume:2021-May
We employ Difference of Log-Sum-Exp neural networks to generate a data-driven feedback controller based on Model Predictive Control (MPC) to track a given reference trajectory. By using this class of networks to approximate the MPC-related cost funct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::517b9d844ddbfecfe9d8dbbf3970f0b8
http://www.scopus.com/record/display.url?eid=2-s2.0-85096083495&origin=inward
http://www.scopus.com/record/display.url?eid=2-s2.0-85096083495&origin=inward
Autor:
Robert R. Bitmead, Sven Brüggemann
Publikováno v:
Automatica. 136:110033
This work deals with the problem of simultaneous regulation and model parameter estimation in adaptive model predictive control. We propose an adaptive model predictive control and conditions which guarantee a persistently exciting closed loop sequen
Autor:
Robert R. Bitmead, Sven Brüggemann
We extend results of the recursive-least-squares-with-forgetting-factor identifier for single-input-single-output systems to the multiple-output case by, under the assumption of persistence of excitation, deriving the corresponding minimized objectiv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a63f30aade75734596aedf9973da39ae
http://arxiv.org/abs/2003.07334
http://arxiv.org/abs/2003.07334
Autor:
Robert R. Bitmead, Sven Brüggemann
Publikováno v:
CDC
Stochastic optimal output feedback control, in all but linear situations, involves duality of the control signal. That is, the control serves two countervailing purposes: to regulate the plant state and to enhance its observability. Optimal solutions