Zobrazeno 1 - 10
of 2 916
pro vyhledávání: '"Pfefferkorn P"'
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Lorenzo Giovannetti
Publikováno v:
Plato, Vol 24 (2023)
Externí odkaz:
https://doaj.org/article/31794afe7c874930b7f9e33d96230ff0
Autor:
Pfefferkorn, Maik, Findeisen, Rolf
Employing model predictive control to systems with unbounded, stochastic disturbances poses the challenge of guaranteeing safety, i.e., repeated feasibility and stability of the closed-loop system. Especially, there are no strict repeated feasibility
Externí odkaz:
http://arxiv.org/abs/2410.08186
Autor:
Hirt, Sebastian, Höhl, Andreas, Pohlodek, Johannes, Schaeffer, Joachim, Pfefferkorn, Maik, Braatz, Richard D., Findeisen, Rolf
Model predictive control (MPC) is a powerful tool for controlling complex nonlinear systems under constraints, but often struggles with model uncertainties and the design of suitable cost functions. To address these challenges, we discuss an approach
Externí odkaz:
http://arxiv.org/abs/2410.04982
Safe learning of control policies remains challenging, both in optimal control and reinforcement learning. In this article, we consider safe learning of parametrized predictive controllers that operate with incomplete information about the underlying
Externí odkaz:
http://arxiv.org/abs/2409.10171
Autor:
Munske Horst Haider
Publikováno v:
Zeitschrift für Rezensionen zur Germanistischen Sprachwissenschaft, Vol 12, Iss 1-2, Pp 8-13 (2020)
Externí odkaz:
https://doaj.org/article/90db22e3452e47debb8a91ebe9b83d9f
Autor:
Imane el Rhomri el Fatmi
Publikováno v:
Revue Internationale des Études du Développement, Vol 245, Pp 254-256 (2021)
Externí odkaz:
https://doaj.org/article/c2c987806272494e96996d06982912e4
Designing predictive controllers towards optimal closed-loop performance while maintaining safety and stability is challenging. This work explores closed-loop learning for predictive control parameters under imperfect information while considering cl
Externí odkaz:
http://arxiv.org/abs/2404.12187
We analyse the conservatism and regret of distributionally robust (DR) stochastic model predictive control (SMPC) when using moment-based ambiguity sets for modeling unknown uncertainties. To quantify the conservatism, we compare the deterministic co
Externí odkaz:
http://arxiv.org/abs/2309.12190
Autor:
Brenscheidt, Diana
Publikováno v:
Relaciones: Estudios de Historia y Sociedad; 2018, Vol. 39 Issue 156, p227-255, 29p