Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Eivind Bøhn"'
Publikováno v:
Physica D : Non-linear phenomena
Hybrid machine learning based on Hamiltonian formulations has recently been successfully demonstrated for simple mechanical systems, both energy conserving and not energy conserving. We introduce a pseudo-Hamiltonian formulation that is a generalizat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb3f7d6d9b5743807195a293240efb97
https://hdl.handle.net/11250/3051813
https://hdl.handle.net/11250/3051813
Publikováno v:
Engineering Applications of Artificial Intelligence. 123:106211
Model predictive control (MPC) is increasingly being considered for control of fast systems and embedded applications. However, the MPC has some significant challenges for such systems. Its high computational complexity results in high power consumpt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::492255636f2eab94d3fea9e2a5cd8e51
https://doi.org/10.1016/j.engappai.2023.106211
https://doi.org/10.1016/j.engappai.2023.106211
Publikováno v:
IFAC-PapersOnLine. 54:257-262
In control applications there is often a compromise that needs to be made with regards to the complexity and performance of the controller and the computational resources that are available. For instance, the typical hardware platform in embedded con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fc8bf3a84abd2c135603a6c566c9aaa
https://doi.org/10.1016/j.ifacol.2021.10.362
https://doi.org/10.1016/j.ifacol.2021.10.362
Publikováno v:
IFAC-PapersOnLine. 54:314-320
Model predictive control (MPC) is a powerful trajectory optimization control technique capable of controlling complex nonlinear systems while respecting system constraints and ensuring safe operation. The MPC's capabilities come at the cost of a high
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2c64dc7f757ae41d364c2f6495a7e95
https://doi.org/10.1016/j.ifacol.2021.08.563
https://doi.org/10.1016/j.ifacol.2021.08.563
Publikováno v:
IFAC-PapersOnLine. 53:8090-8096
Reinforcement learning in domains with sparse rewards is a difficult problem, and a large part of the training process is often spent searching the state space in a more or less random fashion for learning signals. For control problems, we often have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16c6c5f9faf13dfb28c626c37d0f8816
https://doi.org/10.1016/j.ifacol.2020.12.2278
https://doi.org/10.1016/j.ifacol.2020.12.2278
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031105241
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e0d757a88e5ac3ad2b70e7d7b019fdd
https://doi.org/10.1007/978-3-031-10525-8_6
https://doi.org/10.1007/978-3-031-10525-8_6
Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pilots, thereby restricting the conditions UAVs can operate in and the types of missions they can accomp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ab9eb7575b3e55ea0ed0787ffe8c08d