Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Friedrich Solowjow"'
Publikováno v:
Sensors, Vol 20, Iss 1, p 260 (2020)
Wireless sensor networks are used in a wide range of applications, many of which require real-time transmission of the measurements. Bandwidth limitations result in limitations on the sampling frequency and number of sensors. This problem can be addr
Externí odkaz:
https://doaj.org/article/df18923b1b7549c4bf958fa54b77df40
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264184
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2a39cec0d7d1c5ed55762887970ab58
https://doi.org/10.1007/978-3-031-26419-1_9
https://doi.org/10.1007/978-3-031-26419-1_9
Robust controllers ensure stability in feedback loops designed under uncertainty but at the cost of performance. Model uncertainty in time-invariant systems can be reduced by recently proposed learning-based methods, which improve the performance of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e7dc6b76914fb610b2e49190c73d05e
http://arxiv.org/abs/2207.14252
http://arxiv.org/abs/2207.14252
Publikováno v:
13 Seiten (2021). doi:10.18154/RWTH-2021-05758
Safety constraints and optimality are important, but sometimes conflicting criteria for controllers. Although these criteria are often solved separately with different tools to maintain formal guarantees, it is also common practice in reinforcement l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7635afada76de3f95ff9aa9d8cfb1999
http://arxiv.org/abs/2105.12204
http://arxiv.org/abs/2105.12204
Publikováno v:
Sensors
Volume 20
Issue 1
Sensors (Basel, Switzerland)
Sensors 20(1), 260 (2020). doi:10.3390/s20010260 special issue: "Special Issue "Inertial Sensors" / Special Issue Editors: Dr. Thomas Seel, Guest Editor; Dr. Manon Kok, Guest Editor; Dr. Ryan S. McGinnis, Guest Editor"
Sensors, Vol 20, Iss 1, p 260 (2020)
Volume 20
Issue 1
Sensors (Basel, Switzerland)
Sensors 20(1), 260 (2020). doi:10.3390/s20010260 special issue: "Special Issue "Inertial Sensors" / Special Issue Editors: Dr. Thomas Seel, Guest Editor; Dr. Manon Kok, Guest Editor; Dr. Ryan S. McGinnis, Guest Editor"
Sensors, Vol 20, Iss 1, p 260 (2020)
Wireless sensor networks are used in a wide range of applications, many of which require real-time transmission of the measurements. Bandwidth limitations result in limitations on the sampling frequency and number of sensors. This problem can be addr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d4e78d93d8d0f66292465a978f7365f
https://depositonce.tu-berlin.de/handle/11303/11048
https://depositonce.tu-berlin.de/handle/11303/11048
Publikováno v:
CDC
We consider controlling a heterogeneous stochastic growth process defined on a lattice with a control resource constraint. We address heterogeneous effects in three respects: (i) the process grows at different rates for different directions on the la
Publikováno v:
ACC
In networked control systems, communication is a shared and therefore scarce resource. Event-triggered control (ETC) can achieve high performance control with a significantly reduced amount of samples compared to classical, periodic control schemes.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7861228e91ecf3e32972663e78e68d8a
http://arxiv.org/abs/1903.08046
http://arxiv.org/abs/1903.08046
Autor:
Sebastian Trimpe, Friedrich Solowjow
Publikováno v:
Automatica. 117:109009
The efficient exchange of information is an essential aspect of intelligent collective behavior. Event-triggered control and estimation achieve some efficiency by replacing continuous data exchange between agents with intermittent, or event-triggered
Communication load is a limiting factor in many real-time systems. Event-triggered state estimation and event-triggered learning methods reduce network communication by sending information only when it cannot be adequately predicted based on previous
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3a5ec6ee062890f127220878baea4ae
When models are inaccurate, the performance of model-based control will degrade. For linear quadratic control, an event-triggered learning framework is proposed that automatically detects inaccurate models and triggers the learning of a new process m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::547864ef806a456b1b0226e1ece92400