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State-dependent Data Queuing in Shared-resource Networked Control Systems
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-9940-5929
Tech Univ Munich, Chair Informat Oriented Control, Munich, Germany..
2018 (English)In: 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1731-1737, article id 8619752Conference paper, Published paper (Refereed)
Abstract [en]

In the design of shared resource networked control systems (NCSs), resource managers play an important role to appropriately allocate limited resources across the distributed system. They are often used to fairly distribute the limited bandwidth among the medium-sharing entities at the expense of delaying or discarding unnecessary data samples. Considering the rapidly growing volume of information being exchanged, a relevant scenario for efficient resource management is state-dependent data buffering via network queues. In this paper, we propose state-dependent data buffering for shared-resource NCSs, such that the buffer state, i.e. queue length, can be controlled depending on the real-time conditions of both the control systems and the communication network. We consider that the transmission decisions at the sensor sides are taken by event-based schedulers, and those data eventually sent for transmission are queued and processed depending on the available communication resource. We derive sufficient conditions under which the NCS with the proposed cross-layer transmission scheme is stable in almost sure mean-square sense. Moreover, we show performance improvements resulting from our proposed design in comparison with its state-independent counterpart.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 1731-1737, article id 8619752
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-245107DOI: 10.1109/CDC.2018.8619752ISI: 000458114801101Scopus ID: 2-s2.0-85062186801ISBN: 978-1-5386-1395-5 (print)OAI: oai:DiVA.org:kth-245107DiVA, id: diva2:1294290
Conference
57th IEEE Conference on Decision and Control, CDC 2018; Centre of the Fontainebleau in Miami Beach Miami; United States; 17 December 2018 through 19 December 2018
Note

QC 20190307

Available from: 2019-03-07 Created: 2019-03-07 Last updated: 2024-03-18Bibliographically approved

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Mamduhi, Mohammad H.Baras, John S.Johansson, Karl Henrik

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