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Explicit computation of sampling period in periodic event-triggered multi-agent control under limited data rate
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-6046-7129
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-7309-8086
2019 (English)In: IEEE Transactions on Control of Network Systems, E-ISSN 2325-5870, Vol. 6, no 4, p. 1366-1378Article in journal (Refereed) Published
Abstract [en]

This paper investigates the coordination of nonlinear sampled-data multi-agent systems subject to data rate constraint. The purpose is to design resource-efficient communication and control strategies that guarantee exponential synchronization. Two implementation scenarios are considered, the period time-triggered control and the period event-triggered control. One of the main difficulties of the problem is to obtain an explicit formula for the maximum allowable sampling period (MASP). To this end, an approach on finding the MASP for periodic time-triggered control is proposed first. Then, an asynchronous period event-triggered control strategy is formulated, a communication function and a control function are designed for each agent to determine respectively whether or not the sampled data and the control input should be transmitted at each sampling instant. Finally, the constraint of limited data rate is considered. An observer-based encoder-decoder and a finite-level quantizer are designed respectively for the Sensor-Controller communication and the Controller-Actuator communication such that certain constraint on the data rate is satisfied. It is shown that exponential synchronization can still be achieved in the presence of data rate constraint. A simulation example is given to illustrate the effectiveness of the theoretical results

Place, publisher, year, edition, pages
IEEE, 2019. Vol. 6, no 4, p. 1366-1378
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-259649DOI: 10.1109/TCNS.2018.2889012ISI: 000505738600009Scopus ID: 2-s2.0-85058899039OAI: oai:DiVA.org:kth-259649DiVA, id: diva2:1352745
Note

QC 20191009. QC 20200129

Available from: 2019-09-19 Created: 2019-09-19 Last updated: 2020-01-29Bibliographically approved

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Yu, PianDimarogonas, Dimos V.

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