Gering, Stefan ; Willert, Volker (2023)
Solving the N-Consensus Problem: Combining Clustering and Synchronization.
In: IFAC Proceedings Volumes, 2012, 45 (26)
doi: 10.26083/tuprints-00023317
Article, Secondary publication, Publisher's Version
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| Item Type: | Article |
|---|---|
| Type of entry: | Secondary publication |
| Title: | Solving the N-Consensus Problem: Combining Clustering and Synchronization |
| Language: | English |
| Date: | 2023 |
| Place of Publication: | Darmstadt |
| Year of primary publication: | 2012 |
| Publisher: | IFAC - International Federation of Automatic Control |
| Journal or Publication Title: | IFAC Proceedings Volumes |
| Volume of the journal: | 45 |
| Issue Number: | 26 |
| DOI: | 10.26083/tuprints-00023317 |
| Corresponding Links: | |
| Origin: | Secondary publication service |
| Abstract: | This article presents a state synchronization method within multi-agent systems upon multiple states. Based on their formation in state space, the agents decide on a clustering and synchronize their states within these clusters. The solution steps for this N-consensus problem, clustering and synchronization, may both be solved entirely in a decentral manner. This is achieved by means of a distributed Variational Bayes to describe the distribution of the agents' positions as a mixture of densities. The entire N-consensus problem is illustrated with graphical probabilistic models whose underlying potential is shown to be maximized when reaching the final N-consensus. An improvement of the overall convergence speed is achieved by a dynamical adaption of the distributed Variational Bayes, which leads to an intertwining of clustering and synchronization. |
| Uncontrolled Keywords: | Autonomous mobile robots, consensus, distributed control, probabilistic models |
| Status: | Publisher's Version |
| URN: | urn:nbn:de:tuda-tuprints-233178 |
| Additional Information: | Zugl. Konferenzveröffentlichung: 3rd IFAC Workshop on Distributed Estimation and Control in Networked Systems, 14.-15.09.2012, Santa Barbara, USA |
| Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
| Divisions: | 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Intelligent Systems |
| Date Deposited: | 10 Mar 2023 10:09 |
| Last Modified: | 26 May 2023 07:41 |
| URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/23317 |
| PPN: | 507994248 |
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