Geodesic
Topology design for group consensus in directed multi-agent systems
Kybernetika, Tome 56 (2020) no. 3, pp. 578-597
Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

Voir la notice de l'article

In this paper, we investigate the grouping behavior of multi-agent systems by exploiting the graph structure. We propose a novel algorithm for designing a network from scratch which yields the desired grouping in a network of agents utilizing a consensus-based algorithm. The proposed algorithm is shown to be optimal in the sense that it consists of the minimum number of links. Furthermore, we examine the effect of adding new vertices and edges to the network on the number of groups formed in the group consensus problem. These results can be further utilized by the network topology designer to restructure the network and achieve the desired grouping. Theoretical results are illustrated with simulation examples.
In this paper, we investigate the grouping behavior of multi-agent systems by exploiting the graph structure. We propose a novel algorithm for designing a network from scratch which yields the desired grouping in a network of agents utilizing a consensus-based algorithm. The proposed algorithm is shown to be optimal in the sense that it consists of the minimum number of links. Furthermore, we examine the effect of adding new vertices and edges to the network on the number of groups formed in the group consensus problem. These results can be further utilized by the network topology designer to restructure the network and achieve the desired grouping. Theoretical results are illustrated with simulation examples.
DOI : 10.14736/kyb-2020-3-0578
Classification : 93A14, 93C05, 93C85
Keywords: group consensus; topology design; multi-agent agreement 
@article{10_14736_kyb_2020_3_0578,
     author = {Cihan, Onur},
     title = {Topology design for group consensus in directed multi-agent systems},
     journal = {Kybernetika},
     pages = {578--597},
     year = {2020},
     volume = {56},
     number = {3},
     doi = {10.14736/kyb-2020-3-0578},
     mrnumber = {4131744},
     zbl = {07250738},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.14736/kyb-2020-3-0578/}
}
TY  - JOUR
AU  - Cihan, Onur
TI  - Topology design for group consensus in directed multi-agent systems
JO  - Kybernetika
PY  - 2020
SP  - 578
EP  - 597
VL  - 56
IS  - 3
UR  - http://geodesic.mathdoc.fr/articles/10.14736/kyb-2020-3-0578/
DO  - 10.14736/kyb-2020-3-0578
LA  - en
ID  - 10_14736_kyb_2020_3_0578
ER  - 
%0 Journal Article
%A Cihan, Onur
%T Topology design for group consensus in directed multi-agent systems
%J Kybernetika
%D 2020
%P 578-597
%V 56
%N 3
%U http://geodesic.mathdoc.fr/articles/10.14736/kyb-2020-3-0578/
%R 10.14736/kyb-2020-3-0578
%G en
%F 10_14736_kyb_2020_3_0578
Cihan, Onur. Topology design for group consensus in directed multi-agent systems. Kybernetika, Tome 56 (2020) no. 3, pp. 578-597. doi: 10.14736/kyb-2020-3-0578

[1] Alonso-Mora, J., Montijano, E., Nägeli, T., Hilliges, O., Schwager, M., Rus, D.: Distributed multi-robot formation control in dynamic environments. Auton. Robot. 43 (2018), 1079-1100. | DOI

[2] Amelina, N., Fradkov, A., Jiang, Y., Vergados, D. J.: Approximate consensus in stochastic networks with application to load balancing. IEEE Trans. Inform. Theory 61 (2015), 1739-1752. | DOI | MR

[3] Aragues, R., Cortes, J., Sagues, C.: Distributed consensus on robot networks for dynamically merging feature-based maps. IEEE Trans. Robot. 28 (2012), 840-854. | DOI

[4] Cao, Y., Stuart, D., Ren, W., Meng, Z.: Distributed containment control for multiple autonomous vehicles with double-integrator dynamics: Algorithms and experiments. IEEE Trans. Control Syst. Technol. 19, (2011), 929-938. | DOI | MR

[5] Chen, Z., Xing, Y., Qin, H.: Multiagent opinion dynamics influenced by individual susceptibility and anchoring effect. Kybernetika 55 (2019), 714-726. | DOI | MR

[6] Choi, H.-L., Brune, L., How, J.: Consensus-based decentralized auctions for robust task allocation. IEEE Trans. Robot. 25 (2009), 912-926. | DOI

[7] Develer, Ü., Akar, M.: Cluster consensus in first and second-order continuous-time networks with input and communication delays. Int. J. Control (2019). | DOI

[8] Dimarogonas, D. V., Kyriakopoulos, K. J.: On the rendezvous problem for multiple nonholonomic agents. IEEE Trans. Automat. Control 52 (2007), 916-922. | DOI | MR

[9] Erkan, Ö. F., Cihan, O., Akar, M.: Distributed consensus with multi-equilibria in directed networks. In: 2017 American Control Conference, Seattle 2017. | DOI

[10] Erkan, Ö. F., Cihan, O., Akar, M.: Analysis of distributed consensus protocols with multi-equilibria under time-delays. J. Franklin Inst. 355 (2018), 332-360. | DOI | MR

[11] Hegselmann, R., Krause, U.: Opinion dynamics and bounded confidence: Models, analysis and simulation. J. Artif. Soc. Soc. Simul. 5 (2002).

[12] Hu, J.: Bipartite consensus control of multiagent systems on coopetition networks. Abstr. Appl. Anal. Article ID: 689070 (2014), 1-9. | DOI | MR

[13] Hu, J., Zheng, W.-X.: Emergent collective behaviors on coopetition networks. Phys. Lett. A 378 (2014), 1787-1796. | DOI | MR

[14] Jin, J., Gans, N.: Collision-free formation and heading consensus of nonholonomic robots as a pose regulation problem. Rob. Auton. Syst. 95 (2017), 25-36. | DOI

[15] Mirzaei, M., Atrianfar, H., Mehdipour, N., Abdollahi, F.: Asynchronous consensus of continuous-time lagrangian systems with switching topology and non-uniform time delay. Rob. Auton. Syst. 83 (2016), 106-114. | DOI

[16] Mou, S., Liu, J., Morse, A. S.: A distributed algorithm for solving a linear algebraic equation. IEEE Trans. Automat. Control 60 (2015), 2863-2878. | DOI | MR

[17] Navarro, I., Matía, F.: Distributed orientation agreement in a group of robots. Auton. Robot. 33 (2012), 445-465. | DOI

[18] Olfati-Saber, R., Murray, R. M.: Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. Automat. Control 49 (2004), 1520-1533. | DOI | MR

[19] Ren, W., Beard, R.: Consensus seeking in multiagent systems under dynamically changing interaction topologies. IEEE Trans. Automat. Control 50 (2005), 655-661. | DOI | MR

[20] Schenato, L., Fiorentin, F.: Average TimeSynch: A consensus-based protocol for clock synchronization in wireless sensor networks. Automatica 47 (2011), 1878-1886. | DOI | MR

[21] Xu, Z., Cai, X.: Group consensus algorithms based on preference relations. Inform. Sci. 181 (2011), 150-162. | DOI

[22] Yang, S., Tan, S., Xu, J.-X.: Consensus based approach for economic dispatch problem in a smart grid. IEEE Trans. Power Syst. 28 (2013), 4416-4426. | DOI

[23] Zelazo, D., Schuler, S., Allgöwer, F.: Performance and design of cycles in consensus networks. Syst. Control. Lett. 62 (2013), 85-96. | DOI | MR

[24] Zhang, H.-T., Chen, Z., Mo, X.: Effect of adding edges to consensus networks with directed acyclic graphs. IEEE Trans. Automat. Control 62 (2017), 4891-4897. | DOI | MR

[25] Zhang, X., Peng, Z., Yang, S., Wen, G., Rahmani, A.: Distributed fixed-time consensus-based formation tracking for multiple nonholonomic wheeled mobile robots under directed topology. Int. J. Control (2019). | DOI

[26] Zhu, Q., Wang, X., Lin, Q.: Consensus-based impact-time-control guidance law for cooperative attack of multiple missiles. Kybernetika 53 (2017), 563-577. | DOI | MR

Cité par Sources :