A New Consensus Algorithm for Multi-Agent Systems via Decentralized Dynamic Output Feedback
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Abstract
In this paper, we study a consensus problem for multi-agent systems via dynamic output feedback control. The entire system is decentralized in the sense that each agent can only obtain output information from its neighbor agents. For practical purpose, we assume that actuator limitation exists, and require that the consensus be achieved among the agents at a specified convergence rate. By using an appropriate coordinate transformation, we reduce the consensus problem on hand to solving a strict matrix inequality, and then propose to use the homotopy based method for solving the matrix inequality. It turns out that our algorithm includes the existing graph Laplacian based algorithm as a special case.
Keywords
Multi-agent systems Consensus algorithm Decentralized dynamic output feedback Graph Laplacian Matrix inequality Homotopy method LMIPreview
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References
- 1.Saber, R.O., Fax, J.A., Murray, R.M.: Consensus and cooperation in networked multi-agent systems. Proc. IEEE 95(1), 215–233 (2007)CrossRefGoogle Scholar
- 2.Saber, R.O., Murray, R.M.: Consensus protocols for networks of dynamic agents. In: Proceedings of American Control Conference, pp. 951–956. Denver, USA (2003)Google Scholar
- 3.Saber, R.O., Murray, R.M.: Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. Automat. Contr. 49(9), 1520–1533 (2004)CrossRefGoogle Scholar
- 4.Fax, J.A.: Optimal and cooperative control of vehicle formations. Ph.D. dissertation, California Institute of Technology, Pasadena, CA (2001)Google Scholar
- 5.Fax, J.A., Murray, R.M.: Information flow and cooperative control of vehicle formations. IEEE Trans. Automat. Contr. 49(9), 1465–1476 (2004)CrossRefMathSciNetGoogle Scholar
- 6.Zhai, G., Okuno, S., Imae, J., Kobayashi, T.: Consensus algorithms for multi-agent systems: a matrix inequality based approach. In: Proceedings of the 2009 IEEE International Conference on Networking, Sensing and Control, pp. 891–896. Okayama, Japan (2009)Google Scholar
- 7.Namerikawa, T., Yoshioka, C.: Consensus control of observer-based multi-agent system with communication delay. In: Proceedings of the SICE Annual Conference 2008, pp. 2414–2419. Tokyo, Japan (2008)Google Scholar
- 8.Khalil, H.K.: Nonlinear Systems, 2nd edn. Prentice Hall (2002)Google Scholar
- 9.Lin, Z., Broucke, M., Francis, B.: Local control strategies for groups of mobile autonomous agents. IEEE Trans. Automat. Contr. 49(4), 622–629 (2004)CrossRefMathSciNetGoogle Scholar
- 10.Mohar, B.: The Laplacian spectrum of graphs. In: Alavi, Y., Chartrand, G., Ollermann, O., Schwenk, A. (eds.) Graph Theory, Combinatorics, and Applications, pp. 871–898. Wiley, New York (1991)Google Scholar
- 11.Richter, S., DeCarlo, R.: Continuation methods: theory and applications. IEEE Trans. Automat. Contr. AC-28(6), 660–665 (1983)CrossRefMathSciNetGoogle Scholar
- 12.Zhai, G., Ikeda, M., Fujisaki, Y.: Decentralized \({\mathcal{H}}_{\infty}\) controller design: a matrix inequality approach using a homotopy method. Automatica 37(4), 565–572 (2001)MATHCrossRefMathSciNetGoogle Scholar
- 13.Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V.: Linear Matrix Inequalities in System and Control Theory. SIAM, Philadelphia (1994)MATHGoogle Scholar
- 14.Gahinet, P., Nemirovskii, A., Laub, A., Chilali, M.: The LMI control toolbox. In: Proceedings of the 33rd IEEE Conference on Decision and Control, pp. 2038–2041. Lake Buena Vista, USA (1994)Google Scholar