Artificial Swarm System: Boundedness, Convergence, and Control
Publication: Journal of Aerospace Engineering
Volume 21, Issue 4
Abstract
An artificial swarm system consisting of multiagents is considered in this paper. The agents may interact with each other based on their relative position. Each agent exhibits a repulsion/attraction behavior toward another agent, which mimics some biological swarm systems. The performance of each individual agent is the accumulation of these respective considerations toward other agents. The overall performance of the swarm system is analyzed, which includes uniform boundedness, uniform ultimate boundedness, and convergence. This mimics aggregation and formation in biological systems. The control design for each agent toward achieving the performance is then proposed. The control is a mimic of nature’s strategy in constraining mechanical systems.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The writer is grateful for helpful discussions with Professor F. E. Udwadia of the University of Southern California.
References
Al-Awami, A. T., Abdel-Magid, Y. L., and Abido, M. A. (2007). “A particle-swarm-based approach of power system stability enhancement with unified power flow controller.” Int. J. Electr. Power Energy Syst., 29(3), 251–259.
Balch, T., and Arkin, R. C. (1998). “Behavior based formation control for multirobot teams.” IEEE Trans. Rob. Autom., 14(6), 926–939.
Chandrasekaran, S., and Hougen, D. F. (2006). “Swarm intelligence for cooperation of bio-nano robots using quorum sensing.” Proc., 2nd American Society for Microbiology/IEEE Engineering in Medicine and Biology Society Conf. on Bio, Micro and Nanosystems, IEEE, San Francisco, 15–18.
Chen, X. B., Pan, F., Li, L., and Fang, H. (2006). “Practical stability analysis for swarm systems.” IECON 2006–32nd Annual Conference on IEEE Industrial Electronics, IEEE, Paris, 3904–3909.
Chen, Y. H. (1986). “On the deterministic performance of uncertain dynamical systems.” Int. J. Control, 43(5), 1557–1579.
Chen, Y. H., Leitmann, G., and Chen, J. S. (1998). “Robust control for rigid serial manipulators: A general setting.” Proc., 1998 American Control Conf., ACC, Philadelphia, 912–916.
Clerc, M., and Kennedy, J. (2002). “The particle swarm—Explosion, stability, and convergence in a multidimensional complex space.” IEEE Trans. Evol. Comput., 6(1), 58–73.
Darbha, S., and Rajagopal, K. R. (1999). “Intelligent cruise control systems and traffic flow stability.” Transp. Res., Part C: Emerg. Technol., 7(6), 329–352.
Desai, J. P., Ostrowski, J., and Kumar, V. (1998). “Controlling formations of multiple mobile robots.” Proc., 1998 IEEE Int. Conf. on Robotics and Automation, IEEE, Leuven, Belgium, 2864–2869.
Egerstedt, M., and Hu, X. (2001). “Formation constrained multi-agent control.” IEEE Trans. Rob. Autom., 17(6), 947–951.
Gazi, V., and Passino, K. M. (2003). “Stability analysis of swarms.” IEEE Trans. Autom. Control, 48(4), 692–697.
Giulietti, F., Pollini, L., and Innocenti, M. (2000). “Autonomous formation flight.” IEEE Control Syst. Mag., 20(6), 34–44.
Grunbaum, D., and Okubo, A. (1994). “Modelling social animal aggregation.” Frontiers in theoretical biology, S. A. Levin, ed., Springer, New York, 296–325.
Hedrick, J. K., Tomizuka, M., and Varaiya, P. (1994). “Control issues in automated highway systems.” IEEE Control Syst. Mag., 14(6), 21–32.
Khalil, H. K. (2002). Nonlinear systems, 3rd Ed., Prentice-Hall, Upper Saddle River, N.J.
Mogilner, A., Bent, L., Spiros, A., and Edelstein-Keshet, L. (2003). “Mutual interactions, potentials and individual distance in a social aggregation.” J. Math. Biol., 47(4), 353–389.
Okubo, A. (1986). “Dynamical aspects of animal grouping: Swarm schools, flocks, and herbs.” Adv. Biophys., 22(1), 1–94.
Pan, F., Chen, X., and Li, L. (2006). “Stability analysis of stochastic swarms system.” The 6th World Congress on Intelligent Control and Automation, Dalian, China, 1048–1051.
Papastavridis, J. G. (2002). Analytical mechanics, Oxford University Press, New York.
Parrish, J., Viscido, S., and Grunbaum, D. (2003). “Self-organized fish schools: An examination of emergent properties.” Biol. Bull., 202(3), 296–305.
Rosenberg, R. M. (1977). Analytical dynamics of discrete systems, Plenum, New York.
Udwadia, F. E., and Kalaba, R. E. (1992). “A new perspective on constrained motion.” Proc. R. Soc. London, Ser. A, 439(1906), 407–410.
Udwadia, F. E., and Kalaba, R. E. (1996). Analytical dynamics: A new approach, Cambridge University Press, Cambridge, U.K.
Udwadia, F. E., and Kalaba, R. E. (2002). “On the foundations of analytical dynamics.” Int. J. Nonlinear Mech., 37(6), 1079–1090.
Udwadia, F. E., Kalaba, R. E., and Eun, H.-C. (1997). “Equations of motion for constrained mechanical systems and the extended DAlembert principle.” Q. Appl. Math., 56(2), 321–331.
Information & Authors
Information
Published In
Journal of Aerospace Engineering
Volume 21 • Issue 4 • October 2008
Pages: 288 - 293
Copyright
© 2008 American Society of Civil Engineers.
History
Received: Jun 26, 2007
Accepted: Dec 10, 2007
Published online: Oct 1, 2008
Published in print: Oct 2008
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.