The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Distributed tracking control of leader–follower multi-agent systems under noisy measurement
Open accessAbstract
In this paper, a distributed tracking control scheme with distributed estimators has been developed for a leader-follower multi-agent system with measurement noises and directed interconnection topology. It is supposed that each follower can only measure the relative positions of its neighbors in a noisy environment, including the relative position of the second-order active leader. A neighbor-based tracking protocol together with distributed estimators is designed based on a novel velocity decomposition technique. It is shown that the closed loop tracking control system is stochastically stable in mean square and the estimation errors converge to zero in mean square as well. A simulation example is finally given to illustrate the performance of the proposed control scheme.
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Cites
Coordination of groups of mobile autonomous agents using nearest neighbor rules
Jadbabaie, A., Lin, J., & Morse, A. S. (2003) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2003.812781 · Cited by 8,339
Godsil, C., & Royle, G. (2001) · Graduate Texts in Mathematics · doi:10.1007/978-1-4613-0163-9 · Cited by 8,154
Consensus seeking in multiagent systems under dynamically changing interaction topologies
Ren, W., & Beard, R. W. (2005) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.846556 · Cited by 6,569
Stochastic differential equations and applications
Mao, X. (2008) · Woodhead Publishing Limited eBooks · doi:10.1533/9780857099402 · Cited by 4,589
Information Flow and Cooperative Control of Vehicle Formations
Fax, J. A., & Murray, R. M. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.834433 · Cited by 4,579
Tracking control for multi-agent consensus with an active leader and variable topology
Hong, Y., Hu, J., & Gao, L. (2006) · Automatica · doi:10.1016/j.automatica.2006.02.013 · Cited by 2,055
Self-citationStochastic Differential Equations and Applications
(1976) · Elsevier eBooks · doi:10.1016/c2013-0-07333-1 · Cited by 1,375
A vision-based formation control framework
Das, A. K., Fierro, R., Kumar, V., Ostrowski, J. P., Spletzer, J., & Taylor, C. J. (2002) · IEEE Transactions on Robotics and Automation · doi:10.1109/tra.2002.803463 · Cited by 1,146
Probability Theory: Independence, Interchangeability, Martingales
Lund, R. B., Chow, Y. S., & Teicher, H. (1998) · Journal of the American Statistical Association · doi:10.2307/2670078 · Cited by 1,066
Necessary and sufficient graphical conditions for formation control of unicycles
(2005) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.841121 · Cited by 1,041
Leader-following coordination of multi-agent systems with coupling time delays
Hu, J., & Hong, Y. (2007) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2006.08.015 · Cited by 945
Self-citationStochastic Approximation and Recursive Estimation
Nevel′son, M., & Has′minskiĭ, R. (1976) · Translations of Mathematical Monographs · doi:10.1090/mmono/047 · Cited by 525
Li, T., & Zhang, J.-F. (2009) · Automatica · doi:10.1016/j.automatica.2009.04.017 · Cited by 453
Huang, M., & Manton, J. H. (2009) · SIAM Journal on Control and Optimization · doi:10.1137/06067359x · Cited by 401
Navigation strategies for multiple autonomous mobile robots moving in formation
Wang, P. K. C. (1991) · Journal of Robotic Systems · doi:10.1002/rob.4620080204 · Cited by 398
Shi, G., & Hong, Y. (2009) · Automatica · doi:10.1016/j.automatica.2008.12.015 · Cited by 223
UAV Formation Control: Theory and Application
Anderson, B. D. O., Fidan, B., Yu, C., & Walle, D. (2007) · Lecture Notes in Control and Information Sciences · doi:10.1007/978-1-84800-155-8_2 · Cited by 194
Lin, P., Jia, Y., Du, J., et al. (2008) · Asian Journal of Control · doi:10.1002/asjc.24 · Cited by 58
Cited by
Distributed Tracking Control for Linear Multiagent Systems With a Leader of Bounded Unknown Input
Li, Z., Liu, X., Ren, W., & Xie, L. (2013) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2012.2208295 · Cited by 552
Distributed consensus tracking for multi‐agent systems under two types of attacks
Feng, Z., Hu, G., & Wen, G. (2016) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.3342 · Cited by 258
Metadata
- Authors
- Hu, J., & Feng, G.
- Venue
- Automatica
- Publisher
- Elsevier BV
- Published
- 2010-08
- Volume
- 46
- Issue
- 8
- Pages
- 1382-1387
- ISSN
- 0005-1098 (ISSN-L)
- OpenAlex
- W1981685742
- Cited by
- 488
- References
- 18
- FWCI
- 31.14
- Type
- journal article
- Language
- en
- Open access
- green
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