The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Fuzzy Observed-Based Adaptive Consensus Tracking Control for Second-Order Multiagent Systems With Heterogeneous Nonlinear Dynamics
Abstract
In this paper, the consensus tracking control problem of second-order multiagent systems with unknown nonlinear dynamics, immeasurable states, and disturbances is investigated. The nonlinear dynamics in multiagent systems do not satisfy the matched condition. In this paper, fuzzy logic system is introduced to approximate the unknown nonlinear dynamics, and adaptive high-gain observer is designed to estimate the unmeasured states. Based on backstepping approach and Lyapunov theory, a new adaptive fuzzy distributed controller is proposed for each agent only using the information of itself and its neighbors. Then the consensus tracking is achieved under the designed distributed controller. Moreover, it is proved that all the signals in the multiagent systems are semiglobally uniformly ultimately bounded, and the consensus tracking error converges to a small neighborhood of the origin that can be designed as small as possible. Finally, the simulation result illustrates the effectiveness of the designed controller.
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Cites
Slotine, J.-J. E., & Li, W. (1991) · CERN Document Server (European Organization for Nuclear Research) · Cited by 18,975
Consensus Problems in Networks of Agents With Switching Topology and Time-Delays
Olfati-Saber, R., & Murray, R. M. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.834113 · Cited by 12,788 · cited 2×
“For example, the distributed consensus controller in [2] cannot steer the multiagent systems to achieve the average consensus, when there are communication noises which is uncertain from the external environment [11].”
BackgroundConsensus and Cooperation in Networked Multi-Agent Systems
Olfati-Saber, R., Fax, J. A., & Murray, R. M. (2007) · Proceedings of the IEEE · doi:10.1109/jproc.2006.887293 · Cited by 10,522
Spong, M. W., Hutchinson, S., & Vidyasagar, M. (2006) · Cited by 3,313
Adaptive Fuzzy Systems and Control: Design and Stability Analysis
Wang, L. (1994) · Medical Entomology and Zoology · Cited by 2,736
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
On Consensus Algorithms for Double-Integrator Dynamics
Ren, W. (2008) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2008.924961 · Cited by 1,413
Second-Order Consensus for Multiagent Systems With Directed Topologies and Nonlinear Dynamics
Yu, W., Chen, G., Cao, M., & Kurths, J. (2010) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2009.2031624 · Cited by 1,120
Li, Z., Ren, W., Liu, X., & Fu, M. (2013) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2012.2235715 · Cited by 841
Robust Finite-Time Consensus Tracking Algorithm for Multirobot Systems
Khoo, S., Xie, L., & Man, Z. (2009) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2009.2014057 · Cited by 835
Cited by
Tong, S., Sun, K., & Sui, S. (2018) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2017.2686373 · Cited by 551
An Improved Predefined-Time Adaptive Neural Control Approach for Nonlinear Multiagent Systems
Pan, Y., Ji, W., Lam, H.-K., & Cao, L. (2024) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2023.3324397 · Cited by 294
Metadata
- Authors
- Chen, C. L. P., Ren, C.-E., & Du, T.
- Venue
- IEEE Transactions on Fuzzy Systems
- Published
- 2016-08-01
- Volume
- 24
- Issue
- 4
- Pages
- 906-915
- ISSN
- 1063-6706 (ISSN-L)
- 1941-0034
- OpenAlex
- W2501602109
- Cited by
- 305
- References
- 32
- FWCI
- 33.77
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, C. L. P., Ren, C.-E., & Du, T. (2016). Fuzzy Observed-Based Adaptive Consensus Tracking Control for Second-Order Multiagent Systems With Heterogeneous Nonlinear Dynamics. IEEE Transactions on Fuzzy Systems. https://doi.org/10.1109/tfuzz.2015.2486817
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