The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks
Abstract
A robust adaptive control approach is proposed to solve the consensus problem of multiagent systems. Compared with the previous work, the agent's dynamics includes the uncertainties and external disturbances, which is more practical in real-world applications. Due to the approximation capability of neural networks, the uncertain dynamics is compensated by the adaptive neural network scheme. The effects of the approximation error and external disturbances are counteracted by employing the robustness signal. The proposed algorithm is decentralized because the controller for each agent only utilizes the information of its neighbor agents. By the theoretical analysis, it is proved that the consensus error can be reduced as small as desired. The proposed method is then extended to two cases: Agents form a prescribed formation, and agents have the higher order dynamics. Finally, simulation examples are given to demonstrate the satisfactory performance of the proposed method.
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Cites
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
Consensus 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 · cited 4×
“Remark 1: It is noted that most of existing work only considers the agents with deterministic first- or second-order integrator dynamics [6]–[19].”
BackgroundInfluentialCoordination of groups of mobile autonomous agents using nearest neighbor rules
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Identification and control of dynamical systems using neural networks
Narendra, K. S., & Parthasarathy, K. (1990) · IEEE Transactions on Neural Networks · doi:10.1109/72.80202 · Cited by 8,014
Novel Type of Phase Transition in a System of Self-Driven Particles
Vicsek, T., Czirók, A., Ben-Jacob, E., Cohen, I., & Shochet, O. (1995) · Physical Review Letters · doi:10.1103/physrevlett.75.1226 · Cited by 7,380
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
Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory
Olfati-Saber, R. (2006) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.864190 · Cited by 5,037
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
Fast linear iterations for distributed averaging
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Metadata
- Authors
- Hou, Z.-G., Cheng, L., & Tan, M.
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
- Published
- 2009-06
- Volume
- 39
- Issue
- 3
- Pages
- 636-647
- ISSN
- 1083-4419 (ISSN-L)
- OpenAlex
- W2120638718
- Cited by
- 668
- References
- 31
- FWCI
- 23.52
- Type
- journal article
- Language
- en
- Open access
- closed
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- Hou, Z.-G., Cheng, L., & Tan, M. (2009). Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). https://doi.org/10.1109/tsmcb.2008.2007810
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