Disturbance Observer-Based Fuzzy Adaptive Containment Control of Nonlinear Multi-agent Systems with Input Quantization-Reference-Cited by-同舟云学术

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Disturbance Observer-Based Fuzzy Adaptive Containment Control of Nonlinear Multi-agent Systems with Input Quantization

Published:2021-08-28 Issue:1 Volume:24 Page:574-586
ISSN:1562-2479
Container-title:International Journal of Fuzzy Systems
language:en
Short-container-title:Int. J. Fuzzy Syst.

Author:

Li Zan,Pan Yingnan,Ma Jingmin

Funder

National Natural Science Foundation of China

Doctoral Start-up Foundation of Liaoning Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s40815-021-01164-0.pdf

Reference41 articles.

1. Wang, F., Zhang, Y., Zhang, L., Zhang, J., Huang, Y.: Finite-time consensus of Stochastic nonlinear multi-agent systems. Int. J. Fuzzy Syst. 22(1), 77–88 (2020)

2. Lin, G., Li, H., Ma, H., Yao, D., Lu, R.: Human-in-the-loop consensus control for nonlinear multi-agent systems with actuator faults. IEEE/CAA J. Automat. Sin. (2020). https://doi.org/10.1109/JAS.2020.1003596

3. Cui, Y., Liu, X., Deng, X., Wang, Q.: Observer-based adaptive fuzzy formation control of nonlinear multi-agent systems with nonstrict-feedback form. International Journal of Fuzzy Systems. 23(3), 680–691 (2021)

4. Fan, Y., Hao, M., Li, Z.: Distributed fuzzy adaptive consensus control for a class of heterogeneous multi-agent systems with nonidentical dimensions. International Journal of Fuzzy Systems. 23(1), 128–138 (2021)

5. Li, H., Wu, Y., Chen, M.: Adaptive fault-tolerant tracking control for discrete-time multi-agent systems via reinforcement learning algorithm. IEEE Transactions on Cybernetics. 51(3), 1163–1174 (2021)

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