The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Event-Triggered Robust Fuzzy Adaptive Finite-Time Control of Nonlinear Systems With Prescribed Performance
Abstract
In this article, an event-triggered robust fuzzy adaptive prescribed performance finite-time control strategy is presented for a class of strict-feedback nonlinear systems with external disturbances. The relative-threshold-based event-triggered signal is introduced to reduce communication burden, and the dynamic surface control technique is applied to address the computational complexity problem. A disturbance observer is designed to estimate the compounded disturbances, which are composed of external disturbances and fuzzy approximation errors. The proposed control strategy can guarantee that the closed-loop system is semiglobally practically finite-time stable, and the tracking error converges to a small residual set by incorporating the prescribed performance bound in finite-time. Finally, simulation results are provided to verify the effectiveness of the proposed robust fuzzy control strategy.
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Cites
1 retracted
Chadli, M., & Karimi, H. R. (2013) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2012.2197215 · Cited by 388
Self-citationRetractedEvent-Triggered Real-Time Scheduling of Stabilizing Control Tasks
Tabuada, P. (2007) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2007.904277 · Cited by 4,702
Stable adaptive fuzzy control of nonlinear systems
Wang, L.-X. (1993) · IEEE Transactions on Fuzzy Systems · doi:10.1109/91.227383 · Cited by 1,617
Adaptive finite-time tracking control of full state constrained nonlinear systems with dead-zone
Li, H., Zhao, S., He, W., & Lu, R. (2019) · Automatica · doi:10.1016/j.automatica.2018.10.030 · Cited by 555
Li, Y., Li, K., & Tong, S. (2019) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2018.2868898 · Cited by 483
Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems
Wang, F., Chen, B., Lin, C., Zhang, J., & Meng, X. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2715980 · Cited by 473
Zhang, T., Xia, M., & Yi, Y. (2017) · Automatica · doi:10.1016/j.automatica.2017.03.033 · Cited by 468
Adaptive compensation for actuator failures with event-triggered input
Xing, L., Wen, C., Liu, Z., Su, H., & Cai, J. (2017) · Automatica · doi:10.1016/j.automatica.2017.07.061 · Cited by 393
Adaptive Neural Network Tracking Control for Robotic Manipulators With Dead Zone
Zhou, Q. F., Zhao, S., Li, H., Lu, R., & Wu, C. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2869375 · Cited by 378
Iterative Learning Control for a Flapping Wing Micro Aerial Vehicle Under Distributed Disturbances
He, W., Meng, T., He, X., & Sun, C. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2808321 · Cited by 329
Cited by
Event-Triggered Fuzzy Adaptive Fixed-Time Tracking Control for Nonlinear Systems
Hu, X., Li, Y.-X., & Hou, Z. (2022) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.3035779 · Cited by 101
Kharrat, M., & Alhazmi, H. (2024) · AIMS Mathematics · doi:10.3934/math.2024668 · Cited by 11
Input Delay Estimation for Input-Affine Dynamical Systems Based on Taylor Expansion
Zhang, Y., Li, S., & Liao, L. (2021) · IEEE Transactions on Circuits and Systems II: Express Briefs · doi:10.1109/tcsii.2020.3025136 · Cited by 10
Kharrat, M. (2026) · European Journal of Control · doi:10.1016/j.ejcon.2025.101426 · Cited by 1
Metadata
- Authors
- Sun, K., Qiu, J., Karimi, H. R., & Fu, Y.
- Venue
- IEEE Transactions on Fuzzy Systems
- Published
- 2021-06
- Volume
- 29
- Issue
- 6
- Pages
- 1460-1471
- ISSN
- 1063-6706 (ISSN-L)
- 1941-0034
- OpenAlex
- W3009594751
- Cited by
- 334
- References
- 23
- FWCI
- 27.57
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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