Reinforcement learning-based predefined-time secure control for fractional-order nonlinear systems with sensor and actuator attacks.
- DOI
- 10.1016/j.neunet.2026.109697
- Published
- 2026-09-29
- Container
- Neural Netw
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109697,
title = {Reinforcement learning-based predefined-time secure control for fractional-order nonlinear systems with sensor and actuator attacks.},
author = {Liang C and Wang F and Wang Z and Lai G.},
year = {2027},
journal = {Neural Netw},
doi = {10.1016/j.neunet.2026.109697},
url = {https://doi.org/10.1016/j.neunet.2026.109697}
}RIS
TY - JOUR TI - Reinforcement learning-based predefined-time secure control for fractional-order nonlinear systems with sensor and actuator attacks. AU - Liang C AU - Wang F AU - Wang Z AU - Lai G. PY - 2027 JO - Neural Netw DO - 10.1016/j.neunet.2026.109697 UR - https://doi.org/10.1016/j.neunet.2026.109697 ER -
APA
C, L., F, W., Z, W., & G., L. (2027). Reinforcement learning-based predefined-time secure control for fractional-order nonlinear systems with sensor and actuator attacks.. Neural Netw. https://doi.org/10.1016/j.neunet.2026.109697
Source records
- europe-pmc · retrieved 2026-11-10T14:01:40.345Z