- Title
- Data-Driven Practical Cooperative Output Regulation Under Actuator Faults and DoS Attacks
- Creator
- Deng, Chao; Gao, Weinan; Wen, Changyun; Chen, Zhiyong; Wang, Wei
- Relation
- IEEE Transactions on Cybernetics Vol. 53, Issue 11, p. 7417-7428
- Publisher Link
- http://dx.doi.org/10.1109/TCYB.2023.3263480
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- journal article
- Date
- 2023
- Description
- This article addresses the resilient practical cooperative output regulation problem (RPCORP) for multiagent systems subjected to both denial-of-service (DoS) attacks and actuator faults. Fundamentally different from the existing solutions to RPCORPs, the system parameters considered in this article are unknown to each agent, and a novel data-driven control approach is introduced to handle such an issue. The solution starts with developing resilient distributed observers for each follower in the presence of DoS attacks. Then, a resilient communication mechanism and a time-varying sampling period are introduced to, respectively, ensure the neighbor state is available as soon as attacks disappear and to avoid targeted attacks launched by intelligent attackers. Furthermore, a model-based fault-tolerant and resilient controller is designed based on the Lyapunov approach and the output regulation theory. In order to remove the reliance on system parameters, we leverage a new data-driven algorithm to learn controller parameters via the collected data. Rigorous analysis shows that the closed-loop system can resiliently achieve practical cooperative output regulation. Finally, a simulation example is given to illustrate the effectiveness of the achieved results.
- Subject
- actuator faults; multiagent systems (MASs); practical cooperative output regulation; fault tolerance
- Identifier
- http://hdl.handle.net/1959.13/1493307
- Identifier
- uon:53535
- Identifier
- ISSN:2168-2267
- Language
- eng
- Reviewed
- Hits: 985
- Visitors: 984
- Downloads: 0
| Thumbnail | File | Description | Size | Format |
|---|