Hierarchical Safe Control of Multiagent Systems With Malicious Attacks Using Adaptive Fault-Tolerant Consensus Control
This paper proposed a hierarchical control framework that integrates an upper observer layer and a lower tracking layer. Based on higher-order sliding mode observer in the upper layer, a distributed high-order sliding mode observer (SMO) is used to approximate the leader's state, which can also identify some unknown and uncertain terms caused by malicious attacks. For the lower tracking layer, an adaptive fixed-time prescribed performance fault-tolerant control (FTPPFTC) method is leveraged to address the problem of malicious attacks and help the following agent achieve the stable tracking performance. By using the developed method, it is proved that the tracking errors of the multi-agent systems can converge into a small neighborhood within the fixed time. Finally, the numerical examples and comparative results illustrate the effectiveness of the proposed control method.
Authors
- Haibin Duan (ORCID: https://orcid.org/0000-0002-4926-3202)
- Yuezu Lv (ORCID: https://orcid.org/0000-0002-7757-9028)
- Junkang Ni (ORCID: https://orcid.org/0000-0001-7551-4696)
- Pu Zhang (ORCID: https://orcid.org/0000-0003-1425-8443)
- Xin Gong (ORCID: https://orcid.org/0000-0001-6883-5088)
- Yulong Huang (ORCID: https://orcid.org/0000-0001-9303-9083)
- Kun Zhang (ORCID: https://orcid.org/0009-0008-9929-7700)
Institutions
- Beijing Institute of Technology (CN)
- Harbin Engineering University (CN)
- Northwestern Polytechnical University (CN)
- Xi'an University of Technology (CN)
- Southeast University (CN)
- Beihang University (CN)
Publication Details
- Journal
- IEEE Transactions on Aerospace and Electronic Systems
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1109/taes.2025.3559038
- Citations
- 1
- Primary Topic
- Mobile Agent-Based Network Management
- Type
- article
- Field-Weighted Citation Impact
- 1.49
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Beijing Nova Program