Distributed event-driven adaptive three-dimensional formation tracking of networked autonomous underwater vehicles with unknown nonlinearities
- Authors
- Kim, J.H.; Yoo, S.J.
- Issue Date
- 1-Aug-2021
- Publisher
- Elsevier Ltd
- Keywords
- Autonomous underwater vehicles (AUVs); Distributed formation; Event-driven tracking; Neural networks; Three-dimensional space
- Citation
- Ocean Engineering, v.233
- Journal Title
- Ocean Engineering
- Volume
- 233
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/47791
- DOI
- 10.1016/j.oceaneng.2021.109069
- ISSN
- 0029-8018
1873-5258
- Abstract
- This paper presents a distributed event-driven adaptive formation control strategy for networked uncertain nonlinear autonomous underwater vehicles (AUVs) in three-dimensional space. It is assumed that the leader information is only transmitted to a subset of AUV followers under a directed graph and the nonlinearities of the AUV dynamics are unknown. A distributed error transformation method is presented to address the distributed formation tracking problem of AUV followers in three-dimensional space. Then, a distributed event-driven adaptive control method using neural networks and stabilizing auxiliary signals is developed to ensure the stability of the event-driven closed-loop system and accomplish three-dimensional formation tracking in the Lyapunov stability sense. Additionally, it is shown that Zeno behavior does not occur in the resulting event-triggering strategy. A simulation demonstrates the effectiveness of the proposed theoretical methodology. © 2021 Elsevier Ltd
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