反推
控制理论(社会学)
欠驱动
计算机科学
国家(计算机科学)
控制(管理)
控制工程
工程类
自适应控制
人工智能
算法
作者
Jialu Du,Jian Li,Frank L. Lewis
出处
期刊:IEEE Transactions on Industrial Informatics
[Institute of Electrical and Electronics Engineers]
日期:2023-05-01
卷期号:19 (5): 6963-6971
被引量:15
标识
DOI:10.1109/tii.2022.3194632
摘要
Communication delays are a crucial issue in autonomous underwater vehicle (AUV) formation control. To solve this issue, this article for the first time develops an active communication delay compensation (ACDC) mechanism with an innovatively developed data-driven state predictor (DDSP) of AUVs. The DDSP of each AUV can online estimate the current motion states of its neighbors solely depending on its received delayed motion state information of its neighbors. Incorporating the ACDC, prescribed performance control method, and neural networks into the backstepping approach, this article proposes a distributed 3-D time-varying formation prescribed performance control strategy, where a novel auxiliary dynamic system is created to alleviate the adverse effect of input saturations. The proposed formation control strategy ensures AUVs to maintain the desired 3-D time-varying formation pattern, while achieving the asymptotic stability with respect to formation errors and satisfying the performance constraints simultaneously. Simulations are performed to validate our proposed formation control strategy.
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