A Consensus-Based Model Predictive Control with Optimized Line-of-Sight Guidance for Formation Trajectory Tracking of Autonomous Underwater Vehicles-Reference-Cited by-同舟云学术

A Consensus-Based Model Predictive Control with Optimized Line-of-Sight Guidance for Formation Trajectory Tracking of Autonomous Underwater Vehicles

Published:2022-08-26 Issue:1 Volume:106 Page:
ISSN:0921-0296
Container-title:Journal of Intelligent & Robotic Systems
language:en
Short-container-title:J Intell Robot Syst

Author:

Qian Zhonglan,Lyu Weichao,Dai Yizhan,Xu Jing

Funder

National Natural Science Foundation of China

Strategic Priority Research Program of the Chinese Academy of Sciences

Zhoushan-Zhejiang University Joint Research Project

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Industrial and Manufacturing Engineering,Mechanical Engineering,Control and Systems Engineering,Software

Link

https://link.springer.com/content/pdf/10.1007/s10846-022-01710-4.pdf

Reference39 articles.

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2. Shen, C., Shi, Y., Buckham, B.: Trajectory tracking control of an autonomous underwater vehicle using Lyapunov-based model predictive control. IEEE Trans. Ind. Electron. 65, 5796–5805 (2018). https://doi.org/10.1109/TIE.2017.2779442

3. Wang, J., Wang, C., Wei, Y., Zhang, C.: Neuroadaptive sliding mode formation control of autonomous underwater vehicles with uncertain dynamics. IEEE Syst. J. 14, 3325–3333 (2020). https://doi.org/10.1109/JSYST.2019.2938315

4. Shojaei, K.: Neural network formation control of underactuated autonomous underwater vehicles with saturating actuators. Neurocomputing. 194, 372–384 (2016). https://doi.org/10.1016/j.neucom.2016.02.041

5. Sun, Z., Zhang, G., Lu, Y., Zhang, W.: Leader-follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation. ISA Trans. 72, 15–24 (2018). https://doi.org/10.1016/j.isatra.2017.11.008

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