Multiple Autonomous Underwater Vehicle Formation Obstacle Avoidance Control Using Event-Triggered Model Predictive Control Article Swipe

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Linling Wang , Xiaoyan Xu , Bing Han , Hua-Peng Zhang ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.3390/jmse11102016

In this paper, multiple autonomous underwater vehicle (multi-AUV) formation control with obstacle avoidance ability in 3D complex underwater environments based on an event-triggered model predictive control (EMPC) is proposed. Firstly, multi-AUV motion model systems are developed. The navigation reference trajectory of the follower AUVs can be obtained using a multi-AUV relative motion model. Secondly, in order to overcome the speed jump and obstacle avoidance problem in multi-AUV systems, compatibility constraints are presented in MPC that limit the uncertainty deviation of each AUV. The event-triggered mechanism (ET) is designed to decrease the computational load, which is based on the error between the optimal predicted and current state of the AUV. Finally, the effectiveness and superiority of the proposed algorithm are confirmed via simulation and compared with those of other algorithms.

Related Topics

Underwater Acoustics

The Obstacle Is The Way

Artificial Intelligence

Concepts

Obstacle avoidance Control theory (sociology) Model predictive control Underwater Obstacle Jump Computer science Trajectory Collision avoidance Control engineering Control (management) Engineering Mobile robot Artificial intelligence Collision Robot Geology Quantum mechanics Physics Computer security Political science Oceanography Astronomy Law

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Type: article
Language: en
Landing Page: https://doi.org/10.3390/jmse11102016
PDF: https://www.mdpi.com/2077-1312/11/10/2016/pdf?version=1697724770
OA Status: gold
Cited By: 12
References: 47
Related Works: 10
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DOI: https://doi.org/10.3390/jmse11102016

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Title: Multiple Autonomous Underwater Vehicle Formation Obstacle Avoidance Control Using Event-Triggered Model Predictive Control

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Language: en

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Publication year: 2023

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Publication date: 2023-10-19

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Authors: Linling Wang, Xiaoyan Xu, Bing Han, Hua-Peng Zhang

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Landing page: https://doi.org/10.3390/jmse11102016

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Concepts: Obstacle avoidance, Control theory (sociology), Model predictive control, Underwater, Obstacle, Jump, Computer science, Trajectory, Collision avoidance, Control engineering, Control (management), Engineering, Mobile robot, Artificial intelligence, Collision, Robot, Geology, Quantum mechanics, Physics, Computer security, Political science, Oceanography, Astronomy, Law

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Cited by: 12

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Citations by year (recent): 2025: 4, 2024: 8

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