基于分布式模型预测控制的欠驱动 AUV 编队控制

Translated title of the contribution: Formation Control of an Underactuated Autonomous Undersea Vehicle Based on Distributed Model Predictive Control

Yuanbo Guo, Qi Li, Boxu Min, Jian Gao, Yimin Chen

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Compared with centralized model predictive control, distributed model predictive control(DMPC) is characterized by lower computational complexity and stronger fault tolerance and robustness, and it is widely used in multiagent formation control. In this study, an underactuated autonomous undersea vehicle(AUV) formation control method based on DMPC is proposed. Based on local neighbor information, the cost function and constraints of predictive control are constructed for each AUV controller, and the optimal control input in a certain time domain is solved by using an optimization algorithm. To solve the obstacle avoidance problem and communication delay problem that may exist in the formation system, obstacle avoidance methods based on distance and relative line of sight, as well as a waiting mechanism for problem solving after receiving all neighbor information, are designed. The simulation results demonstrate that, by using the method proposed in this study, the multi-AUV formation can remain stable under the conditions of obstacles and communication delays.

Translated title of the contributionFormation Control of an Underactuated Autonomous Undersea Vehicle Based on Distributed Model Predictive Control
Original languageChinese (Traditional)
Pages (from-to)405-412
Number of pages8
JournalJournal of Unmanned Undersea Systems
Volume31
Issue number3
DOIs
StatePublished - Jun 2023

Fingerprint

Dive into the research topics of 'Formation Control of an Underactuated Autonomous Undersea Vehicle Based on Distributed Model Predictive Control'. Together they form a unique fingerprint.

Cite this