Cooperative Path Following Control of Unmanned Surface Vehicles Using Model Predictive Control

被引:0
作者
Ahmed, Syed Hamza [1 ]
Zhao, Minzhong [1 ]
Li, Huiping [1 ]
机构
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian, Peoples R China
来源
2024 IEEE 7TH INTERNATIONAL CONFERENCE ON INDUSTRIAL CYBER-PHYSICAL SYSTEMS, ICPS 2024 | 2024年
基金
中国国家自然科学基金;
关键词
Unmanned surface vehicle (USV); Model Predictive Control (MPC); Cooperative Path Following (CPF); Collision Avoidance (CA); COLLISION-AVOIDANCE; IDENTIFICATION;
D O I
10.1109/ICPS59941.2024.10640036
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper addresses the challenges in Cooperative Path Following (CPF) for Unmanned Surface Vehicles (USVs) in formation control, a subject with significant applications in ocean monitoring and marine habitat mapping. We propose a novel approach integrating Model Predictive Control (MPC) with a vehicle's speed coordination mechanism. This method allows for effective management of constraints on vehicle inputs and facilitates the maintenance of vehicle formation while also avoiding obstacles and collision with each other. Our strategy decomposes the CPF problem into two sub-problems: path following of each vehicle with constrained inputs and coordination of a multi-agent system (MAS). The path following problem is managed using a non-linear MPC-based scheme, while the coordination challenge is addressed through a novel distributed control law using the path parameters of neighboring USVs. The approach has been rigorously tested across various scenarios, demonstrating its robustness and ability to consistently guide the MAS towards the desired formation, regardless of trajectories and obstacles encountered.
引用
收藏
页数:6
相关论文
共 22 条
[1]   Nonlinear Model Predictive Control for trajectory tracking and collision avoidance of underactuated vessels with disturbances [J].
Abdelaal, Mohamed ;
Fraenzle, Martin ;
Hahn, Axel .
OCEAN ENGINEERING, 2018, 160 :168-180
[2]   Marine Vehicles with Streamers for Geotechnical Surveys: Modeling, Positioning, and Control [J].
Abreu, Pedro ;
Morishita, Helio ;
Pascoal, Antonio ;
Ribeiro, Jorge ;
Silva, Henrique .
IFAC PAPERSONLINE, 2016, 49 (23) :458-464
[3]   A distributed Model Predictive Control scheme for coordinated output regulation [J].
Alessandretti, Andrea ;
Pedro Aguiar, A. .
IFAC PAPERSONLINE, 2017, 50 (01) :8692-8697
[4]   CasADi: a software framework for nonlinear optimization and optimal control [J].
Andersson, Joel A. E. ;
Gillis, Joris ;
Horn, Greg ;
Rawlings, James B. ;
Diehl, Moritz .
MATHEMATICAL PROGRAMMING COMPUTATION, 2019, 11 (01) :1-36
[5]   Distributed receding horizon control for multi-vehicle formation stabilization [J].
Dunbar, WB ;
Murray, RM .
AUTOMATICA, 2006, 42 (04) :549-558
[6]  
Fossen T. I., 2011, Handbook of Marine Craft Hydrodynamics and Motion Control, DOI DOI 10.1002/9781119994138
[7]   Cooperative path following of constrained autonomous vehicles with model predictive control and event-triggered communications [J].
Hung, Nguyen T. ;
Pascoal, Antonio M. ;
Johansen, Tor A. .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2020, 30 (07) :2644-2670
[8]   Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment [J].
Johansen, Tor Arne ;
Perez, Tristan ;
Cristofaro, Andrea .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (12) :3407-3422
[9]   Review of Collision Avoidance and Path Planning Methods for Ships Utilizing Radar Remote Sensing [J].
Lazarowska, Agnieszka .
REMOTE SENSING, 2021, 13 (16)
[10]   Cooperative Path Following Ring-Networked Under-Actuated Autonomous Surface Vehicles: Algorithms and Experimental Results [J].
Liu, Lu ;
Wang, Dan ;
Peng, Zhouhua ;
Li, Tieshan ;
Chen, C. L. Philip .
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 50 (04) :1519-1529