Formation Control and Obstacle Avoidance Algorithm of a Multi-USV System Based on Virtual Structure and Artificial Potential Field

被引:5
作者
Ghaderia, F. [1 ]
Toloei, A. [1 ]
Ghasemi, R. [2 ]
机构
[1] Shahid Beheshti Univ, Dept Aerosp Engn, Tehran, Iran
[2] Univ Qom, Dept Engn, Qom, Iran
来源
INTERNATIONAL JOURNAL OF ENGINEERING | 2024年 / 37卷 / 01期
关键词
Formation Control; Model Predictive Control; Obstacle Avoidance; Improved Artificial Potential Field; QUADROTOR FORMATION; FORMATION TRACKING;
D O I
10.5829/ije.2024.37.01a.11
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The purpose of this article is to control the formation and pass static and dynamic obstacles for the quadrotor group, maintain the continuity and flight formation after crossing the obstacles, and track the moving target. Model Predictive Control (MPC) method has been used to control the status and position of quadrotors and formation control. Flight formation is based on the leader-follower method, in which the followers maintain a certain angle and distance from the leader using the formation controller. The improved Artificial Potential Field (APF) method has been used to pass obstacles, the main advantage of which compared to the traditional APF is to increase the range of the repulsive force of the obstacles, which solves the problem of getting stuck in the local minimum and not passing through the environments full of obstacles. The results of the design of the attitude and position controller showed that the quadrotors were stabilized and converged in less than 3 seconds. Formation control simulations in the spiral path showed that the followers, follow the leader. The results of the quadrotors passing through the obstacles were presented in four missions. In the first mission, 4 quadrotors crossed static obstacles. In the second mission, 4 quadrotors crossed dynamic obstacles. In these two missions, the quadrotors maintained a square flight formation after crossing the obstacles. In the third mission, the number of quadrotors increased to 6. The leader tracked the moving target and the quadrotors crossing the static obstacles. In the last mission, the quadrotors passed through the dynamic obstacles and the leader tracked the static target. In these missions, the quadrotors maintain the hexagonal formation after crossing the obstacles. The results simulations showed that the quadrotors crossed the fixed and moving obstacles and after crossing, they preserved the flight formation.
引用
收藏
页码:115 / 126
页数:12
相关论文
共 36 条
[1]  
Abdellatif Rawan A., 2020, 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES), P497, DOI 10.1109/NILES50944.2020.9257973
[2]   Enhanced multi-agent systems formation and obstacle avoidance (EMAFOA) control algorithm [J].
Aljassani, Alaa M. H. ;
Ghani, Suadad Noori ;
Al-Hajjar, Ali M. H. .
RESULTS IN ENGINEERING, 2023, 18
[3]  
Andaluz GM., 2022, EMERGING SCI J, V6, P429, DOI [10.28991/ESJ-2022-06-03-01, DOI 10.28991/ESJ-2022-06-03-01]
[4]  
Arofiati F, 2021, Robot, DOI [10.28991/esj-2021-SPER-13, DOI 10.28991/ESJ-2021-SPER-13]
[5]   An improved ant colony optimization algorithm based on particle swarm optimization algorithm for path planning of autonomous underwater vehicle [J].
Che, Gaofeng ;
Liu, Lijun ;
Yu, Zhen .
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2020, 11 (08) :3349-3354
[6]   Decentralized MPC for UAVs Formation Deployment and Reconfiguration with Multiple Outgoing Agents [J].
Chevet, Thomas ;
Vlad, Cristina ;
Maniu, Cristina Stoica ;
Zhang, Youmin .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2020, 97 (01) :155-170
[7]   Cooperative payload transportation with real-time formation control of multi-quadrotors in the presence of uncertainty [J].
Doakhan M. ;
Kabganian M. ;
Azimi A. .
Journal of the Franklin Institute, 2023, 360 (02) :1284-1307
[8]   Time-Varying Formation Tracking for Second-Order Multi-Agent Systems Subjected to Switching Topologies With Application to Quadrotor Formation Flying [J].
Dong, Xiwang ;
Zhou, Yan ;
Ren, Zhang ;
Zhong, Yisheng .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2017, 64 (06) :5014-5024
[9]   Distributed Formation Control of Multiple Quadrotor Aircraft Based on Nonsmooth Consensus Algorithms [J].
Du, Haibo ;
Zhu, Wenwu ;
Wen, Guanghui ;
Duan, Zhisheng ;
Lu, Jinhu .
IEEE TRANSACTIONS ON CYBERNETICS, 2019, 49 (01) :342-353
[10]   Finite-time formation control for a group of quadrotor aircraft [J].
Du, Haibo ;
Zhu, Wenwu ;
Wen, Guanghui ;
Wu, Di .
AEROSPACE SCIENCE AND TECHNOLOGY, 2017, 69 :609-616