Formation Tracking and Transformation of AUVs Based on the Improved Particle Swarm Optimization Algorithm

被引：0
|
作者：
Li, Yue [1 ]
Zhu, Daqi [1 ]
机构：
[1] Shanghai Maritime Univ, Shanghai Engn Res Ctr Intelligent Maritime Search, Haigang Ave 1550, Shanghai 201306, Peoples R China
来源：
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020) | 2020年
基金：
中国国家自然科学基金;
关键词：
Improved PSO; Virtual Formation; Formation Tracking and Formation Transformation; SPACECRAFT;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A novel algorithm is proposed to solve the problem of formation tracking and formation transformation. It is inspired from the biological principle of particle swarm optimization algorithm (PSO). All the AUVs are taken as particles, and key points of virtual formation are taken as one of the navigation targets respectively. When all of the AUVs arrive the desired corresponding key points, the aim of formation tracking is achieved. On the other hand, the formation transformation can be achieved by this algorithm, too. Some simulations are done to prove the effectiveness of the proposed method.
引用
收藏
页码：3159 / 3162
页数：4
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