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
相关论文
共 50 条
  • [41] Chemical Process Optimization based on Improved Particle Swarm Algorithm
    Wu Rui-hong
    2016 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2016), 2016, : 82 - 85
  • [42] Improved Particle Swarm Optimization Algorithm Based on Social Psychology
    Liu, Wenyuan
    Sui, Peipei
    Wang, Changwu
    2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL I, PROCEEDINGS, 2009, : 145 - 148
  • [43] Improved Particle Swarm Optimization Algorithm Based on Multiple Strategies
    Kang Y.-S.
    Zang S.-L.
    Dongbei Daxue Xuebao/Journal of Northeastern University, 2023, 44 (08): : 1089 - 1097
  • [44] Improved salp swarm algorithm based on particle swarm optimization for feature selection
    Ibrahim, Rehab Ali
    Ewees, Ahmed A.
    Oliva, Diego
    Abd Elaziz, Mohamed
    Lu, Songfeng
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2019, 10 (08) : 3155 - 3169
  • [45] Improved salp swarm algorithm based on particle swarm optimization for feature selection
    Rehab Ali Ibrahim
    Ahmed A. Ewees
    Diego Oliva
    Mohamed Abd Elaziz
    Songfeng Lu
    Journal of Ambient Intelligence and Humanized Computing, 2019, 10 : 3155 - 3169
  • [46] Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems
    Dagal, Idriss
    Akin, Burak
    Akboy, Erdem
    INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2022, 46 (07) : 8742 - 8759
  • [47] Three-Dimensional Path Planning for AUVs Based on Standard Particle Swarm Optimization Algorithm
    Zhan, Bangshun
    An, Shun
    He, Yan
    Wang, Longjin
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2022, 10 (09)
  • [48] Constrained optimization with an improved particle swarm optimization algorithm
    Munoz Zavala, Angel E.
    Hernandez Aguirre, Arturo
    Villa Diharce, Enrique R.
    Botello Rionda, Salvador
    INTERNATIONAL JOURNAL OF INTELLIGENT COMPUTING AND CYBERNETICS, 2008, 1 (03) : 425 - 453
  • [49] An improved particle swarm optimization particle filter algorithm based on harmony search
    Liu, Zhen-dong
    Fang, Yi-ming
    Liu, Le
    Zhao, Xiao-dong
    PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 1661 - 1666
  • [50] An Improved Particle Swarm Algorithm for Search Optimization
    Li Zhi-jie
    Liu Xiang-dong
    Duan Xiao-dong
    Wang Cun-rui
    PROCEEDINGS OF THE 2009 WRI GLOBAL CONGRESS ON INTELLIGENT SYSTEMS, VOL I, 2009, : 154 - 158
12345