[1]袁健,周忠海,金光虎,等.基于卡尔曼滤波的自主式水下航行器大尺度编队控制[J].智能系统学报,2013,8(04):344-348.[doi:10.3969/j.issn.1673-4785.201304033]
 YUAN Jian,ZHOU Zhonghai,JIN Guanghu,et al.Large-scale formation control for autonomous underwater vehicles based on Kalman filtering[J].CAAI Transactions on Intelligent Systems,2013,8(04):344-348.[doi:10.3969/j.issn.1673-4785.201304033]
点击复制

基于卡尔曼滤波的自主式水下航行器大尺度编队控制(/HTML)
分享到:

《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第8卷
期数:
2013年04期
页码:
344-348
栏目:
出版日期:
2013-08-25

文章信息/Info

Title:
Large-scale formation control for autonomous underwater vehicles based on Kalman filtering
文章编号:
1673-4785(2013)04-0344-05
作者:
袁健12周忠海12金光虎12徐娟12李俊晓12
1. 山东省海洋环境监测技术重点实验室,山东 青岛 266001; 2. 山东省科学院 海洋仪器仪表研究所,山东 青岛 266001
Author(s):
YUAN Jian12 ZHOU Zhonghai12 JIN Guanghu12 XU Juan12 LI Junxiao12
1. Shandong Provincial Key Laboratory of Ocean Environment Monitoring Technology, Qingdao 266001, China; 2. Institute of Oceanographic Instrumentation of Shandong Academy of Sciences, Qingdao 266001, China
关键词:
自主式水下航行器卡尔曼滤波一致性大尺度编队控制
Keywords:
autonomous underwater vehicle Kalman filtering consensus large-scale formation control
分类号:
TP273
DOI:
10.3969/j.issn.1673-4785.201304033
文献标志码:
A
摘要:
针对网络环境下环境噪声对自主式水下航行器编队控制的影响,提出一种利用卡尔曼滤波实时估计AUV最优运动状态的编队控制方法.将空间间隔较远的多AUV系统建模为多智能体系统,从大尺度上研究其编队控制问题.为了得到每个AUV速度状态的最优估计值,每个AUV都嵌入一个全局卡尔曼滤波器,利用该全局滤波器进行最优估计从而计算出噪声环境下其自身的最优位置.仿真结果验证了所给出的控制策略的有效性.
Abstract:
Aiming at investigating the influence of environmental noise on autonomous underwater vehicles(AUV) formation control, a formation control for estimating AUV optimal motion states in real time is proposed. We modeled multiple AUVs with larger interval in space as a multi-agent system in order to investigate the large-scale formation control. Each AUV is embedded with one global Kalman filter to obtain the optimal estimation of each AUV speed states. And thus the optimal position of AUV in a noisy environment can be calculated by the optimal estimation with the global filter. Finally, some simulations were demonstrated to show the effectiveness of the proposed formation control scheme.

参考文献/References:

[1]FIORELLI E . Multi-AUV control and adaptive sampling in Monterey Bay[J]. IEEE Journal of Oceanic Engineering, 2006, 31(4): 935-948.
[2]YU S C, URA T. A system of multi-AUV interlinked with a smart cable for autonomous inspection of underwater structures[J]. International Journal of Offshore and Polar Engineering, 2004, 14(4): 264-272.
[3]DEREK P, ZHANG F M, LEONARD N E. Cooperative control for ocean sampling: the glider coordinated control system[J]. IEEE Transactions on Control Systems Technology, 2008, 16(4): 735-744.
[4]XIANG X B. Coordinated control for multiAUV systems based on hybrid automata[C]// IEEE International Conference on Robotics and Biomimetics. [S.l.],2007: 2121-2126.
[5]DO K D. Formation tracking control of unicycle-type mobile robots with limited sensing ranges[J]. IEEE Transactions on Control Systems Technology, 2008, 16(3): 527-538.
[6]YANG E F, GU D B. Nonlinear formationkeeping and mooring control of multiple autonomous underwater vehicles[J]. IEEE/ASME Transactions on Mechatronics, 2007, 2(2): 164-178.
[7]JADBABAIE A, LIN J, MORSE A S. Coordination of groups of mobile autonomous agents using nearest neighbor rules[J]. IEEE Transactions on Automatic Control, 2003, 48(6): 988-1001.

相似文献/References:

[1]李 晔,常文田,万 磊,等.水下机器人自适应卡尔曼滤波技术研究[J].智能系统学报,2006,1(02):44.
 LI Ye,CHANG Wen-tian,WAN Lei,et al.Research on underwater vehicle adaptive Kalman filter[J].CAAI Transactions on Intelligent Systems,2006,1(04):44.
[2]叶玲,李太华,代学武.无线传感器网络环境下基于卡尔曼滤波的PTP协议[J].智能系统学报,2012,7(06):518.
 YE Ling,LI Taihua,DAI Xuewu.Kalman filtering based precision time protocol (PTP) in wireless sensor networks[J].CAAI Transactions on Intelligent Systems,2012,7(04):518.
[3]李大伟,贾鹏飞,李卫国,等.一种基于卡尔曼滤波与模糊算法的变电站机器人组合导航及控制系统设计[J].智能系统学报,2013,8(03):226.
 LI Dawei,JIA Pengfei,LI Weiguo,et al.A kind of integrated navigation and control system design for substation robot based on the Kalman filtering and fuzzy algorithm[J].CAAI Transactions on Intelligent Systems,2013,8(04):226.
[4]马健,俞扬.一种基于全局位置估计误差的路标探索策略[J].智能系统学报,2014,9(03):313.[doi:10.3969/j.issn.1673-4785.201310014]
 MA Jian,YU Yang.Landmark exploration strategy using estimated global localization error[J].CAAI Transactions on Intelligent Systems,2014,9(04):313.[doi:10.3969/j.issn.1673-4785.201310014]
[5]欧伟奇,尹辉,许宏丽,等.一种基于Multi-Egocentric视频运动轨迹重建的多目标跟踪算法[J].智能系统学报,2019,14(02):246.[doi:10.11992/tis.201709003]
 OU Weiqi,YIN Hui,XU Hongli,et al.A multi-object tracking algorithm based on trajectory reconstruction on multi-egocentric video[J].CAAI Transactions on Intelligent Systems,2019,14(04):246.[doi:10.11992/tis.201709003]

备注/Memo

备注/Memo:
收稿日期:2013-04-15.     网络出版日期:2013-06-21. 
基金项目:国家自然科学基金资助项目(61074092);山东省自然科学基金资助项目(ZR2012FL18);山东省科学院博士基金项目(201244);青岛科技发展计划项目(13-+1-4-172-jch);国际科技合作资助项目(2011DFR60810).
通信作者:袁健. E-mail:jyuanjian801209@163.com.
作者简介:
袁健,男,1980年生,副研究员,博士,主要研究方向为自主水下航行器的编队控制.参与国家自然科学基金、国际科技合作项目、山东省自然科学基金等项目多项.发表学术论文20余篇.
周忠海,男,1975年生,研究员,博士,主要研究方向为海洋环境监测技术.先后承担了国家“863”计划、国际科技合作项目、海洋公益性项目和青岛市对外合作项目.现主持国家科技部国际科技合作项目1项.发表学术论文50余篇.
金光虎,男,1979年生,副研究员,博士,主要研究方向为海洋传感技术.参与多项国际科技合作项目.发表学术论文20余篇,获得专利10余项.
更新日期/Last Update: 2013-09-25