Wind Speed Estimation and Station-Keeping Control for Stratospheric Airships with Extended Kalman Filter

被引：4

作者：

Shen, Shaoping ^{[1
]}

Liu, Ling ^{[1
]}

Huang, Bomin ^{[1
]}

Lin, Xianwu ^{[1
]}

Lan, Weiyao ^{[1
]}

Jin, Huiyu ^{[1
]}

机构：

[1] Xiamen Univ, Dept Automat, Xiamen 361005, Peoples R China

来源：

PROCEEDINGS OF THE 2015 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT AUTOMATION | 2015年 / 337卷

关键词：

Stratospheric airship; Wind speed estimation; Extended Kalman filter; Robustness; Station-Keeping control;

D O I：

10.1007/978-3-662-46463-2_17

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Wind speed estimation and station-keeping control for stratospheric airship are studied. A mathematical model of the stratospheric airship flying against the wind is derived. Then using the position information of the airship, an extended Kalman filter (EKF) is designed to estimate the speeds of the airship and the wind. Numerical simulations show the filter is effective and robust so that it can be used in not only wind speed estimation but also station-keeping control of the stratospheric airship.

引用

页码：145 / 157

页数：13

共 50 条

[21] A Method of the Locomotive Speed Estimation Based on Fuzzy Logic and Extended Kalman Filter [J].

Deng, Wenqi ;

Huang, Jingchun ;

Zhang, Qinghua .

PROCEEDINGS OF THE 15TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2020), 2020, :1353-1358

[22] Application of the Extended KALMAN Filter to the Parameters Estimation in the Vector Control of the BDFIG [J].

Omar, Saidi ;

Hammou, Djadi ;

Krim, Yazid ;

Mohamed, Menaa .

2016 THE 4TH IEEE INTERNATIONAL CONFERENCE ON SMART ENERGY GRID ENGINEERING (SEGE), 2016, :208-214

[23] Trajectory planning of stratospheric airship for station-keeping mission based on improved rapidly exploring random tree [J].

Luo, Qin-chuan ;

Sun, Kang-wen ;

Chen, Tian ;

Zhang, Yi-fei ;

Zheng, Ze-wei .

ADVANCES IN SPACE RESEARCH, 2024, 73 (01) :992-1005

[24] Autonomous Trajectory Planning Method for Stratospheric Airship Regional Station-Keeping Based on Deep Reinforcement Learning [J].

Liu, Sitong ;

Zhou, Shuyu ;

Miao, Jinggang ;

Shang, Hai ;

Cui, Yuxuan ;

Lu, Ying .

AEROSPACE, 2024, 11 (09)

[25] Evaluating Extended Kalman Filter and Unscented Kalman Filter for accurate trajectory estimation [J].

Golic, Anastasija ;

Radovic, Mirna .

2025 24TH INTERNATIONAL SYMPOSIUM INFOTEH-JAHORINA, INFOTEH, 2025,

[26] Trajectory control method of stratospheric airships based on model predictive control in wind field [J].

Zhang, Jiashi ;

Yang, Xixiang ;

Deng, Xiaolong ;

Lin, Huijing .

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 2019, 233 (02) :418-425

[27] Extended Kalman Filter for Speed Sensorless Induction Motor Control with Torque Compensation [J].

Chen, Tien-Chi ;

Fan, Gang-Ming ;

Chen, Chun-Jung ;

Wu, Ming-Fang ;

Lin, You-Je ;

Wang, Ming-Bin .

PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON INTELLIGENT TECHNOLOGIES AND ENGINEERING SYSTEMS (ICITES2013), 2014, 293 :697-704

[28] Station keeping control method based on deep reinforcement learning for stratospheric aerostat in dynamic wind field [J].

Bai, Fangchao ;

Yang, Xixiang ;

Deng, Xiaolong ;

Ma, Zhenyu ;

Long, Yuan .

ADVANCES IN SPACE RESEARCH, 2025, 75 (01) :752-766

[29] Air speed estimation from a pneumatic levitator using a Extended Kalman Filter in LabVIEW [J].

Nunez, David ;

Rojas, Cinthia ;

Garcia, Luis .

2019 IEEE 4TH COLOMBIAN CONFERENCE ON AUTOMATIC CONTROL (CCAC): AUTOMATIC CONTROL AS KEY SUPPORT OF INDUSTRIAL PRODUCTIVITY, 2019,

[30] Estimation of speed and armature temperature in a brushed DC drive using the extended Kalman filter [J].

Acarnley, PP ;

AlTayie, JK .

IEE PROCEEDINGS-ELECTRIC POWER APPLICATIONS, 1997, 144 (01) :13-20

← 1 2 3 4 5 →