学位论文详细信息
Anomaly detection based on the estimation of speed and flow mapping for controlled Lagrangian particles | |
Anomaly detection;Fault detection;Autonomous underwater vehicles;Autonomous indoor blimp;Acoustic detection;Wind field mapping;Adaptive control | |
Cho, Sungjin ; Zhang, Fumin Edwards, Catherine Electrical and Computer Engineering Vela, Patricio Ma, Xiaoli West, Michael Rogers, Jonathan ; Zhang, Fumin | |
University:Georgia Institute of Technology | |
Department:Electrical and Computer Engineering | |
关键词: Anomaly detection; Fault detection; Autonomous underwater vehicles; Autonomous indoor blimp; Acoustic detection; Wind field mapping; Adaptive control; | |
Others : https://smartech.gatech.edu/bitstream/1853/62180/1/CHO-DISSERTATION-2017.pdf | |
美国|英语 | |
来源: SMARTech Repository | |
【 摘 要 】
The main contribution of this dissertation is a set of algorithms that detect anomaly of autonomous underwater vehicles (AUVs) without sensors monitoring vehicle components. Only using trajectory information, the proposed strategy detects abnormal vehicle motion under unknown ocean flow. It has the potential for mitigating abnormal vehicle motion with path-planning and controller design of AUVs. The experimental results of the Georgia Tech Miniature Autonomous Blimp (GT-MAB) and Georgia Tech Wind Measuring Robot (GT WMR) in an indoor test bed verify the proposed strategy.
【 预 览 】
Files | Size | Format | View |
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Anomaly detection based on the estimation of speed and flow mapping for controlled Lagrangian particles | 49908KB | download |