Research on Bottom Drag Prevention for an Unmanned Deepwater Collection

Autor: Yu-Long Xiao, Guigeng Yang, Yan Peng, Qi-Xing Cheng, Zhu Chuan, Junfeng Yao
Rok vydání: 2018
Předmět:
Zdroj: 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC).
Popis: For reducing the risk of marine monitoring crew and avoiding the occurrence of the bottom drag event of water collector, this paper focuses on an unmanned deepwater collection based on the deck of unmanned surface vehicle(USV). From analysis of the water flow model given by Acoustic Doppler Current Profilers(ADCP), a depth prediction model was proposed. So that the control strategies was further developed and the closed-loop control systems were well designed. The deepwater collection mechanism controlled by this system can ensure that the distance between the collector and seabed is more than two meters while in the descending task. It This system can be used utilized in island surveys, marine monitoring and hydrology studies.
Databáze: OpenAIRE