Waypoints Trajectory Tracking Control for Nonholonomic Unmanned Surface Vehicle under Environment Disturbance

Yuan, Jian; Liu, Hailin; Zhang, Wenxia

doi:10.1109/ccdc49329.2020.9164041

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…In [22], the performance of a novel control strategy for imperfect systems associated with physical realizations is investigated, which takes advantage of the unavoidable imperfections. In [23], we have investigated the waypoints trajectory-tracking problem for unmanned surface vehicle with environment disturbance. An upper-triangle and diagonal matrix decomposition method of Unscented Kalman Filter for the environment noise is proposed.…”

Section: Waypoint Trajectory-trackingmentioning

confidence: 99%

Waypoint Tracking Control for Autonomous Mobile Sampling and Dissolved Oxygen Enrichment of Unmanned Surface Vehicle

Yuan

Liu

Zhang

2022

Journal of Robotics

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An autonomous monitoring and control system of unmanned surface vehicle (USV) with mobile water quality monitoring, sampling, and oxygenation functions is constructed. The control hardware and monitoring configuration software of the system is designed, respectively, which can be installed on USV and its remote control and monitoring terminal. The kinematic modeling of USV, waypoint trajectory-tracking control, distributed controller, simulation of tracking control, and verification of software and hardware design are carried out. In order to reject the system noise and external noise, a states estimation method with fully observable states is considered in the control law design. The software and hardware are also implemented to verify the effectiveness of the monitoring platform. Through setting a series of monitoring target points and monitoring parameters in the configuration software of the remote user terminal or in the APP of the mobile user terminal, the USV can realize the automatic cruise monitoring using an autonomous navigation and tracking control algorithm, and quantitative water sampling collection. The reliability of the system is verified by the experiment of the shore test station, and the waypoint trajectory tracking and sensors data are replaying in a logview GUI of MOOS-Ivp and APP.

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Section: Waypoint Trajectory-trackingmentioning

confidence: 99%