AUV Vertical Motion Control Based on Kalman Filtering
文献类型：会议论文
| 作者 | Guo JQ(国婧倩)1; Zheng R(郑荣)3 ; Wei AB(魏奥博)2,3
|
| 出版日期 | 2018 |
| 会议日期 | August 16, 2018 |
| 会议地点 | Beijing, China |
| 页码 | 334-339 |
| 英文摘要 | AUV docking is a hot topic in underwater robot research. In order to fulfill the mission of docking, AUV needs to have more precise vertical navigation control ability, reduce the depth of the sensor there is a big noise data when calculating the error and AUV vertical depth when motion is not smooth. In this paper, the kalman filter is integrated into the motion control of vertical plane, and the double closed-loop PID cascade control system is designed and not based on the model. The whole control system is divided into two loops, the inner ring for the trim Angle PID controller, the output through the thrust allocation to calculate the required torque and torque, outer ring for the depth of the PID controller, the output for the input of pitch Angle. The kalman filter is integrated into the feedback loop of the depth data to improve the accuracy of the feedback data. The precision of vertical motion control is reflected by the stability of fixed depth navigation. Through the experiment on the lake, the depth mean square deviation of the vertical plane at the speed of 2kn is 0.24m2, the mean square deviation of the vertical Angle is 0.18 degree2 which proves the feasibility of this method. |
| 产权排序 | 1 |
| 会议录 | Proceedings of the 1st WRC Symposium on Advanced Robotics and Automation 2018
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-5386-7674-5 |
| WOS记录号 | WOS:000457712000054 |
| 源URL | [http://ir.sia.cn/handle/173321/23782]  |
| 专题 | 沈阳自动化研究所_海洋信息技术装备中心 |
| 通讯作者 | Wei AB(魏奥博) |
| 作者单位 | 1.Northeastern University, Shenyang, CO 110819 China 2.University of Chinese Academy of Sciences, Beijing 100049 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, CO 110016 China |
| 推荐引用方式 GB/T 7714 | Guo JQ,Zheng R,Wei AB. AUV Vertical Motion Control Based on Kalman Filtering[C]. 见:. Beijing, China. August 16, 2018. |
入库方式： OAI收割
来源：沈阳自动化研究所
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