基于微惯性导航传感器的模型转换型ROV抗波动态定位研究

Zeng Qingjun, Liang Song, Liu Huiting, Zhang Ming, Dai Xiaoqiang
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引用次数: 0

摘要

针对水下航行器在水面运行时波浪扰动带来的不确定性,结合海洋工程新型模型转换遥控航行器(MC-ROV),建立了基于CFD的6DOF定位动力学模型。根据定位误差设计了一种力力矩分配策略,并用非奇异终端滑动模型(NTSM)算法对定位误差进行补偿,同样降低了波浪对定位误差的影响。并基于微机电系统(MEMS)器件,设计了集成式微惯性导航系统。采用无气味卡尔曼滤波(Unscented Kalman Filter, UKF)来提高MC-ROV的导航精度和实时位置信息估计。仿真结果表明,该算法能使水下机器人快速有效地到达预定位置,并能在遇到扰动时及时调整力和力矩策略,减少了扰动的负面影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on dynamic positioning of Model-Converted ROV anti-waves based on micro inertial navigation sensors
In terms of the uncertainties induced by wave disturbances when an underwater vehicle is operated by the surface of water, a dynamic model based on CFD is built to analyze 6DOF positioning combining with the novelty Model-Converted Remotely Operated Vehicle (MC-ROV) of ocean engineering. A strategy of force and moment allocations is designed according to positioning error, then compensating it with an algorithm known as Non-singular Terminal Sliding Model (NTSM) to low the impact brought by waves likewise. And based on Micro-Electro-Mechanical Systems (MEMS) devices, an integrated micro inertial navigation system is designed. The Unscented Kalman Filter (UKF) is used to improve the navigation accuracy and estimate the real-time location information of MC-ROV. Simulation results show that the proposed algorithm can make the underwater vehicle reach a pre-given position rapidly and effectively, moreover it can adjust the strategy of force and moment promptly when encounters with perturbations so that reduces the negative effects.
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