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基于阿基米德螺旋加密重构技术的无人航行器KT辨识研究
Parameter identification of unmanned underwater vehicle's KT model based on Archimedes spiral interpolation algorithm
- DOI:
- 作者:
- 韩璐羽1, 白佳钰1, 于曹阳1, 连琏1,2
HAN Lu-yu1, BAI Jia-yu1, YU Cao-yang1, LIAN Lian1,2
- 作者单位:
- 1. 上海交通大学 海洋学院, 上海 200030;
2. 上海交通大学 海洋工程国家重点实验室, 上海 200240
1. School of Oceanography, Shanghai Jiaotong University, Shanghai 200030, China;
2. State Key Laboratory of Ocean Engineering, Shanghai Jiaotong University, Shanghai 200240, China
- 关键词:
- 无人航行器;参数辨识;插值重构;阿基米德螺旋
unmanned underwater vehicles; parameter identification; interpolation reconstruction; Archimedes spiral
- 摘要:
- 针对无人航行器操纵模型参数辨识精度受限于航向数据采集频率的问题，提出一种运用阿基米德螺旋(Archimedes spiral, AS)加密重构稀疏数据集进而改良辨识精度的思路。首先，选取不同采集频率的Z形操纵仿真试验数据集，基于最小二乘算法进行一阶线性KT方程的参数辨识，定量分析采样频率对辨识精度的影响，阐述重构稀疏数据的必要性。随后，提出预先应用AS插值加密优化的策略，重构光滑连续的加密数据集，并与初始稀疏集、基于三次样条插值的加密集完成对比分析。数值结果表明，基于AS的数据重构策略使KT辨识精度提高了31.1%，平均误差仅2.4%，较三次样条插值处理准确了1%。基于AS的加密重构技术弥补了实际数据采样频率相对较低时的不足，为无人航行器高精度操纵模型参数辨识提供了新思路。
Archimedes spiral (AS) is used for the interpolation reconstruction of sparse data to improve the parameter identification accuracy of unmanned underwater vehicle′s maneuvering model, which is limited by the frequency of heading angle data acquisition. First, 15° zigzag simulation is carried out to collect data with different acquisition frequencies and the parameters of the first-order linear KT equation are identified based on the least squares algorithm, which helps us quantitatively analyze the influence of sampling frequency on identification accuracy and expound the necessity of reconstructing sparse data. Then, the AS interpolation optimization strategy is applied to reconstruct smooth and continuous data with increased density, and its identification effects is compared with those of the initial sparse data and the data optimized based on cubic spline interpolation. The numerical results show that the AS-based data reconstruction strategy improves the KT identification accuracy by 31.1%, and the average error is only 2.4%, which is 1% more accurate than that of the cubic spline interpolation strategy. The AS-based interpolation algorithm makes up for the deficiency when the data sampling frequency is relatively low, and provides a new idea for the high-precision parameter identification of unmanned vehicle′s maneuvering model.
2023,45(7): 79-84 收稿日期：2022-05-27
DOI：10.3404/j.issn.1672-7649.2023.07.017
分类号：U661.33
基金项目：国家自然科学基金资助项目（51909161）；上海市科学技术委员会资助项目（22ZR1434600）
作者简介：韩璐羽(2002-),女,研究方向为无人系统辨识
