• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于计算流体动力学模拟的微型自主水下航行器水动力参数识别及其在控制性能评估中的应用

Mini-AUV Hydrodynamic Parameters Identification via CFD Simulations and Their Application on Control Performance Evaluation.

作者信息

Castillo-Zamora José J, Camarillo-Gómez Karla A, Pérez-Soto Gerardo I, Rodríguez-Reséndiz Juvenal, Morales-Hernández Luis A

机构信息

L2S of Université Paris Sud-CNRS-CentraleSupelec, Université Paris Saclay, 91190 Gif-sur-Yvette, France.

IPSA Paris, 94200 Ivry-sur-Seine, France.

出版信息

Sensors (Basel). 2021 Jan 26;21(3):820. doi: 10.3390/s21030820.

DOI:10.3390/s21030820
PMID:33530425
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7865711/
Abstract

This manuscript presents a fully detailed methodology in order to identify the hydrodynamic parameters of a mini autonomous underwater vehicle (mini-AUV) and evaluate its performance using different controllers. The methodology consists of close-to-reality simulation using a Computed Fluid Dynamics (CFD) module of the ANSYS™ Workbench software, the processing of the data, obtained by simulation, with a set of Savistky-Golay filters; and, the application of the Least Square Method in order to estimate the hydrodynamic parameters of the mini-AUV. Finally, these parameters are considered to design the three different controllers that are based on the robot manipulators theory. Numerical simulations are carried out to evaluate the performance of the controllers.

摘要

本手稿提出了一种全面详细的方法,以识别微型自主水下航行器(mini-AUV)的流体动力学参数,并使用不同的控制器评估其性能。该方法包括使用ANSYS™ Workbench软件的计算流体动力学(CFD)模块进行接近实际的模拟,对模拟获得的数据使用一组Savistky-Golay滤波器进行处理;以及应用最小二乘法来估计mini-AUV的流体动力学参数。最后,考虑这些参数来设计基于机器人操纵器理论的三种不同控制器。进行了数值模拟以评估控制器的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/70cbbee1155f/sensors-21-00820-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/9fb4476f1b58/sensors-21-00820-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/0059c0a4569e/sensors-21-00820-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/507d05d66d8a/sensors-21-00820-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/a25676c6b77a/sensors-21-00820-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/42953c97ceda/sensors-21-00820-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/a230e0eec4ae/sensors-21-00820-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/70cbbee1155f/sensors-21-00820-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/9fb4476f1b58/sensors-21-00820-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/0059c0a4569e/sensors-21-00820-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/507d05d66d8a/sensors-21-00820-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/a25676c6b77a/sensors-21-00820-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/42953c97ceda/sensors-21-00820-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/a230e0eec4ae/sensors-21-00820-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2b/7865711/70cbbee1155f/sensors-21-00820-g008.jpg

相似文献

1
Mini-AUV Hydrodynamic Parameters Identification via CFD Simulations and Their Application on Control Performance Evaluation.基于计算流体动力学模拟的微型自主水下航行器水动力参数识别及其在控制性能评估中的应用
Sensors (Basel). 2021 Jan 26;21(3):820. doi: 10.3390/s21030820.
2
Design and Motion Performance Analysis of Turbulent AUV Measuring Platform.湍流自主水下航行器测量平台的设计与运动性能分析
Sensors (Basel). 2022 Jan 8;22(2):460. doi: 10.3390/s22020460.
3
Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data.基于CFD数据的AUV建模与轨迹跟踪模型预测控制新方法
Sensors (Basel). 2022 Jun 1;22(11):4234. doi: 10.3390/s22114234.
4
New Vectorial Propulsion System and Trajectory Control Designs for Improved AUV Mission Autonomy.用于提高自主水下航行器任务自主性的新型矢量推进系统与轨迹控制设计
Sensors (Basel). 2018 Apr 17;18(4):1241. doi: 10.3390/s18041241.
5
Motion control and path optimization of intelligent AUV using fuzzy adaptive PID and improved genetic algorithm.基于模糊自适应PID和改进遗传算法的智能自主水下航行器运动控制与路径优化
Math Biosci Eng. 2023 Mar 14;20(5):9208-9245. doi: 10.3934/mbe.2023404.
6
Observability analysis of DVL/PS aided INS for a maneuvering AUV.用于机动自主水下航行器的深度与速度传感器/位置传感器辅助惯性导航系统的可观测性分析
Sensors (Basel). 2015 Oct 22;15(10):26818-37. doi: 10.3390/s151026818.
7
Hydrodynamic analysis and manipulation control on a streamlined I-AUV.流线型I型自主水下航行器的水动力分析与操纵控制
ISA Trans. 2024 Oct;153:453-466. doi: 10.1016/j.isatra.2024.07.019. Epub 2024 Jul 20.
8
Real-Time Ocean Current Compensation for AUV Trajectory Tracking Control Using a Meta-Learning and Self-Adaptation Hybrid Approach.基于元学习与自适应混合方法的AUV轨迹跟踪控制实时洋流补偿
Sensors (Basel). 2023 Jul 14;23(14):6417. doi: 10.3390/s23146417.
9
Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations.具有执行器饱和的自主水下航行器俯仰和偏航通道的自适应积分反馈控制器
ISA Trans. 2016 Nov;65:284-295. doi: 10.1016/j.isatra.2016.08.002. Epub 2016 Sep 15.
10
Data-Gathering Scheme Using AUVs in Large-Scale Underwater Sensor Networks: A Multihop Approach.在大规模水下传感器网络中使用自主水下航行器的数据收集方案:一种多跳方法。
Sensors (Basel). 2016 Sep 30;16(10):1626. doi: 10.3390/s16101626.

引用本文的文献

1
Linear matrix genetic programming as a tool for data-driven black-box control-oriented modeling in conditions of limited access to training data.线性矩阵遗传规划作为一种在训练数据获取受限条件下用于数据驱动的面向黑箱控制建模的工具。
Sci Rep. 2024 Jun 3;14(1):12666. doi: 10.1038/s41598-024-63419-8.
2
Fuzzy logic controller for UAV with gains optimized via genetic algorithm.通过遗传算法优化增益的无人机模糊逻辑控制器。
Heliyon. 2024 Feb 15;10(4):e26363. doi: 10.1016/j.heliyon.2024.e26363. eCollection 2024 Feb 29.

本文引用的文献

1
Experimental and Computational Methodology for the Determination of Hydrodynamic Coefficients Based on Free Decay Test: Application to Conception and Control of Underwater Robots.基于自由衰减试验测定水动力系数的实验与计算方法:在水下机器人概念设计与控制中的应用
Sensors (Basel). 2019 Aug 21;19(17):3631. doi: 10.3390/s19173631.
2
Modeling and Control of a Micro AUV: Objects Follower Approach.微型水下航行器的建模与控制:目标跟随方法。
Sensors (Basel). 2018 Aug 6;18(8):2574. doi: 10.3390/s18082574.
3
Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.
《多传感器信息融合进展:理论与应用(2017年)》
Sensors (Basel). 2018 Apr 11;18(4):1162. doi: 10.3390/s18041162.
4
Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method.基于改进速度障碍法的无人水下航行器动态避障
Sensors (Basel). 2017 Nov 27;17(12):2742. doi: 10.3390/s17122742.
5
Polar Grid Navigation Algorithm for Unmanned Underwater Vehicles.用于无人水下航行器的极坐标网格导航算法
Sensors (Basel). 2017 Jul 9;17(7):1599. doi: 10.3390/s17071599.
6
An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles.一种适用于低成本自主水下航行器的有效地形辅助导航
Sensors (Basel). 2017 Mar 25;17(4):680. doi: 10.3390/s17040680.
7
Smoothing and differentiation of data by simplified least square procedure.用简化最小二乘法对数据进行平滑和求导。
Anal Chem. 1972 Sep 1;44(11):1906-9. doi: 10.1021/ac60319a045.