采用在线干扰补偿方案对无人潜航器进行动态建模

IF 1.4 Q4 ROBOTICS Journal of Robotics Pub Date : 2024-03-14 DOI:10.1155/2024/1996159
S. Azid, Utkal Mehta, Adarsh Kuar, Zahid Ali
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引用次数: 0

摘要

近年来,随着机器人技术的发展,水下机器人的设计和开发越来越受到关注。无人水下航行器(UUV)在水产养殖、深海探索、研究和加强救援任务方面有很多应用。然而,在开发任何水下航行器系统以探索水下世界深处时,都必须考虑各种因素。在本文中,我们开发了最适合理解各种系统参数的模型。新的数学模型考虑了对系统施加的某些约束和外部干扰。此外,我们还为 UUV 的稳定性和鲁棒性提出了一种控制策略。建议的观测器和模型非常简单,能够以最小的计算成本准确估计所有系统状态和未知临界扰动的全局影响。
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Dynamic Modeling of Unmanned Underwater Vehicles with Online Disturbance Compensation Scheme
With the advancement in robotics technology over the recent years, underwater robots’ design and development are gaining interest. Unmanned underwater vehicles (UUVs) have many applications in aquaculture, deep-sea exploration, research, and enhanced rescue tasks. However, various factors must be considered when developing any underwater vehicle system to explore the deep ends of the underwater world. In this paper, we develop the most suitable model for understanding various system parameters. The new mathematical model considers certain constraints and external disturbances exerted on the system. Also, a control strategy is suggested for the UUV’s stability and robustness. The suggested observer and model are simple, allowing for accurate estimations of all system states and the global impacts of unknown limped perturbations with a minimal computational cost.
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来源期刊
CiteScore
3.70
自引率
5.60%
发文量
77
审稿时长
22 weeks
期刊介绍: Journal of Robotics publishes papers on all aspects automated mechanical devices, from their design and fabrication, to their testing and practical implementation. The journal welcomes submissions from the associated fields of materials science, electrical and computer engineering, and machine learning and artificial intelligence, that contribute towards advances in the technology and understanding of robotic systems.
期刊最新文献
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