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基于偏微分方程的车载柔性机械手边界控制研究

Research on boundary control of vehicle-mounted flexible manipulator based on partial differential equations.

作者信息

Tang Yuzhi

机构信息

Nantong Institute of Technology, Nantong, Jiangsu Province, China.

出版信息

PLoS One. 2025 Jan 7;20(1):e0317012. doi: 10.1371/journal.pone.0317012. eCollection 2025.

DOI:10.1371/journal.pone.0317012
PMID:39775285
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11706493/
Abstract

Vehicle-mounted flexible robotic arms (VFRAs) are crucial in enhancing operational capabilities in sectors where human intervention is limited due to accessibility or safety concerns, such as hazardous environments or precision surgery. This paper introduces the latest generation of VFRAs that utilize advanced soft materials and are designed with elongated structures to provide greater flexibility and control. We present a novel mathematical model, derived using Hamilton's principle, which simplifies the analysis of the arm's dynamic behaviors by employing partial differential equations (PDEs). This model allows us to understand how these arms behave over time and space, classifying them as distributed parameter systems. Furthermore, we enhance the practical utility of these robotic arms by implementing a proportional-derivative (PD) based boundary control law to achieve precise control of movement and suppression of vibrations, which are critical for operations requiring high accuracy. Our approach's effectiveness and practical utility are evidenced by numerical simulations, which verify that our advanced control strategy greatly enhances the performance and dependability of VFRAs in actual applications. These advancements not only pave the way for more sophisticated robotic implementations but also have broad implications for the future of automated systems in various industries.

摘要

车载柔性机器人手臂(VFRAs)在提升因可达性或安全问题导致人工干预受限的领域的操作能力方面至关重要,例如危险环境或精准手术。本文介绍了利用先进软材料并采用细长结构设计以提供更大灵活性和控制能力的新一代VFRAs。我们提出了一种基于哈密顿原理推导的新型数学模型,该模型通过使用偏微分方程(PDEs)简化了对手臂动态行为的分析。此模型使我们能够了解这些手臂在时间和空间上的行为,将它们归类为分布参数系统。此外,我们通过实施基于比例 - 微分(PD)的边界控制律来增强这些机器人手臂的实际效用,以实现对运动的精确控制和振动抑制,这对于要求高精度的操作至关重要。数值模拟证明了我们方法的有效性和实际效用,验证了我们的先进控制策略在实际应用中极大地提高了VFRAs的性能和可靠性。这些进展不仅为更复杂的机器人实现铺平了道路,也对各行业自动化系统的未来具有广泛影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/b090d1079f63/pone.0317012.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/e46d11995bd3/pone.0317012.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/954422e43a0c/pone.0317012.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/bf3e554895d1/pone.0317012.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/f4984e7124bc/pone.0317012.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/3b285d0c5c4f/pone.0317012.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/c030374ac07d/pone.0317012.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/b090d1079f63/pone.0317012.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/e46d11995bd3/pone.0317012.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/954422e43a0c/pone.0317012.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/bf3e554895d1/pone.0317012.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/f4984e7124bc/pone.0317012.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/3b285d0c5c4f/pone.0317012.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/c030374ac07d/pone.0317012.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec9/11706493/b090d1079f63/pone.0317012.g007.jpg

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Dual-loop control and state prediction analysis of QUAV trajectory tracking based on biological swarm intelligent optimization algorithm.基于生物群体智能优化算法的四旋翼飞行器(QUAV)轨迹跟踪双环控制与状态预测分析
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Promising directions of machine learning for partial differential equations.
机器学习在偏微分方程方面的前景方向。
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Adaptive Prescribed Performance Control of A Flexible-Joint Robotic Manipulator With Dynamic Uncertainties.自适应规定性能控制的柔性关节机器人具有动态不确定性。
IEEE Trans Cybern. 2022 Dec;52(12):12905-12915. doi: 10.1109/TCYB.2021.3091531. Epub 2022 Nov 18.
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Motion Planning and Adaptive Neural Tracking Control of an Uncertain Two-Link Rigid-Flexible Manipulator With Vibration Amplitude Constraint.具有振动幅度约束的不确定两连杆刚柔混合机械臂的运动规划和自适应神经跟踪控制。
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