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Updated: Jan 15, 2026

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Ex vivo Mechanical Loading of Tendon
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模拟和补偿控制一个单一的肌盖驱动系统,具有时间变化的参数
Mingxing Yang1,2,3, Qi Wang2,3, Hongliang Wang1,3
1Department of Spinal Orthopaedics, Maanshan People's Hospital, Ma'anshan, 243000, Anhui, China.
Scientific reports
|October 8, 2025
概括
这项研究引入了一种适应式滑动模式补偿控制 (ASMCC) 用于肌盖驱动系统 (TSAS). 这种新的方法通过补偿非线性摩擦和歇斯底里,提高了精确的远端控制,提高了轨迹跟踪精度.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 机械工程 机械工程
- 生物机械学是生物机械学.
背景情况:
- 肌盖驱动系统 (TSAS) 提供了合规性和灵巧性,但由于非线性摩擦和歇斯底里,在精确的远端控制方面面临着挑战.
- 准确的轨迹跟踪对于TSAS应用程序至关重要,但非线性动态阻碍了性能.
研究的目的:
- 开发一种新的自适应滑动模式补偿控制 (ASMCC) 方案,用于TSAS中精确的轨迹跟踪.
- 解决影响TSAS控制精度的摩擦和歇斯底里等非线性现象.
主要方法:
- 基于库伦摩擦模型的TSAS静态和动态模型的分析.
- 使用离线近接端传感器测量的反向传输模型的校准.
- 开发一种适应性控制策略,将反向模型与利亚普诺夫稳定性理论以及用于在线参数估计的滑动模式控制器相结合.
主要成果:
- 分析了TSAS的静态和动态模型,通过模拟和实验证实了系统输出特征.
- 拟议的ASMCC计划在TSAS的参数识别和补偿方面表现出了有效性和准确性.
- 有或没有外部弹的轨迹跟踪实验验证实了控制策略的可行性和性能.
结论:
- 新的ASMCC方案有效地弥补了TSAS中的非线性,从而实现了准确的轨迹跟踪.
- 该研究证实了该系统在单肌盖系统的参数识别和精度补偿方面的有效性.
- 拟议的控制策略提供了一种可行的解决方案,以提高肌盖驱动系统的精度和性能.
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