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在平面可重新配置的电缆驱动的平行机器人中控制和规划电缆故障耐受性
Adhiti Raman1, Ian Walker2, Venkat Krovi1
1Clemson University, Automotive Engineering, Greenville, SC, United States.
Frontiers in robotics and AI
|June 2, 2023
概括
本研究介绍了可重新配置的电缆驱动并行机器人 (rCDPR) 的耐故障控制框架. 该系统使用自适应估计来检测和恢复故障,使机器人能够在电缆故障后完成任务.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 机械工程 机械工程
背景情况:
- 电缆驱动的并行机器人 (CDPR) 提供了独特的优势,但容易发生电缆故障.
- 在CDPR中,几何重构性引入了动力冗余,从而实现了故障容忍.
- 现有的故障耐受性控制 (FTC) 方法往往难以同时进行故障诊断和任务恢复.
研究的目的:
- 为可重新配置的CDPR (rCDPR) 开发FTC框架,将故障检测,诊断和任务恢复集成在一起.
- 通过利用动力冗余,使rCDPR能够保持轨迹跟踪,尽管有多个电缆故障.
- 确保在轨道精度至关重要的应用中完成任务,例如3D打印或接.
主要方法:
- 实现交互式多重模型 (IMM) 适应性估计过器,用于同时检测和诊断故障 (FDD).
- 开发一个冗余解决方案方案,优先考虑避免奇点,可操纵性和匙质量最大化.
- 引入轨迹跟踪方法,用于自动恢复任务到故障点.
主要成果:
- 拟议的FTC框架在平面rCDPR与弹性电缆和不确定性的模拟中成功验证.
- 该系统通过多个电缆故障展示了强大的轨迹跟踪,适应不断变化的机器人拓 (过度约束到不足约束).
- 整合了恒定速度的动力前和LQR反控制器,确保了稳定状态输入和抑制振荡.
结论:
- 基于IMM的FTC框架为rCDPR提供了有效的容错性,使其能够持续运行和完成任务.
- 开发的冗余解决和恢复战略提高了CDPR在关键工业过程中的可靠性和适用性.
- 这项研究有助于推进强大的机器人系统,能够自主适应动态故障.
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