顺和安全的停止:对于重腿机器人,固定时间故障耐受性控制,具有对耐受性能力的积极识别
Shaoxun Liu1, Shiyu Zhou1, Lei Shi1
1School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
ISA transactions
|December 13, 2024
概括
本研究介绍了使用主动伺服故障状态估计器 (ASFSE) 的重腿机器人 (HLR) 的故障耐受性控制 (FTC) 框架. 它通过预测和管理伺服器故障来确保平稳的停止并防止损坏.
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:
- 重腿机器人 (HLR) 对制造和运输效率至关重要.
- 先进的主动伺服器故障诊断和故障耐受性控制 (FTC) 对HLR可靠性至关重要.
- 现有系统需要增强实时故障识别和缓解的方法.
研究的目的:
- 为HLRs开发一个新的FTC框架,包括主动故障状态识别和故障容忍能力评估.
- 为实时的伺服器状态监控引入一个主动伺服器故障状态估计器 (ASFSE).
- 为了确保精确的轨迹跟踪和减轻在伺服器故障期间设备损坏.
主要方法:
- 使用剩余差异开发一个主动伺服故障状态估计器 (ASFSE).
- 实施双线颗粒过器 (DPF) 以预测超出容忍能力区间 (TCI) 的情况.
- 关于目标轨迹修改器 (TTM) 和固定时间后退控制器 (FTBC) 的建议,用于轨迹调整和趋同.
主要成果:
- ASFSE可以实时监控伺服器状态.
- 在故障条件下,DPF算法有效地预测何时HLR超过TCI.
- 该TTM和FTBC确保顺的停车和精确的轨迹跟踪,即使在模型的不确定性.
结论:
- 拟议的FTC框架提高了HLR的安全性和可靠性.
- 集成ASFSE,DPF,TTM和FTBC提供了强大的容错能力.
- 数学稳定性证明和模拟验证了框架在减轻伺服器故障影响方面的有效性.
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