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Fault detection for robot manipulators with parametric uncertainty: a prediction-error-based approach

机译:具有参数不确定性的机器人机械手的故障检测:一种基于预测误差的方法

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摘要

In this paper, we introduce a new approach to fault detection for robot manipulators. The technique, which is based on the isolation of fault signatures via filtered torque prediction error estimates, does not require measurements or estimates of manipulator acceleration as is the case with some previously suggested methods. The method is formally demonstrated to be robust under uncertainty in the robot parameters. Furthermore, an adaptive version of the algorithm is introduced, and shown to both improve coverage and significantly reduce detection times. The effectiveness of the approach is demonstrated by experiments with a two-joint manipulator system.
机译:在本文中,我们介绍了一种新的机器人机械手故障检测方法。该技术基于通过滤波后的转矩预测误差估计值隔离故障特征的技术,不需要像某些先前建议的方法那样对机械手加速度进行测量或估计。正式证明了该方法在机器人参数不确定的情况下的鲁棒性。此外,引入了该算法的自适应版本,并被证明可以提高覆盖范围并显着减少检测时间。通过使用两关节机械手系统进行的实验证明了该方法的有效性。

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