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Design of Robust Stabilization and Fault Diagnosis for an Auto-balancing Two-Wheeled Cart

机译:自动平衡两轮手推车的鲁棒稳定与故障诊断设计

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摘要

This paper investigates robust fault diagnosis strategies for the auto-balancing of an ergonomically designed two-wheeled cart which is inherently unstable and has a non-minimum phase. To endow the rider with robust stabilization, the normalized coprime factorization for steering is employed for allowing maximum model uncertainties and the driving orientation is achieved with an electronic differential steering control. A model-based fault-detection filter is designed to detect sensor faults. The observer gain obtained by solving an algebraic Riccati equation in the normalized coprime factorization approach offers some design convenience associated with the fault diagnosis filter. In order to promptly alert the rider for safety purposes in the event of a malfunction, the decision-making process to identify a critical failure is also investigated. Finally, evaluation examples are given to illustrate the performance of the proposed robust fault diagnosis strategies.
机译:本文研究了一种稳健的故障诊断策略,用于根据人体工程学设计的两轮手推车自动平衡,该手推车固有地不稳定且具有非最小相位。为了使骑手具有强大的稳定性,采用了用于转向的归一化互质分解,以实现最大的模型不确定性,并且通过电子差速转向控制来实现驾驶方向。基于模型的故障检测滤波器旨在检测传感器故障。通过在归一化互质分解方法中求解代数Riccati方程获得的观测器增益为故障诊断滤波器提供了一些设计上的便利。为了在出现故障的情况下出于安全目的迅速警告骑手,还研究了确定严重故障的决策过程。最后,给出了评估示例以说明所提出的鲁棒故障诊断策略的性能。

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