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Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System

机译:PMSM驱动系统基于滑模观测器的电流传感器故障重构和未知负载扰动估计

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摘要

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.
机译:本文提出了一种重构永磁同步电动机(PMSM)驱动系统电流传感器故障并估算未知负载扰动的新方案。首先,将原始PMSM系统转换为两个子系统;第一个子系统具有与传感器故障无关的未知系统负载干扰,第二个子系统具有传感器故障,但不受未知负载干扰影响。引入新的状态变量后,具有传感器故障的增强子系统可以转换为具有执行器故障的子系统。其次,设计了两个滑模观测器(SMO):未知负载扰动由子系统中的第一个SMO估计,具有未知负载扰动,并且传感器故障可以使用增强子系统中的第二个SMO进行重建,后者具有传感器故障。拟议的SMO的增益及其稳定性分析是通过线性矩阵不等式(LMI)的解决方案开发的。最后,通过仿真和实验验证了该方案的有效性。结果表明,该方案可以重构电流传感器故障并估计PMSM驱动系统的未知负载扰动。

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