Zhao Kaihui, Li Peng, Zhang Changfan, Li Xiangfei, He Jing, Lin Yuliang
College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410000, China.
Sensors (Basel). 2017 Dec 6;17(12):2833. doi: 10.3390/s17122833.
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.
本文提出了一种用于永磁同步电机（PMSM）驱动系统的电流传感器故障重构和未知负载扰动估计的新方案。首先，将原始的PMSM系统转换为两个子系统；第一个子系统存在未知的系统负载扰动，且与传感器故障无关，第二个子系统存在传感器故障，但不存在未知负载扰动。引入一个新的状态变量后，存在传感器故障的增广子系统可转换为存在执行器故障的子系统。其次，设计了两个滑模观测器（SMO）：在存在未知负载扰动的子系统中，通过第一个SMO估计未知负载扰动，在存在传感器故障的增广子系统中，利用第二个SMO重构传感器故障。所提出的SMO的增益及其稳定性分析通过线性矩阵不等式（LMI）的求解来进行。最后，通过仿真和实验验证了所提方案的有效性。结果表明，所提方案能够对PMSM驱动系统的电流传感器故障进行重构，并估计未知负载扰动。
