Abstract
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.
Highlights
The permanent magnet synchronous motor (PMSM) has been widely used in high-speed trains and electric vehicles, due to its good dynamic response, high torque-to-current ratio, high power density and excellent tracking precision [1]
This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for the PMSM-driven system
Two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in subsystem, which has unknown load disturbance, and the sensor faults are reconstructed using the second SMO in augmented subsystem which have sensor faults
Summary
The permanent magnet synchronous motor (PMSM) has been widely used in high-speed trains and electric vehicles, due to its good dynamic response, high torque-to-current ratio, high power density and excellent tracking precision [1]. An observer-based sensor fault estimation method for generalized Lipschitz nonlinear systems in the presence of input disturbance and measurement noise is developed in [11]. A new scheme for estimating the actuator and sensor fault for Lipschitz nonlinear systems with unstructured uncertainties is proposed using the sliding mode observer technique in [20,21]. This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for the PMSM-driven system. The scheme can be applicable for incipient fault, intermittent fault, high frequency and low frequency fault or any other types of faults This makes the theory of the sliding mode observer applicable to the engineering of PMSM current sensor fault reconstruction.
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