Current Sensor Fault Diagnosis Based on a Sliding Mode Observer for PMSM Driven Systems

Due to the process defects and imperfection of drivers, permanent magnet synchronous motors (PMSM) are problematic to control. There is still a lack of effective high-performance control methods for inertial stabilized platforms based on PMSM currently. At present, the most frequently used method is sliding mode control (SMC), but traditional sliding mode control cannot overcome the contradiction between high performance and system chattering. In order to solve this problem and improve the system reliability and pointing accuracy, a new approach law for the sliding mode controller is proposed in this paper. In view of the large periodic torque ripple in PMSM, an iterative learning controller (ILC) is introduced to compensate for the disturbance. Based on these, aimed at suppressing all kinds of real-time disturbances in the working environment of the system, the extended state observer (ESO) is brought into the servo system to observe the lumped disturbance of the system, and the total disturbance observed is compensated into the sliding mode controller, so as to better suppress the system chattering and enhance the system’s ability of resisting external disturbance. Experiments are carried out on an inertial stabilization platform based on DSP + CPLD. The final experiments verify that the SMC with the new approach, combined with ILC and ESO, is of outstanding performance when compared with the traditional proportional integral (PI) + disturbance observer (DOB) control scheme.

Section: Traditional Sliding Mode Control (Smc)mentioning

confidence: 99%

“…Combining Equations (14), (23), (24), the output of the new SMC controller proposed in this paper is as follows:…”

Section: Smc Of New Approach Lawmentioning

confidence: 99%

High Precision Low-Speed Control for Permanent Magnet Synchronous Motor

Xia

Bao

2020

“…The stator voltage equations for the IPMSM in the rotating reference dq frame can be expressed as [ 16 ]:

…”

Section: Ipmsm Mathematical Modelmentioning

confidence: 99%

Current Sensor Fault Reconstruction for PMSM Drives

Huang

Luo

Zhang

et al. 2016

Self Cite

This paper deals with a current sensor fault reconstruction algorithm for the torque closed-loop drive system of an interior PMSM. First, sensor faults are equated to actuator ones by a new introduced state variable. Then, in αβ coordinates, based on the motor model with active flux linkage, a current observer is constructed with a specific sliding mode equivalent control methodology to eliminate the effects of unknown disturbances, and the phase current sensor faults are reconstructed by means of an adaptive method. Finally, an αβ axis current fault processing module is designed based on the reconstructed value. The feasibility and effectiveness of the proposed method are verified by simulation and experimental tests on the RT-LAB platform.

“…In some studies, the position sensor value of the motor is estimated using a sensor-less method and is compared with the actual sensor value for fault diagnosis and fault tolerance [6,7]. The current sensor value of the motor is estimated for fault diagnosis using the proportional–integral [8] and the sliding-mode [9,10] observers. In other studies, the parity equation was used to diagnose the faults in electric current and position sensors [11,12].…”

Section: Introductionmentioning

confidence: 99%

Integrated Fault Diagnosis Algorithm for Motor Sensors of In-Wheel Independent Drive Electric Vehicles

Jeon

Lee

2016

An integrated fault-diagnosis algorithm for a motor sensor of in-wheel independent drive electric vehicles is presented. This paper proposes a method that integrates the high- and low-level fault diagnoses to improve the robustness and performance of the system. For the high-level fault diagnosis of vehicle dynamics, a planar two-track non-linear model is first selected, and the longitudinal and lateral forces are calculated. To ensure redundancy of the system, correlation between the sensor and residual in the vehicle dynamics is analyzed to detect and separate the fault of the drive motor system of each wheel. To diagnose the motor system for low-level faults, the state equation of an interior permanent magnet synchronous motor is developed, and a parity equation is used to diagnose the fault of the electric current and position sensors. The validity of the high-level fault-diagnosis algorithm is verified using Carsim and Matlab/Simulink co-simulation. The low-level fault diagnosis is verified through Matlab/Simulink simulation and experiments. Finally, according to the residuals of the high- and low-level fault diagnoses, fault-detection flags are defined. On the basis of this information, an integrated fault-diagnosis strategy is proposed.