In this study, a robust model-free nonsingular terminal sliding mode control (MFNTSMC) algorithm based on the ultra-local model is proposed to reduce the influence of permanent magnet (PM) demagnetization for permanent magnet synchronous motors (PMSMs). First, the PMSM mathematical model in normal and demagnetization is described, and the ultra-local model of speed loop and current loop is constructed based on the input and the output of PMSM vector control system. Then, the MFNTSMC method is proposed and adopted to design speed controller and d-q-axis current controller, and sliding mode observer (SMO) is designed to estimate the unknown terms of the ultra-local model. Finally, compared with the PI control method and Model-Free Control (MFC) method, the results of simulations and experimentations show that the MFNTSMC method can improve the dynamic response while maintaining robustness of PMSM driven system, reduce the dependence of the design of controller on the precise PMSM model, and has fault-tolerant control function for PM demagnetization fault.

A demagnetization fault not only degrades the performance of a permanent magnet synchronous motor (PMSM) drive system, but also may even cause the irreversible demagnetization. This article presents an improved-sliding-mode-observer (ISMO) based equivalent-input-disturbance (EID) method to reconstruct a demagnetization fault and to perform fault-tolerant control for the demagnetization fault in a PMSM drive system. The models of healthy and demagnetized PMSM are first established. Next, an ISMO is constructed by inserting a decoupling term. It completely removes the influence of the motor speed on the reconstruction of a demagnetization fault. Then, the ISMO-based EID approach is developed to reconstruct the fault with the high precision and maintain system control performance even for a demagnetization fault. The stability of the whole system is proved by using the concept of globally uniformly ultimately bounded. Finally, the validity of the method is demonstrated using hardware-in-the-loop simulation.

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.

To prevent irreversible demagnetization of a permanent magnet (PM) for interior permanent magnet synchronous motors (IPMSMs) by flux-weakening control, a robust PM flux-linkage nonsingular fast terminal-sliding-mode observer (NFTSMO) is proposed to detect demagnetization faults. First, the IPMSM mathematical model of demagnetization is presented. Second, the construction of the NFTSMO to estimate PM demagnetization faults in IPMSM is described, and a proof of observer stability is given. The fault decision criteria and fault-processing method are also presented. Finally, the proposed scheme was simulated using MATLAB/Simulink and implemented on the RT-LABplatform. A number of robustness tests have been carried out. The scheme shows good performance in spite of speed fluctuations, torque ripples and the uncertainties of stator resistance.