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In this paper, 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 PM 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 the PMSM vector control system. Then, the MFNTSMC method is proposed and adopted to design the speed controller and d-q-axis current controller, and the sliding-mode observer is designed to estimate the unknown terms of the ultra-local model. Finally, compared with the PI control method and model-free control 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. INDEX TERMS Ultra-local model, permanent magnet synchronous motor (PMSM), demagnetization, model-free nonsingular terminal sliding mode control (MFNTSMC), sliding mode observer (SMO).

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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.