High-precision smooth speed regulation in permanent magnet synchronous motors (PMSMs) is challenged by torque ripple, parameter mismatches, and load fluctuations. Considering the uncertain nature of these disturbances, neural network (NN)-based methods provide superior applicability compared to internal model approaches due to their frequency-independent characteristics. However, most of these methods utilize feedforward NNs designed via asymptotic stability theory, which exhibit severe output distortions stemming from abrupt error surges and prolonged convergence times under varying operating conditions. To address these issues, this article proposes a robust speed control framework that integrates a recurrent NN (RNN) with fixed-time sliding-mode control (FTSMC), theoretically guaranteeing closed-loop fixed-time stability even under input saturation. Specifically, the RNN employs an internal recurrent loop to leverage historical context, thereby reducing the network output's susceptibility to instantaneous error spikes and alleviating transient distortions. Furthermore, incorporating FTSMC principles into the weight update law design accelerates the network's learning process, ensuring accurate approximation of periodic disturbances while shortening the transient period. Extensive experimental results validate the effectiveness of the proposed scheme across diverse operating scenarios.

Natural fault-tolerance performance is becoming popular for dual three-phase permanent magnet synchronous motors (PMSMs) under open-phase fault, as it eliminates the need for control structure reconfiguration and fault diagnosis. Unlike the current constraint imposed by the open-phase fault, little attention has been given to the voltage relationship between the inverter and the motor. In this paper, aiming to address the voltage disturbance by this constraint, an improved universal control scheme has been proposed for dual three-phase PMSM under single open-phase fault. The voltage disturbances have been modelled as dc-type and periodic-type, and then the low-passing filter plus resonator-based disturbance observer has been utilized in control scheme of torque subspace for improving disturbance rejection. The simulation and experimental results are presented to illustrate the effectiveness of the proposed method.

Fault-tolerant control (FTC) strategy can be realized without modifying the peripheral hardware circuit when the open-circuit fault (OCF) occurs in the multiphase motor. However, FTC relies on accurately identifying the fault location and switching to a new reconfiguration fault-tolerant algorithm. This can significantly increase the complexity of the system. To overcome the challenge, this article investigates a passive fault-tolerant scheme of a 2 × 3-phase surface-mounted permanent-magnet synchronous motor (SPMSM) driven by a mono-inverter when single-phase OCF occurs. The state equations based on field-oriented control of 2 × 3-phase SPMSM under healthy and single-phase OCF are discussed. The special motor drive mode and the constraint ofid= 0 make the phase currents of each module passively optimized under the two neutral point configurations (i.e., isolated or connected), thus meeting the demand of restraining torque ripple. In the proposed PFTS, when the OCF occurs, the system does not require to attempt to diagnose or correct faults. Hence, a seamless transition from normal to faulty operation is guaranteed. Moreover, it enhances system reliability and stability. Furthermore, taking an existing 2 × 3-phase SPMSM as an example, the experiments are carried out for validation.

The inverter nonlinearity induces current harmonics and mismatches between permanent magnet synchronous machine reference voltages and terminal voltages, which will degrade the sensorless drive system performance, especially at the low-speed range. In this paper, a radial basis function neural network (RBFNN)-based voltage compensator is proposed to suppress the current ripple. Without the requirement of any additional hardware or complex signal analysis procedure and processing algorithm, the RBFNN is self-tuned to directly generate the compensation voltage with the objective to minimize the current tracking error, so as to improve the active flux modeling accuracy and reduce position and speed estimation fluctuation.

Active disturbance rejection control (ADRC) is promising for permanent magnet synchronous machine (PMSM) speed regulation system. However, the control performance of ADRC scheme is generally affected by the measurement noise introduced by position sensors. To solve this problem, a high-order nonlinear extended stated observer (NESO) is proposed in this paper to directly estimate the motor speed. The bode diagrams of the high-order NESO based measurement noise suppression system obtained by frequency-sweep approach are illustrated to show its frequency domain characteristics. Taking full advantage of nonlinear control and high-order observer techniques, the proposed strategy can maintain satisfactory noise suppression performance without sacrificing the robustness of PMSM system. Comprehensive experimental results are conducted to verify the superior properties of the proposed control strategy.

The existing dead beat-direct torque and flux control under M-T framework (DB-DTFC-MT) strategy achieves fast dynamic response as well as robustness. But by nature, the DB control strategy only uses proportional control which is not able to eliminate the steady-state error when a disturbance happens. To be more specifically, one of the remaining issues in DB-DTFC-MT is when a disturbance caused by motor parameters variation happens, there will be an obvious steady-state error in the torque as well as flux control loops causing deterioration to the control performance. In this paper, active disturbance rejection control (ADRC) technique containing two extended state observers are adopted in DB-DTFC-MT strategy. The designed DB-ADRC strategy is able to estimate as well as compensate the disturbances resulting in the voltage vectors. Hence, the robustness of DB-DTFC-MT to motor parameters mismatch is further improved. The designed control scheme is verified on a real-time control platform in reliance on dSPACE MicroLabBox with a surface mounted permanent magnet synchronous motor.