This study studies a double-surface sliding-mode observer (DS-SMO) for estimating the flux and speed of induction motors (IMs). The SMO equations are based on an IM model in the stationary reference frame. The DS-SMO is developed based on the equations of a single-surface SMO (SS-SMO) of IM. In DS-SMO method, the observer is designed through combining sliding variables produced by combining estimated fluxes of currents error. The speed is easily determined based on the pass of switching signal through a low-pass filter. Also, an optimal DS-SMO (ODS-SMO) is proposed to improve the transient condition by optimally tuning the observer parameters. To optimise these parameters, the particle swarm optimisation method is adopted. Moreover, an improved DS-SMO (IDS-SMO) is proposed to improve both transient and steady-state conditions, torque ripple and total harmonic distortion. Moreover, the proposed IDS-SMO has a stable performance under sudden load change and the low-speed region. Finally, the accuracy of the proposed ODS-SMO and IDS-SMO methods is substantiated through simulation and experimental results.
This study presents a combined vector and direct torque control (CVDTC) for surface‐mounted permanent magnet synchronous motor (SM‐PMSM). The CVDTC method has a fast dynamic torque response without requiring any conventional PWM signal‐generators. Besides, it provides low‐speed control and standstill operation, torque and flux ripple reduction, minor switching frequency variations, and low computational burden. In this study, CVDTC is mathematically analysed in the stator flux reference frame and then both DTC and CVDTC are simulated and compared for SM‐PMSMs. To further reduce torque and flux ripple, model predictive combined vector and direct torque control (MPCVDTC) with the finite control set is analysed and proposed in the stator flux reference frame. Moreover, maximum torque per ampere (MTPA) and constant stator flux magnitude analysis for SM‐PMSM are explored in the stator flux reference frame. Simulation and experimental results substantiate the effectiveness and performance of the CVDTC and MPCVDTC methods over a vast speed range.
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