This paper proposes a simple and effective method to reduce speed ripples of Permanent Magnet Synchronous Machines (PMSMs) at low speed working conditions. The treated issue is related to the periodic torque ripples which induce speed oscillations that deteriorate the drive performance. The main idea of the proposed method is to modify a conventional PMSM controller by superposing an appropriate compensation signal to the quadratic-current reference. The proposed approach allows to reduce speed ripples at low speed through a simple compensation signal and does not require a hard calculation cost. A theoretical analysis is presented, and both simulation and experimental results are presented to validate the proposed compensation method.

Operation at low speed and high torque can lead to the generation of strong ripples in the speed, which can deteriorate the system. To reduce the speed oscillations when operating a five-phase asynchronous motor at low speed, in this article, we propose a control method based on Gray Wolf optimization (GWO) algorithms to adjust the parameters of proportional–integral (PI) controllers. Proportional–integral controllers are commonly used in control systems to regulate the speed and current of a motor. The controller parameters, such as the integral gain and proportional gain, can be adjusted to improve the control performance. Specifically, reducing the integral gain can help reduce the oscillations at low speeds. The proportional–integral controller is insensitive to parametric variations; however, when we employ a GWO optimization strategy based on PI controller parameters, and when we choose gains wisely, the system becomes more reliable. The obtained results show that the hybrid control of the five-phase induction motor (IM) offers high performance in the permanent and transient states. In addition, with this proposed strategy controller, disturbances do not affect motor performance.

The integration of photovoltaic (PV) systems with the grid connected four-leg voltage source inverters (4LVSI) offers more efficient power conversion and distribution. However, the complexity of these higher-order systems presents significant control challenges due to the sensitive nature of both DC bus voltage and 4LVSI output currents, which introduce complex dynamic interactions within the 4LVSI control system and limit its overall control performance, particularly under system uncertainties and disturbances such as variations in irradiance, PV cell temperature, and grid voltage. To address these challenges, an enhanced active disturbance rejection control (EADRC) scheme based on a super-twisting sliding mode observer (STSMO) is designed for the outer DC bus voltage control loop. The STSMO is incorporated in the ADRC method for its fast uncertainties and external disturbances estimations, high resilience against uncertainties, and good immunity to measurement noise. The proposed STSMO-based ADRC approach effectively estimates and compensates for system uncertainties and external disturbances, thereby enhancing DC bus voltage dynamics and stability, improving resilience against uncertainties, increasing immunity to measurement noise, ensuring better steady-state accuracy of the DC bus voltage, and increasing system reliability while reducing cost and size. The effectiveness and superiority of the proposed control method for the PV grid-connected 4LVSI system are validated through both simulation and real-time studies using the OPAL-RT simulator. The results demonstrate robust performance under parameter uncertainties and disturbances, including variations in irradiance, PV cell temperature, DC bus capacitor value, and grid voltage sags.

This paper presents an enhanced sensorless control strategy for permanent magnet synchronous motors (PMSMs) by improving back-electromotive force (back-EMF) estimation and control robustness. An improved back-EMF extended state observer (ESO) is proposed, incorporating back-EMF differentiation to compensate for DC position error without requiring an increased observer bandwidth. Furthermore, an ESO-based quadrature phase-locked loop (QPLL) is developed to improve position tracking accuracy and enhance the robustness of the speed loop sliding mode controller (SMC) against unknown disturbances. To address parameter uncertainties in the back-EMF observer and current controller, a recursive least squares (RLSs) algorithm with an adaptive forgetting factor is introduced, providing a balance between adaptation speed and noise suppression. Simulation results validate the proposed approach, demonstrating improved estimation accuracy, disturbance rejection, and overall robustness in sensorless PMSM control.