Aperiodic and periodic disturbances in the current loop adversely affect the dynamic performance and steady-state accuracy of the permanent magnet synchronous motor (PMSM). Meanwhile, existing active disturbance rejection control (ADRC) methods face the challenge of coupled tracking performance and disturbance suppression performance, which restricts the improvement of the overall performance of the system. To address these issues, an enhanced ADRC with a improved extended state observer (IESO) is proposed. In the proposed IESO, an error-derivative compensation term is incorporated into the disturbance observation loop, which effectively eliminates gain overflow and significantly improves the estimation capability for aperiodic and low-frequency periodic disturbances. Moreover, the observer integrates a resonant internal model structure, enabling accurate estimation of periodic disturbances while effectively eliminating unexpected peaks. Based on this, the enhanced ADRC can effectively suppress both aperiodic and periodic disturbances while achieving complete decoupling between tracking performance and disturbance rejection performance. Additionally, a comprehensive performance analysis of the proposed scheme is conducted. Finally, the effectiveness and feasibility of the proposed scheme are validated on the PMSM experimental platform.

Under complex operating conditions, permanent magnet synchronous motor (PMSM) drive systems are subject to uncertain aperiodic and periodic disturbances, which degrade speed control performance. To address this issue, this article proposes an enhanced active disturbance rejection control (ADRC) method. First, the limitations of conventional linear ADRC and its existing improvements in disturbance rejection are analyzed. Based on this, an error corrected cascaded extended state observer (EC-CESO) is proposed. Compared with traditional CESO, EC-CESO provides greater flexibility in zero placement, which enhances its ability to suppress aperiodic disturbances while reducing sensitivity to high-frequency noise. Second, an error-transformed adaptive radial basis function neural network (ET-ARBFNN) is designed to compensate for the shortcomings of EC-CESO against periodic harmonics. Unlike internal model principle-based resonant control, ET-ARBFNN requires no prior harmonic order information while achieving a significantly enhanced dynamic response. Furthermore, the disturbance rejection performance and stability of the proposed enhanced ADRC combining EC-CESO and ET-ARBFNN are analyzed. Finally, the effectiveness and superiority of the proposed method are experimentally validated on a PMSM platform.

Piezo-driven fast steering mirrors (PFSMs) are widely employed in high-precision beam steering and accurate tracking applications. However, the inherent hysteresis nonlinearity of piezoelectric actuators significantly degrades tracking accuracy. To address the challenges posed by dynamic hysteresis nonlinearity, this study proposes an improved non-singular fast terminal sliding mode control strategy. The proposed method integrates a non-singular fast terminal sliding surface and introduces an adaptive function in the reaching law to enhance response speed and improve control robustness. Additionally, the strategy incorporates an extended state observer (ESO) and an inverse model-based feedforward compensation mechanism. Specifically, the feedforward compensation based on the inverse model aims to offset hysteresis effects, while the ESO provides a real-time estimation of the total system disturbance to mitigate the impact of external disturbances and unmodeled hysteresis. Experimental results demonstrate that the proposed method effectively compensates for the hysteresis nonlinearity of PFSMs, improves disturbance rejection performance, and enhances position control accuracy.

When suppressing both aperiodic and periodic disturbances in surface-mounted permanent magnet synchronous motor (SPMSM), the traditional method based on a two-degree-of-freedom (TDOF) parallel quasi-resonant controller suffers from inherent coupling issues. These include coupling between tracking and anti-disturbance performance, as well as coupling between the aperiodic and periodic disturbance suppression loops. To address these issues, a novel TDOF structure is proposed based on the SPMSM discrete-time complex vector model, incorporating an enhanced resonant controller. This design effectively eliminates undesired peaks caused by coupling without requiring complex parameter tuning. Theoretical analysis shows that the proposed method achieves improved stability, enhanced aperiodic and periodic disturbance suppression performance, and greater robustness to parameter mismatches. Experimental results further validate the effectiveness of the approach in all these aspects.

Under complex operating conditions, deadbeat predictive current control (DPCC) is susceptible to multisource disturbances, including periodic and aperiodic components, which degrade the current control accuracy. To address this issue, a DPCC strategy based on a complex vector disturbance observer (CVDO) is proposed for the current loop of permanent magnet synchronous motor (PMSM) drives. First, the structure of the CVDO is developed from the PMSM mathematical model, and its sensitivity function is derived. On this basis, the CVDO is designed in the frequency domain to achieve precise estimation of multisource disturbances. Distinct from existing observers with embedded resonant structures, the proposed CVDO is designed directly from the perspective of frequency-domain response. This approach achieves ideal frequency-domain characteristics and facilitates stability analysis. Benefiting from a unique multiband synergistic architecture, the proposed method not only achieves the accurate separation and extraction of positive- and negative-sequence harmonics as well as aperiodic disturbances, but also effectively overcomes the disturbance amplification problem inherent in existing methods. Significantly, this architecture allows for the independent adjustment of disturbance estimation across different frequency bands, thereby enabling the independent optimization of observation performance for each band. Thus, this enhances the degrees of freedom in parameter tuning and improves design flexibility. Furthermore, the estimation performance and stability of the observer are analyzed theoretically. Finally, the effectiveness and advantages of the proposed method are validated on a PMSM platform.

To enhance the control performance of surface-mount permanent magnet synchronous motor (SPMSM) under low switching-to-fundamental frequency ratios (SFRs), an improved discrete-time current regulator (IDCR) is proposed in this brief. The regulator naturally aligns with digital implementation, effectively avoiding performance degradation due to discretization. The designed feedback controller allows arbitrary placement of system poles and eliminates speed-dependent phase terms, ensuring a constant critically damped characteristic. Furthermore, the IDCR achieves precise orthogonal decoupling and, separately, does not require complex predictive computation. The proposed method significantly improves current control performance under low SFRs conditions, and experimental results further verify its effectiveness and superiority.