In this article, an observer-based prescribed performance speed control method is proposed for permanent magnet synchronous motors. A transformed speed error is introduced and a suitable controller is designed to make it converge to zero, while guaranteeing the original speed error evolves strictly within a prescribed region. The controller is designed based on a backstepping approach. A linear extended state observer is applied to estimate and feed forward the external constant load disturbance to improve robustness. A data-driven radial-basis function neural network is proposed to approximate the nonlinear dynamic caused by parameter uncertainties and periodic-changing disturbance by deploying real-time and historical data. The stability analysis is based on Lyapunov's control theory. Experimental results verify the effectiveness and advantages of the proposed control scheme.

This article proposed a robust model predictive control (MPC) for permanent magnet synchronous motors taking into account the effect of disturbance. A structure cascading extended Kalman filter (EKF) and linear extended state observer (LESO) are used to estimate the position of the motor without using encoders. First, the voltage vector reference containing information of the system speed and current is predicted using the deadbeat control. Meanwhile, the ultralocal model of the system is built considering the lumped disturbance of the motor. The disturbed part of the ultralocal model is updated online according to the information of voltage and current in the past two moments. Then, a cascaded EKF-LESO is designed to efficiently estimate position and speed, taking into account disturbances such as measurement noise and model parameter uncertainty. Experimental results verify the effectiveness and advantages of the proposed method.

This paper proposes a novel integral sliding mode (ISM)-based model predictive current control (MPCC) strategy with low computational amount for three-level neutral-point-clamped (3L-NPC) inverter-fed PMSM drives. For conventional MPCC for 3L-NPC inverter, 27 voltage vectors are evaluated for prediction and calculation in each control cycle, therefore computational burden is a major hurdle for practical implementation of MPCC. With only calculation of reference voltage and determination of its sector position, a revised MPCC strategy with neutral point potential (NPP) balancing is proposed, which not only dramatically reduces the number of candidate voltage vectors involved in cost function calculation but also effectively suppresses NPP fluctuation of 3L-NPC inverter. To enhance MPCC robustness against motor parameter variations, the integral sliding mode (ISM) is embedded into MPCC for PMSM drives by enforcing sliding mode throughout the entire system response, and thus a novel ISM-based MPCC strategy is put forward. Furthermore, its robust stability is analyzed. The results of simulation experiments confirm that the proposed ISM-based MPCC strategy with NPP balancing for 3L-NPC inverter can enable PMSM drive system to have satisfactory control performance and strong robustness against motor parameter variations.

To enhance the position tracking performance of permanent magnet synchronous motors (PMSMs) under unknown disturbances, this article proposes a fast fixed-time control strategy based on an improved nonlinear extended state observer (NESO). First, load disturbances and nonlinear friction are considered as lumped disturbance, for which an NESO is designed to estimate the lumped disturbance. The control parameters of the NESO are tuned online using a neural network optimization algorithm, eliminating the need for offline training. Then, a robust fixed-time sliding mode control method is proposed, based on an improved nonsingular fast terminal sliding mode manifold, which offers better convergence performance. The Lyapunov method is used to prove the fixed-time stability of the position tracking error system. Finally, the effectiveness of the proposed method is validated on an experimental platform with PMSMs, and it is compared with other advanced fixed-time position control methods. The comparison results confirm that the proposed method exhibits superior control performance.

This article proposes an improved deadbeat predictive current control (DPCC) method and an adaptive fixed-time speed controller to enhance the current and speed tracking performance of permanent magnet synchronous motors. First, a theoretical analysis is conducted to examine the limitations of conventional DPCC in maintaining control accuracy under conditions of parameter mismatches. To address this, a fixed-time disturbance observer is designed to estimate and compensate for lumped disturbance caused by motor parameter mismatches and unknown dynamic uncertainties. Then, an adaptive fixed-time sliding mode speed controller is proposed. This controller employs a second-order integral sliding manifold, which reduces system chattering. Moreover, the designed adaptive law does not require prior knowledge of disturbance bounds, thereby reducing the over-conservatism of the controller. The stability of the system is demonstrated through Lyapunov’s stability theorem. Finally, experimental results validate the effectiveness and superiority of the proposed method, demonstrating enhanced robustness, reduced overshoot, and shorter response times.

To enhance the anti-disturbance performance and dynamic response capability of permanent magnet synchronous motors (PMSMs) under sensorless conditions, this article proposes a sensorless robust control scheme that integrates an adaptive fixed-time sliding mode speed controller with an improved back electromotive force (EMF) observer and a variable-gain extended state observer (VGESO). First, an improved back EMF observer is designed based on a high-order sliding mode algorithm, effectively suppressing chattering and enhancing estimation accuracy at lower speeds. On this basis, VGESO is constructed to estimate rotor position and speed information, eliminating the phase-locked loop (PLL) structure and improving the system’s dynamic response. Then, an adaptive fixed-time sliding mode speed controller is proposed, whose convergence time is independent of the system’s initial conditions, thereby enhancing convergence performance. In addition, by incorporating the proposed adaptive law, the assumption of a known upper bound on unknown disturbances is eliminated, reducing the conservatism in controller design. The stability of the system is demonstrated through Lyapunov’s stability theorem. Finally, the experimental results demonstrate that the proposed control scheme significantly enhances the system’s robustness while concurrently improving its dynamic response.