The performance of the permanent magnet synchronous motor (PMSM) sensorless control system is limited in the case of the low carrier ratio such as high-power transmission systems. This work analyzes the main factors that cause system delay under low carrier ratio. A linear current prediction method base on volt-second equilibrium principle is proposed to solve the sampling filter and inverter nonlinear delay. Meanwhile, a self-adjustive position compensation is obtained through a PI controller based on the$dq$-axis voltage error to further suppress the digital control delay. On this basis, a sensorless field oriented control system is built based on a model reference adaptive system. Finally, a 1.5-kW SPMSM is tested to verify the feasibility of the proposed method.

The paper researches on the phase current reconstruction technology of a common DC bus type open-end winding permanent magnet synchronous machine system, and proposes a method to reduce the immmeasurable regions of the medium vector modulation method by alternating the medium voltage vectors. Based on the medium vector modulation method, the paper synthesizes the reference vector by alternating the medium voltage vector with the same effect and using the large voltage vector as an auxiliary to obtain sufficient DC bus sampling time for the control system in the immeasurable regions. The proposed method not only does not increase the additional times of switch, but also adopts a symmetrical modulation method. The method can be implemented based on triangular carriers, which is very convenient for its practical application in digital controllers. By using the method proposed in the paper, the reconstruction of three-phase currents is achieved and the zero sequence current is obtained. Finally, the effectiveness of the method proposed is verified through simulation, further improving the reliability of the system.

The accurate speed control is significant for PMSM in aircraft flap-slat elctromechanical actuator, which serves as the key motion unit of aircraft high-lift system. However, the speed controller suffers from internal and external periodical disturbances due to current sampling and scaling errors and aerodynamic load. The periodical disturbance estimation in extended state observer is done by a proportional resonant scheme to enhance the disturbance rejection ability of speed control loop [1]. This paper proposes an adaptive sinusoidal frequency observer(ASFO)to expand the applicability of proportional resonant-based active disturbance rejection control(PRADRC) technique to applications where periodic and aperiodic disturbances exist. The resonant frequency is adaptively estimated through the ASFO whose input is the speed tracking error. The performance analysis of proposed method is proved theoretically and then validated by experiments.

In rail transit application, the performance of the permanent magnet synchronous motor (PMSM) sensorless control system is limited by the low switching frequency. In this case, the time-delay of system is becoming more significant and degrades the control performance. To solve the problem, a time-delay compensation method based on high frequency (HF) square-wave voltage injection strategy is proposed in this paper. Firstly, a series time-delay filter is used to extract the HF response current, which can improve the signal-to-noise ratio. Then, a zero-order holder is used to obtain the HF current envelope containing rotor position information. The rotor speed and position are estimated by a Luenberger observer. For the time-delay compensation, the feedback current in a-β coordinates is utilized to calculate the estimated delay angle error. It serves as the input of a PI controller, through which the estimated delay angle can be acquired. And then, the estimated delay angle is compensated to the actual system. Simulations verified the effectiveness of the proposed method.

This paper proposes a field programmable gate array (FPGA) implementation of predictive speed and current control of permanent magnet synchronous motor (PMSM) with two-time-scale optimization. Considering the time-scale characteristics of speed loop and current loop, different sampling times are assigned to the subsystems. The predictions of both slow and fast models consuming great computation resource for all the prediction instants are analyzed in two-time-scale system. In order to achieve a fast and accurate predictive control, the proposed method is implemented on an FPGA. Parallel unrolling and maximized parallel pipeline architecture are designed specifically to optimize the computational time of the proposed method. Experimental results validated in PMSM drives illustrate that proposed implementation achieves a high performance with balanced resource consumption.

The internal model control (IMC) has been widely used for its simple structure, but its control performance has a relationship with the filter order and time constant directly, so that its disturbance rejection performance is influenced in the permanent magnet synchronous motor (PMSM) drive system. An IMC with extended state observer (ESO) is proposed in this paper. Based on the mechanism of IMC and the mathematical model of PMSM, the first order and second order internal model controllers are designed. Then, the design method of dynamic compensation using ESO for PMSM is presented, and the novel internal model controller with ESO is realized. Simulation and experimental results show that the proposed control strategy can reduce the influence of external torque disturbance and moment of inertia variation on the performance of the system. And the effectiveness of IMC with ESO is verified.

Sensorless ac drives have been widely adopted in many industry applications. However, the characteristic of strong multiple saliencies is still a main drawback impeding applying sensorless control over several types of machine, e.g., surface-mounted permanent magnet synchronous machine with concentrated windings (cwSPMSM). This work proposes a novel secondary saliency tracking (SST) algorithm to implement the sensorless control exclusively for such machines at low speed range. The saliency signals of a typical cwSPMSM under consideration are experimentally investigated. The stator background and physical mechanism of its strong multiple saliencies are explained in detail. Instead of processing the primary saliency signal, secondary saliency signal that has a better signal to noise ratio and more precise resolution is processed by a specially designed bandpass filter, and an adaptive notch filter for speed and rotor position estimation. Finally, the effectiveness and accuracy of the newly proposed SST method are verified by experimental results.

Surface-mounted permanent magnet synchronous machine with concentrated windings (cwSPMSM) is widely adopted in many industry applications. However, strong multiple saliencies is a main drawback impeding applying sensorless control over this type of machine. This work proposes a hybrid sensorless control scheme which integrates a novel Secondary Saliency Tracking (SST) algorithm and an improved Active Flux Observer (AFO) for cwSPMSMs. The saliency signals of a typical cwPMSM under consideration are experimentally investigated. Instead of processing the primary saliency signal, secondary saliency signal which has a better signal to noise ratio and more precise resolution, is processed by a special designed band pass filter for speed and rotor position estimation reaching a very low speed range with full-load. An improved AFO method with robust structure but effective performance is adopted for higher speed range estimation. The transient phase (switching between the SST and AFO) performance is guaranteed by a smooth transition region design, reaching a Hybrid Sensorless Control with wide speed range. Finally the effectiveness and accuracy of the newly proposed Hybrid Sensorless Control method are both verified by experimental results.

Direct Model Predictive Control (DMPC) is an attractive control method for power electronics and drives, characterized by straightforward concept, nice dynamics and great flexibility. However, relatively big ripples of the control variables and heavy computational efforts are regarded as two of the shortcomings. To cope with these, this work proposes a performance-enhanced DMPC concept with multi-predictions and lower computational efforts. The novelty of the proposed scheme is two-folds: i) By dividing each sampling interval into 3 prediction periods, the resolution of the control accuracy is therefore improved compared with the classical DMPC schemes with the same sampling period; ii) Instead of using the exhausting enumeration concept, a deadbeat notion is in-cooperated to find the equivalently optimal vectors and much lower computational efforts are therefore required. As a case of study it is here verified on a grid-tied two level Active-Front-End (AFE) and is realized using an entirely FPGA based solution. Compared with the classical DMPC schemes, better current/power qualities are achieved with the same sampling frequency. The effectiveness of the proposed scheme is emphasized with experimental results.

An encoderless predictive torque control (PTC) is proposed in this paper. By using a rotor flux model reference adaptive system (MRAS) estimation method to PTC, the system has the virtue of low cost due to the absence of PWM and speed measurement components. PTC requires not only estimated speed but also estimated stator and rotor flux. In implementation, a compensated MRAS is considered for obtaining good flux estimations. The experimental results confirm that this control strategy has very fast dynamics, can adapt a very wide speed range, and shows good performance both at transient and steady states.