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.

This article presents an improved rotor position estimation method for a brushless electrically excited synchronous starter/generator (BESSG). Based on the multistage characteristics of BESSG, a high-frequency voltage is injected into the stator side of the main machine (MM), and the estimated rotor position is obtained through the estimation of excitation current. To suppress the estimated rotor position harmonic error caused by inverter nonlinearities, a novel phase-locked loop based on the gradient descent algorithm is proposed. In this method, the weight of harmonics is adjusted iteratively to improve the accuracy and reliability of the rotor position estimation. Experimental results have verified the feasibility of the proposed strategy.

The diagnosis and fault-tolerant control of open-phase faults in permanent magnet synchronous motor (PMSM) drive significantly rely on models describing post-fault behaviors of current and voltage. This paper aims to propose an improved current prediction model that can accurately estimate the post-fault current dynamics under the single open-phase fault. Firstly, in each switching state, the post-fault phase voltages are derived by considering the floating neutral voltage incurred by the back electromagnetic force (back-EMF). Furthermore, by incorporating the derived phase voltages as the activation sources in each switching cycle, the post-fault current prediction model is established. Moreover, the changes of inductances under the open-phase fault are taken into account by establishing the model in the independent phase model. Finally, experimental results validate the derived post-fault phase voltages and the post-fault current prediction model.

In order to improve robustness of permanent magnet synchronous motor (PMSM) servo system, a nonlinear generalized predictive control (NGPC) strategy based on extended state observer (ESO) is proposed. According to the NGPC theory, a NGPC controller is designed by using the continuous-time model of PMSM. In the case of the parameter variations and external load disturbance in the actual motor system, an ESO based on inverse hyperbolic sine function is introduced to estimate the total disturbance of the system and compensate dynamically in real time. The simulation results show that the proposed control strategy has good dynamic performance and strong robustness, providing an effective approach for engineering implementation.

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 state of charge (SOC) balancing control strategy for the modular multilevel converter (MMC) with integrated supercapacitor energy storage system (ISC-ESS). The equivalent model is derived by analyzing the behavioral characteristics between the SOC of the supercapacitors and ac-side output power. Moreover, the submodule (SM) capacitor voltage fluctuation suppression and energy management control strategy are put forward. The proposed control strategy enables the converter system to suppress SM capacitor voltage fluctuation during SC charging and discharging. A thorough simulation evaluation of the MMC with ISC-ESS has been conducted to validate the correctness and feasibility of the proposed solution.

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.

In order to improve the control performance of permanent magnet synchronous motor (PMSM)servo system, a non-smooth control strategy based on model compensation is proposed. According to the non-smooth theory and the disturbance analysis of the position loop, a non-smooth controller is designed to make the position error of the closed-loop system converges into a small region in finite time. The model identification compensation technology is combined with the nonsmooth control strategy. Partially model of the PMSM is identified and is employed to compensate disturbance partially to improve the accuracy of the disturbance estimation. The simulation and experimental results show that the proposed control strategy not only has a faster convergence speed of the position error, but also has stronger anti-disturbance ability.

Nowadays distribution power systems are used in different applications such as aircraft, ships, submarines and hybrid electric vehicles. However, the interaction between individually designed power subsystems may cause instability. Moreover, in these applications, the constant power load (CPL) also poses challenges for system dynamic response and stability. Thus, the main objective is to stabilize the cascaded system supplying the CPL. An interconnection and damping assignment (IDA) passivity-based control (PBC) scheme for LC filter cascaded with buck converter supplying CPL is proposed. The plant is described by port-controlled Hamiltonian (PCH) form. Particularly, an adaptive interconnection matrix is developed to achieve internal links in PCH system. A modified IDA-PBC and its proof are presented to perfect the implementation for the CPL application. Simulation results are given to illustrate the effectiveness of the proposed approach.

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.

It is well know that the interaction between poorly damped LC input filter with dc-dc converter lead to degradation of dynamic performance and fault scenario of the system. This problem also often occurs in fuel cell systems. Due to the relatively low and unregulated output voltage, the high gain boost converter is need in such application. A floating interleaved boost converter (FIBC) is selected as a good candidate to achieve this desired effect. In order to ensure the system stability, this paper addresses a method which permits to design a fault-tolerant stabilizing system for the proposed converter and the filter. It consists in implementing an active stabilizer for each switch. Afterward, a method to design fault-tolerant stabilizing system is developed. The simulation results are reported to verify the effectiveness of the proposed method.

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.

An optimized state of charge (SOC) estimation method is critical for energy control strategy in hybrid energy system. For an embedded system, the executed algorithm should be less time consuming and also robust on measurement noise from sensors. Moreover, the estimation method should also be insensitive to initial SOC for the purpose of avoiding battery relaxing time in real application. The proposed method in this paper combines adaptive unscented Kalman filter (AUKF) and multivariate adaptive regression splines (MARS) to meet the above demands of embedded hybrid energy system. Samples which consist of battery current, terminal voltage and temperature are used to for MARS model training. The effectiveness and robustness of the proposed method is validated by experimental test. Also, the proposed method is compared with least squares support vector machine (LSSVM) based method in estimated accuracy and time consumption. Experiment results indicate that the proposed method is less time consuming as well as good accuracy is guaranteed.