Dual-grounded single-phase inverters (DGSPIs) are widely used in photovoltaic (PV) power systems because of no common-mode leakage current (CMLC). However, the traditional topology derivation method of the DGSPIs based on graph theory is complex. Therefore, a topology derivation method for DGSPIs based on adjacency matrices is proposed. The topologies of the DGSPIs can be derived by determining the characteristics of the dual-grounded topology and inserting switches, capacitors, and inductors into the adjacency matrices. In addition, the voltage gain of the derived topology can be calculated based on the switching logic and the adjacency matrices. Finally, the topologies of the DGSPIs can be drawn by the adjacency matrices with inverter capability. Thus, it is easy to deduce the topologies by the mathematical and programming software. The topologies with three nodes, two switches, one capacitor, and two inductors are taken as an example to illustrate the derivation method. Operating principle of one deduced topology is elaborated. Experimental results verify the theoretical analysis.

Existing fault diagnosis techniques for interturn short circuits (ITSCs) in switched reluctance motors (SRMs) still face several challenges, including limited accuracy and sensitivity, compatibility with different control strategies, and dependence on operating speed and load. This article introduces a novel fault diagnosis technique for the ITSCs in SRMs using the extracted faulty inductance data over the minimum inductance zone (MIZ) using the superposition principle. First, it provides a detailed analysis for the magnetic circuit of SRM considering ITSCs. Second, it introduces the superposition principle to accurately extract the faulty inductance component of faulty coil/pole. Third, it deduces the mathematical formulation to relate the faulty and healthy component of inductances along with their active number of turns. Fourth, in order to improve the accuracy and sensitivity, it defines the proper calculation window (CW) over the MIZ considering the switching angles and the threshold current level. Finally, the experimental results show a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">maximum</i> reported error of 1.05% over the entire speed range and different fault ratios (0% to 25%) that confirms the high accuracy and high sensitivity for the proposed technique. In addition, the proposed technique features a simple structure; is completely independent of speed, load, and control algorithm; offers a powerful tool for several industrial applications including electric vehicles (EVs).

Eddy-current sensor-free control based on reusing Hall sensors of a bearingless slice motor system can reduce the volume, cost, weight, and the impact of shear on transmitted liquid. However, the algorithm will fail in the presence of the PM’s third harmonic. Hence, this article presents the eddy-current sensor-free control algorithm based on the two negative sequence coordinate transformation in parallel with different frequencies (TNSPDF). The random and disordered signal in the Hall output is modulated into asymmetrical component about the displacement vector angle through negative sequence coordinate transformation at different electrical frequencies, achieving decoupling between the displacement vector angle and the motor electrical frequency. The interference signal does not lead to any pulsation in the estimated displacement; rather, it evolves into a significant coefficient for the purpose of displacement identification. The validity and effectiveness of the proposed method are verified through experiments on a bearingless permanent magnet slice motor system.

In virtual synchronous generator (VSG) systems, positive and negative sequence compound control in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i>–<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> axis rotating coordinate system is a mainstream approach for low-voltage ride-through (LVRT) due to its effective suppression capability of unbalanced components. However, the time delay caused by sequence decomposition leads to serious transient overcurrent during voltage sag/recovery. To solve this issue, this article analyzes the characteristics of three-phase voltage equivalent amplitude <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">u_gm </i> under various voltage sag conditions, and proposes a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">u_gm </i>-based rapid fault diagnosis method to distinguish symmetrical and asymmetrical sag faults. Based on the theoretical analysis, an adaptive LVRT control strategy was proposed. Specifically, the strategy determines whether to introduce positive–negative sequence decomposition at the appropriate time point, which significantly mitigates the delay influences caused by sequence decomposition during voltage sag and recovery. Ultimately, this smooths the transient response of the VSGs grid-side current. Finally, the correctness and effectiveness of the control strategy are experimentally verified.

The soft open point (SOP) can improve the dynamic regulation capability of distribution networks and mitigate the adverse impacts of distributed generations (DGs). The back-to-back (B2B) link of voltage source converters has been regarded as the sole SOP topology for a long time, but the high cost hinders the application of SOPs and the upgradation of distribution grids. Some new topologies, such as the solid-state transformers (SSTs) with serial shunt structures, have been discussed as alternative SOP solutions recently. In this work, a cost-effective solution of the SOP based on the hybrid transformer (HT) is proposed. The combination control of the HT, including voltage coordination and power regulation, is analyzed for stable operation under steady and dynamic conditions. The performance is also investigated and compared with that of the B2B and SST schemes. The total converter capacity of the HT-based SOP is highly reduced. It is only sixteen percent of that of the B2B scheme and twenty-eight percent of that of the SST scheme. Efficiency can also be enhanced by 2.7% and 0.9%, respectively. Simulations and experiments have been completed to verify the effectiveness of the proposed solution.

With the rapid development of artificial intelligence technology and Internet of Things technology, cyber–physical systems (CPSs) have also been fully developed, which promotes the widespread use of CPS in a variety of areas and brings many new opportunities and challenges. This article considers the consistent identification of finite impulse response (FIR) systems with multilevel quantized observations subjected to data tampering attacks. First, a defense algorithm based on known parameters is designed for the case where the attack is known. Second, on the basis of the algorithm with known attack, a joint consistent estimation approach is proposed for estimating system parameters, and the convergence and asymptotic normality of the algorithm are proved. Then, according to the asymptotic normality of the algorithm, the trace of the defense algorithm’s asymptotic error covariance matrix is used as the defense index to establish the optimal defense model. Finally, the effectiveness of the defense strategy is verified through experiments.

Fault-tolerant control (FTC) is essential for maintaining the stability of uncrewed aerial vehicles (UAVs). Quadrotors can maintain stability during rotor failure via sacrificing yaw control. However, hybrid UAVs, such as lifting-wing quadrotors, generate substantial aerodynamic forces at high speeds, making it difficult to directly apply the fault-tolerance strategies existing for quadrotors. This article proposes a control approach that leverages aerodynamic forces from the wings to compensate for the thrust and moment losses caused by rotor failure, enabling the aircraft to maintain nondegraded flight. First, the theoretical feasibility of this strategy is assessed through controllability analysis. Based on this analysis, a passive fault-tolerant controller is developed that permits normal operation under unknown failure conditions. Additionally, the controller can handle different aileron malfunctions. Furthermore, the closed-loop stability of the attitude system under the proposed controller is analyzed and verified. In order to evaluate the effectiveness of the proposed approach, the controller is first tested in a model-in-the-loop (MIL) simulation to assess its response under different failure conditions. Subsequently, real-world flight tests using onboard sensors and GPS are performed to verify the performance of the proposed controller in practical operational environments.

The motion reproduction system (MRS) transfers human dexterous motion skills to robots. Compared with other machine learning-based methods, it has an advantage in terms of the number of data points and hyperparameters. However, it may fail when the actual object of motion differs from that of acquired human motion. Conventional studies consider human stiffness, which characterizes the intention of human motion. Although they performed better than the original MRS with variable objects, they estimated human impedance using linear interpolation. Linear interpolation is insufficient for generating novel, human-like motions that are nonlinear and time-variant. In this article, more sophisticated motions were generated by fitting the relationship between environmental stiffness and position, velocity, and force nonlinearly using Gaussian process regression, which requires a smaller amount of data compared to machine learning-based schemes. Through experiments, the data number and error reduction between the true human motion and actual motion were confirmed by comparing the original and conventional MRS and the imitation learning. Therefore, the proposed method can generate motion for variable objects more precisely with a small amount of human motion data.

This article presents an adaptive ridge regression (ARR)-based data-driven current prediction model aimed at enhancing robustness in permanent magnet synchronous motor (PMSM) drives. Although least squares (LS) methods have displayed certain potential for improving parameter robustness in model predictive control (MPC) applications, the influence of the inevitable data noises has not been fully considered in such a data-based method. Aiming to improve the robustness against data noises, an adaptive ridge regression (ARR) data-driven current prediction is proposed for permanent magnet synchronous machine (PMSM) drives in this article. The proposed method introduces an online evaluation of data noise severity through a variance inflation factor (VIF). A dynamic ridge coefficient adjustment mechanism according to the VIF is then applied. As a result, an adaptive penalization to the data noises is achieved, leading to an improved robustness. Experimental verification on a PMSM drive system shows improvements compared to conventional LS methods, especially under challenging low-speed operating conditions where noise sensitivity is most evident. The proposed ARR method preserves the parameter-independent benefits of data-driven approaches while achieving superior current prediction accuracy in noisy settings, thereby advancing the practical implementation of robust MPC strategies for PMSM drives.

This article introduces a novel high-efficiency single-stage power factor corrector (PFC) converter for wide input voltage range applications. The proposed converter features an asymmetrical half-bridge flyback (AHBF) configuration and a feedforward branch. The feedforward branch connects to a tapped transformer via an inductor, enabling effective shaping of the input current and reduction of the dc bus voltage. The transformer excitation inductor is optimized to operate in boundary conduction mode (BCM), which minimizes switching losses. In contrast, the feedforward inductor is designed to function in discontinuous conduction mode (DCM) or BCM to enhance overall system efficiency and improve the power factor. The design considerations for the feedforward inductor, excitation inductor, and transformer tap positioning are presented in detail. Finally, a 100 W prototype with 90–264 V ac input and 20 V/5 A output is designed to verify the theoretical analysis. Experimental results show that the proposed converter can achieve high efficiency throughout the entire input voltage range, with a peak efficiency of 95.12%, while meeting the IEC 61000-3-2 Class D standard.