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An isolated matrix rectifier is promising as it can provide galvanic isolation and maintain high power density due to the high-frequency link when compared with dc link in voltage source converter based solutions. To increase power rating or extend the output dc voltage range, this article proposes the input-parallel–output-parallel (IPOP) and input-parallel–output-series (IPOS) modular structures. These modular structures can achieve favorable features such as modularity and scalability without circulating current issues. To facilitate the operation of an IPOS- or IPOP-connected isolated matrix rectifier, this article proposes a carrier-based modulation strategy. Compared to space vector modulation methods, the proposed carrier-based modulation strategy is preferable due to the low complexity even under a high number of modules. The proposed modulation method can well compensate for the duty cycle loss to reduce current harmonics. Compared to conventional modulation methods, the narrow pulse is reduced to achieve high current quality even at a low modulation index. Moreover, the common-mode voltage is reduced by 50%. Simulation and experimental results are provided to validate the feasibility and performance of the proposed carrier-based modulation method. [ABSTRACT FROM AUTHOR]

This article investigates observability/controllability of a networked dynamic system (NDS) in which system matrices of its subsystems are expressed through linear fractional transformations (LFTs). Some relations have been obtained between this NDS and descriptor systems about their observability/controllability. A necessary and sufficient condition is established with the associated matrices depending affinely on subsystem parameters/connections. An attractive property of this condition is that all the required calculations are performed independently on each individual subsystem. Except well posedness, not any other conditions are asked for subsystem parameters/connections. This is in sharp contrast to recent results on structural observability/controllability, which is proven to be NP-hard. Some characteristics are established for a subsystem that are helpful in constructing an observable/controllable NDS. It has been made clear that subsystems with an input matrix of full column rank are helpful in constructing an observable NDS while subsystems with an output matrix of full row rank are helpful in constructing a controllable NDS. These results are extended to an NDS with descriptor form subsystems. As a byproduct, the full normal rank condition of previous works on network observability/controllability has been completely removed. On the other hand, satisfaction of this condition is shown to be appreciative in building an observable/controllability NDS. [ABSTRACT FROM AUTHOR]

This brief proposes an effective implementation for addressing permutation ambiguity issue of convolutive blind source separation in frequency domain. Generally, signal envelope and power ratio as common inter-frequency dependence measures are utilized to group bin-wise separated signals for convolutive mixtures, where the new measure of permutation alignment method is represented by the activation matrix of bin-wise spectrum which is based on nonnegative matrix factorization (NMF). Meanwhile, canonical correlation analysis (CCA) rather than the maximum sum of correlation coefficient among different bins, is applied for verifying correlation determinations. In addition, the influence of bin distance and separation quality at each bin are explored to optimize permutation result. Simulation results demonstrate the effectiveness of the proposed technique in real recorded convolutive mixtures. [ABSTRACT FROM AUTHOR]

The Ledley solution method is applied to analysis and control design of output trackability of Boolean control networks (BCNs) in this brief. By constructing the maximal control invariant set with respect to a defined state set, the output tracking problem is converted into a set stabilization problem and a corresponding condition for verifying solvability is obtained. Then an effective algorithm is provided to design the optimal state feedback controllers. Finally, we give an illustrated example. [ABSTRACT FROM AUTHOR]

This article, for the first time, extends the zeroing neural network (ZNN) method to address the problem of dynamic quaternion-valued matrix inversion. Due to the noncommutative property of quaternion multiplication, the complex representation method is first adopted to transform quaternion-valued matrices into the corresponding complex-valued matrices. Then, based on two kinds of ways to deal with nonlinear activation functions in the complex-valued domain, this article proposes two quaternion-valued ZNN (QVZNN) models for dynamic quaternion-valued matrix inversion. In addition, a novel nonlinear activation function is given to accelerate the convergence rate of the models to reach the predefined-time convergence. The detailed theoretical analysis, together with four theorems, are given to show the excellent properties of the QVZNN models. Furthermore, the upper bound of the convergence time is derived analytically with the residual error being zero theoretically. Finally, two numerical examples are provided to verify the theoretical results and the effectiveness of the QVZNN models for the dynamic quaternion-valued matrix inversion, and an application to mobile manipulator control is provided to indicate the practical application value of the QVZNN models. [ABSTRACT FROM AUTHOR]

Tensor robust principal component analysis (TRPCA) is a fundamental model in machine learning and computer vision. Recently, tensor train (TT) decomposition has been verified effective to capture the global low-rank correlation for tensor recovery tasks. However, due to the large-scale tensor data in real-world applications, existing TRPCA models often suffer from high computational complexity. In this letter, we propose an efficient TRPCA under hybrid model of Tucker and TT. Specifically, in theory we reveal that TT nuclear norm (TTNN) of the original big tensor can be equivalently converted to that of a much smaller tensor via a Tucker compression format, thereby significantly reducing the computational cost of singular value decomposition (SVD). Numerical experiments on both synthetic and real-world tensor data verify the superiority of the proposed model. [ABSTRACT FROM AUTHOR]

Unlike the traditional dock-based systems, dockless bike-sharing systems are more convenient for users in terms of flexibility. However, the flexibility of these dockless systems comes at the cost of management and operation complexity. Indeed, the imbalanced and dynamic use of bikes leads to mandatory rebalancing operations, which impose a critical need for effective bike traffic flow prediction. While efforts have been made in developing traffic flow prediction models, existing approaches lack interpretability, and thus have limited value in practical deployment. To this end, we propose an Interpretable Bike Flow Prediction (IBFP) framework, which can provide effective bike flow prediction with interpretable traffic patterns. Specifically, by dividing the urban area into regions according to flow density, we first model the spatio-temporal bike flows between regions with graph regularized sparse representation, where graph Laplacian is used as a smooth operator to preserve the commonalities of the periodic data structure. Then, we extract traffic patterns from bike flows using subspace clustering with sparse representation to construct interpretable base matrices. Moreover, the bike flows can be predicted with the interpretable base matrices and learned parameters. Finally, experimental results on real-world data show the advantages of the IBFP method for flow prediction in dockless bike sharing systems. In addition, the interpretability of our flow pattern exploitation is further illustrated through a case study where IBFP provides valuable insights into bike flow analysis. [ABSTRACT FROM AUTHOR]

This article deals with circuit modeling of power systems and more particularly of DC–AC converters used for controlling electric motors. The objective of the model is to be able to assess conducted emission currents at both inputs and outputs for fixed operating power in order to apply appropriate mitigation design rules, such as filtering. First, we propose a linear Thevenin block model of the converter considering it as a five-port linear black box allowing possible interaction between the DC and AC ports. To this extent, the block model is made of an impedance matrix and a Thevenin voltage generators vector. We also propose theoretical relationships allowing the processing of data to generate this model from measurements. Then, we test the linear simplifications on a real DC–AC converter and compare the results to measurements. For this, S-parameter measurements in off-mode and currents at the five ports in on-mode are used for the characterization of the model on a first test setup. The model is then applied and checked by comparing circuit simulated and measured current responses on a modified test setup for which the lengths of the connection cables are modified. Finally, the capability of this block model to extrapolate by calculation the response of other installation configurations is shown considering a filter and its insertion at input/output ports of the converter with much longer cables. [ABSTRACT FROM AUTHOR]

Dq impedance measurement is of great importance as a part of the impedance-based analysis. At present, impedance of objects in single-phase vehicle-grid system are mainly obtained by injecting the voltage or current disturbance of one single frequency into the system circularly. However, as the number of measurement frequency points increases, there will produce much time-consuming of measurement. In this paper, a quick dq impedance measurement algorithm for single-phase vehicle-grid system based on multi-frequency sweep is proposed. First, pseudo-random binary sequences (PRBS) and ternary sequences are modified as the driving signals rather than directly injecting into the control link. Then three types of disturbance with specific frequency characteristics are introduced into the system and their parameters setting principle are given for the first time. According to the different characteristics of measurement objects, the proposed algorithms are also different to ensure the maximum specificity and sensitivity. Finally, for different objects in vehicle-grid system like traction network, single-phase converter and dual-interleaved converter, simulation and experimental results based on the hardware in the loop real-time simulation platform both show the correctness of the proposed algorithm, and the possible causes of errors are also analyzed in detail. Moreover, the proposed algorithm makes it possible to quickly measure the dq impedance of the single-phase vehicle-grid system, and the correctness of the theoretical and measured value can be judged and used for the stability analysis of electrical systems. [ABSTRACT FROM AUTHOR]

The three-phase isolated ac–dc matrix converter (3P-IMC) inherits all the merits of the conventional matrix converter. But it also suffers from a large number of bidirectional switches and cannot operate safely in an open-circuit fault condition. Hence, with a general space vector PWM (SVPWM) model presented in this article, three types of asymmetrical SVPWM (ASVPWM) schemes are first proposed for normal and open-circuit fault-tolerant operation. The ASVPWM schemes have more kinds of synthetic vectors with asymmetrical distribution, however, also feature a higher freedom and flexibility to further improve the system performance. Then by sectional combining the above ASVPWM schemes with the conventional one, the 3P-IMC could be continued to operate with a tight dc output voltage regulation under single-switch open-circuit fault condition, which has an inherent open-circuit fault-tolerant capability. Compared with the conventional two-phase fault-tolerant operation, the proposed strategy has a smaller output voltage ripple, lower current stress, lower current harmonic, higher maximum output power, etc. The safety and reliability of the converter are greatly improved. Finally, a 3P-IMC experimental prototype is built up to verify the performance of the proposed ASVPWM schemes. [ABSTRACT FROM AUTHOR]

The modular multilevel matrix converter (M3C) is a promising topology for high-voltage and high-power direct ac-to-ac power conversion applications. Fault tolerance ability is one of the advantages of the M3C. To further enhance the reliability of the M3C, this article proposes a novel branch current configuration method for branch fault conditions, which is available either one or two branches are failed. By deriving basic branch current configurations and analyzing branch dc power equations under branch fault conditions, feasible branch current configurations can be directly derived. In terms of minimizing the maximum peak branch current, the derived configuration is also the optimal one for the single branch fault condition. Compared with the existing method, the proposed method does not need to solve configuration coefficients of branch currents offline, which is automatically adaptive to different load conditions. An M3C prototype with three submodules each branch is built, and experimental results are presented to validate the proposed branch fault tolerance method. [ABSTRACT FROM AUTHOR]

This article studies a decoupling cooperative control (DCC) with state feedback. It solves the output consensus problem on heterogeneous multiagent systems (MASs) over the input graph whose all nodes are reachable from the external reference signal. In light of the communication topology, the DCC forces each agent to reach a consensus on the given trajectory, which is from the reference signal of the common exosystem. Here, the output consensus problem is first equivalently converted into a stabilization one. Second the DCC involves a mapping ${\mathcal{ L}}_{d}$ of Laplacian matrix ${\mathcal{ L}}$ , i.e., every diagonal element of the Laplacian matrix is multiplied by a parameter $d_{i}$. ${\mathcal{ L}}_{d}$ moves Geršgorin circles of ${\mathcal{ L}}$. By the merit of ${\mathcal{ L}}_{d}$ , the equivalent stabilization problem is solved by the strictly positive real (SPR). In fact, the DCC is an approximate distributed decoupling control, when $d_{i}$ is sufficiently large. In addition, under the framework of the DCC, the assignment problem of the dominant poles for each agent is also solved by inverse optimal regulator technology in this article. Finally, several simulation examples verify the effectiveness of our method. [ABSTRACT FROM AUTHOR]

In this letter, we investigate the problem of intelligent network selection in hybrid classical-quantum communication systems. We propose a novel link selection mechanism based on the Fuzzy Analytic Hierarchy Process (FAHP) that effectively adapts classical network selection algorithms to handle hybrid communication scenarios involving classical and quantum communication systems. We analyze the performance of the proposed system using a generalization of a classical network selection algorithm based on FAHP and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Finally, we perform a power consumption analysis to validate the performance of the proposed system in the context of energy awareness. [ABSTRACT FROM AUTHOR]

This article deals with the control techniques of a low-voltage grid-connected to wind power conversion system based on a permanent magnet synchronous generator (PMSG) using an indirect matrix converter (IMC). Details of the proposed strategies for both the rectifier and inverter stages of the IMC are presented. Thus, a rectifier control strategy based on voltage-oriented control using space vector modulation is proposed. In addition, the control objective of the direct power control (DPC) inverter is the regulation of the active powers of the PMSG according to references established on the basis of the maximum power point tracker (MPPT) of the wind turbine, and also a good tracking of the output reactive power to its reference ensures unit power factor (UPF). A numerical simulation investigation is conducted to investigate the fast-dynamic performance of the proposed control systems during the wind speed variation. The obtained results in simulation are then complemented with tests in laboratory environment, the DPC control system is implemented on a dSpace DS1104 real time board. Selective experimental results are presented using a laboratory prototype of the wind energy conversion system to demonstrate the resulting improvements of the developed system. The results achieved have been clearly responded to the follow-up of references even under fluctuating wind conditions, and show promising relevance of the proposed method. [ABSTRACT FROM AUTHOR]

Hybrid-polarimetric architecture may become a new option for spaceborne quadrature-polarimetric (quad-pol) synthetic aperture radar (SAR) mainly due to the range ambiguity improvement without loss of polarization information. To inherit the analytical methods developed for the conventional quad-pol SAR data, it is necessary to transform the hybrid quad-pol SAR data into a linear polarimetric basis. However, this operation will result in deterioration of azimuth ambiguity performance. The theoretical analysis on range and azimuth ambiguities in quad-pol SAR has been relatively complete, which is also summarized in this article. Yet, there is no real data to verify the equivalence of polarization information and to compare the ambiguity levels. Based on P-band airborne experiment, real hybrid and conventional quad-pol SAR data are used for comparative verification. In addition, considering that polarimetric target decomposition is often used in the practical applications, we suggest a new perspective from target decomposition for the ambiguities in quad-pol SAR. Identical polarimetric processing results for two sets of comparative data verify that hybrid quad-pol SAR data are indistinguishable from conventional quad-pol SAR data. The demonstrated intensity images and decomposed RGB images with azimuth ambiguities, acquired by the two quad-pol modes, completely conform to the theory. [ABSTRACT FROM AUTHOR]

Sliding-window-based low-rank matrix approximation (LRMA) is a technique widely used in hyperspectral images (HSIs) denoising or completion. However, the uncertainty quantification of the restored HSI has not been addressed to date. Accurate uncertainty quantification of the denoised HSI facilitates applications such as multisource or multiscale data fusion, data assimilation, and product uncertainty quantification since these applications require an accurate approach to describe the statistical distributions of the input data. Therefore, we propose a prior-free closed-form element-wise uncertainty quantification method for LRMA-based HSI restoration. Our closed-form algorithm overcomes the difficulty of handling uncertainty in HSI patch mixing caused by the sliding-window strategy used in the conventional LRMA process. The proposed approach only requires the uncertainty of the observed HSI and provides the uncertainty result relatively rapidly and with similar computational complexity as the LRMA technique. We conduct extensive experiments to validate the estimation accuracy of the proposed closed-form uncertainty approach. The method is robust to at least 10% random impulse noise at the cost of 10%–20% of additional processing time compared to the LRMA. The experiments indicate that the proposed closed-form uncertainty quantification method is more applicable to real-world applications than the baseline Monte Carlo test, which is computationally expensive. [ABSTRACT FROM AUTHOR]

Direct Torque Control (DTC), a superior technique, which controls the stator flux and electromagnetic torque of an electrical machine. In spite of its numerous advantages, it possesses certain shortcomings like torque ripples, flux ripples, variable switching frequency and problems during the startup conditions. Recently, Matrix Converters (MC) have emerged as an efficient alternate for the Voltage Source Inverter employed in the DTC technique, which is capable of providing flexible and dynamic control over the torque and flux ripples associated in a machine. In this paper, a review on different control techniques associated in implementing the Matrix Converters for DTC method are categorized as follows: Subdivision of MC Voltage Vector method, SVM (Space Vector Modulation) based MC-DTC method, MC-DTC Duty Cycle Control, Employing Rotational Vectors of MC and Model Predictive Torque Control method. The pros and cons of each matrix converter fed direct torque control methods are presented by analyzing the experimental results from the literature. [ABSTRACT FROM AUTHOR]

This article proposes a family of two-to-three-phase ac–ac indirect matrix converters with an open-end rectifier stage (IMCORS) which are direct ac–ac converters, having no energy storage element at their dc-link. The IMCORSs are the first indirect matrix converters (IMC) with an open-end rectifier stage, creating a new category of IMC. The IMCORS is a full-controlled and unidirectional power flow converter. By replacing four active/controlled switches of the rectifier stage of the IMCORS with four diodes, two new configurations are proposed with reduced active switch count, resulting in reduced costs and increased efficiency. Also, by adding an inverting link to the dc-link of the rectifier stage of the IMCORS (which enables the bidirectional power flow operation), another converter is proposed. The IMCORSs topologies are suitable for wind energy conversion systems. A new modulation scheme for the rectifier stage is proposed in this article, which is titled two-phase open-end modulation scheme. The zero dc-link current commutation and the space vector modulation applied to the proposed converters provide a unity power factor for the input system, reduction of power losses, and decrease the complexity of the commutation when compared with classical matrix converters. The proposed converters are verified by simulation and experimentally using a 1.7-kW/liter prototype operating at 1 kW. [ABSTRACT FROM AUTHOR]

Though the merits of matrix-based dual-active-bridge (MB-DAB) ac–dc converter as a submodule for grid-connected multilevel medium-voltage ac (MVac)–low-voltage dc (LVdc) conversion have been presented in recent literature, its operational challenges in the cascaded configuration have not been explored. The objective of this article is to present the inevitable challenge of unequal power routing through the submodules of cascaded matrix-based dual-active-bridge (CMB-DAB) and its mitigation. The detailed and simplified small-signal model of the CMB-DAB converter along with the proposed power balance control (PBC) strategy required to eliminate the power imbalance issue are explained comprehensively. The simulation results for a 3-cell 52.65-kVA CMB-DAB converter along with scaled-down 5.85 kVA experimental results are presented, to demonstrate the unavoidable power imbalance issue and the proposed PBC strategy as a mitigation technique. The proposed scheme is observed to perform seamlessly with the conventional LVdc bus voltage control and remediate power-routing imbalance issue during the steady-state, load-change and hot plug-in/hot plug-out operations. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For massive multiple-input multiple-output (MIMO) systems, minimum mean square error (MMSE) detection is near-optimal, but requires high-complexity matrix inversion. To avoid matrix inversion, we formulate MMSE detection as a strictly convex quadratic optimization problem, which can be solved iteratively by the recognized most efficient Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method. According to special properties of massive MIMO systems, we propose a novel limited-memory BFGS (L-BFGS) scheme for MMSE detection with one correction search, unit step length, and simplified initialization, which can greatly reduce the storage and computation cost compared to BFGS method. Simulation results finally verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Heilongjiang University of Science & Technology is the property of Journal of Heilongjiang University of Science & Technology Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the modeling, design and analysis of Three Phase Matrix Converter (TPMC) using Direct Space Vector Modulation technique for the purpose of generation of gate pulses to the switches of the matrix converter. In this paper TPMC with different loads of resistive, Resistor-Capacitor (RC), Resistor-Inductor (RL) has been analyzed. TPMC converts Alternating Current (AC) input power to AC output power directly without the aid of DC link in between the conversion making the availability of the input power directly at the output without intermediate stage. The proposed TMPC with Space Vector Modulation technique possess several advantages compared with the convention converters & Sine Pulse Width Modulation (SPWM) technique. Any distortion or fluctuation in the input side of the converter can be easily depicted at the output side of the converter directly. The proposed topology has been implemented in the MATLAB/SIMULINK software and the desired results of the converter topology has been verified. [ABSTRACT FROM AUTHOR]

Matrix converter is a class of AC–AC power converters, which facilitates variable voltage and frequency control without intermediate conversion like pulse width modulated [PWM] inverters. Traditional control strategies for variable frequency control for AC–AC conversion can be extended for matrix converters. This research work proposes two PWM strategies with an objective of enhanced fundamental voltage and reduced THD for low-frequency operation. The concept behind the approach is concatenating both fundamental switching and PWM pulses. The fundamental switching reduces switching losses and enhances fundamental output voltage which is equal to the instantaneous values of fundamental component in that particular segment. On the other hand, the variation of pulse width using PWM has a control in the harmonic content which reduces THD. The simulation and experimental results prove the competencies of the proposed strategies in real-time application. [ABSTRACT FROM AUTHOR]

This paper proposes an extended method of zero-voltage switching (ZVS) range for a dual active bridge (DAB) matrix converter with a discontinuous current mode (DCM). In the traditionalDAB converter, ZVS cannot be achieved at a light load condition. The duty ratio calculation to achieve power factor correction and ZVS is explained using a circulating current. From the experimental results using a 5-kW prototype, the ZVS operation with zero transmission power is achieved by increasing the circulating current. In addition, the grid current distortion is lower than 5.0% at the rated power regardless of the DC voltage variation of plus or minus 20%. [ABSTRACT FROM AUTHOR]

To improve the poor dynamic consensus in multiple dc–dc converter systems caused by parameter differences, this article proposes a global optimal cooperative control strategy. The proposed control strategy achieves dynamic consensus of output currents by minimizing a global performance index, which consists of local errors and neighbor synchronization errors. In this system, each converter is regarded as an agent in the communication digraph, so as to construct a cyber-physical model. Accordingly, a cooperative control method based on the linear quadratic regulator (LQR) is proposed, with the help of nonlinear coordinate transformation techniques. Different from conventional LQR, integral action is introduced to eliminate steady-state errors and improve coordinated performance. Meanwhile, the proof of the stability and consensus of the closed-loop system is given using Lyapunov approach. Moreover, the design guidelines to tune the dynamic response are provided through simulations. The experimental results further demonstrate the effectiveness and superiority of the proposed control method in a multiconverter prototype. [ABSTRACT FROM AUTHOR]

This article proposes a systematic synthesis method to identify the optimum converter topology for a specified voltage conversion ratio. This gain-oriented converter synthesis is formulated as an inverse problem around the inductor flux balance equations. The proposed synthesis method consists of two processes. A set of distinct converter topologies is first synthesized from the specified voltage conversion ratio by obtaining the solutions for a set of six inverse equations in twelve unknowns. The optimal topology for any intended application can be identified based on the desired performance metrics. The complete synthesis method is illustrated with quadratic buck–boost gain as an example. In total, 25 distinct topologies are synthesized using the first process, and their feasibility is validated by PLECS simulation. In total, three case studies are reported to explain the second process. Ground-referenced output and the minimum number of switches are used as the first two selection criteria in all the case studies. Minimum peak inductor current, minimum component stress factor, and minimum voltage and current stress are the third selection criterion in Case Studies-1, 2, and 3, respectively. The steady-state operations of two optimal converters selected in Case Study-1 were verified experimentally. [ABSTRACT FROM AUTHOR]

Common-source inductance (CSI) is proven to be detrimental for high-speed switching. It can significantly slow down switching speed and increase switching losses. Recent research also demonstrated a self-turn-on phenomenon during the device turn-off transient in a simple buck converter. Yet there is lack of literature investigating the impact of CSI in circuits using bidirectional devices. This letter aims to first demonstrate and then reveal the mechanism of a unique turn-off voltage overshoot and oscillation phenomenon in converters using active bidirectional devices. The issue is found to be associated with the CSI in the bidirectional devices and can result in more than 100% voltage overshoot and significantly higher switching loss during the turn-off transient. Practical solutions are also provided to attenuate or eliminate the detrimental effects. The phenomenon and provided analysis are demonstrated and verified on a custom-built SiC-based matrix converter phase-leg. [ABSTRACT FROM AUTHOR]

A seven-level hybrid-clamped (7L-HC) converter is a promising option for medium-voltage drives due to its low number of devices and the ability to well balance all the capacitors. However, like other hybrid-clamped multilevel converters, the freewheeling paths during deadtime can produce unexpected output voltage levels. The unexpected output voltage can cross a few consecutive output levels, introducing a large dv/dt to the system. To address this problem, in this article, we conduct a detailed study of the mechanism that produces such undesirable voltages and propose a commutation scheme to coordinate the turn-on/off sequence of switches in the 7L-HC converters. The proposed method is based on an easy-to-implement bitwise operation of switching vectors, where the number of switching actions is not increased. The proposed method is validated by both simulation and experimental results. [ABSTRACT FROM AUTHOR]

The efficiency and safety issues caused by cell differences are the key factor to hinder the use of retired batteries. The reconfigurable battery technique is an effective method to break through the bottleneck. However, the potential short-circuit paths increase exponentially with the number of cells, which makes manual analysis unapplicable and brings serious risks in large scale reconfigurable battery systems. Existing researches are about topology and energy efficiency optimization, but the problem of short circuit is ignored. In this article, a systematic approach based on the sneak circuit theory is proposed to fundamentally avoid the short-circuit problem of reconfigurable battery systems. A novel sneak circuit theory based approach is creating a short circuit path table, which will be indexed to avoid connecting the anode and cathode of a battery cell/string. In addition, all the paths are further studied and analyzed, and the simplest path table can be obtained to improve the energy efficiency. To validate the theoretical foundation and feasibility of proposed approach, a reconfigurable battery system containing two kinds of batteries is developed. All experimental results well verify the effectiveness and feasibility of proposed approach. This work provides theoretical foundation for avoiding short-circuit paths in reconfigurable battery systems, which will break through the bottleneck in scale application. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main focus of the presented work is to provide an easy, efficient and rapid method of implementing the carrier-based PWM (CPWM) technique for the three-to-three phase indirect matrix converter (IMC). The control platforms DSP (TMS320F28335) and the FPGA (Spartan-6) are used for realising the CPWM scheme for the IMC. In the presented work, the auto code generation facility provided by the simcoder module of the PSIM software is utilised to develop the C-code for the TI F28335 hardware target. The FPGA is used to perform the logical operations on the switching pulses produced by the DSP. The complete procedure of implementing the CPWM scheme in DSP using simcoder module of PSIM and FPGA is demonstrated in this work. The simulation and the experimental results are included to verify the effective implementation of the CPWM scheme for the IMC. [ABSTRACT FROM AUTHOR]

Conventional processors suffer from high access latency and power dissipation due to the demand for memory bandwidth for data-intensive workloads, such as machine learning and analytic. In-memory computing support for various memory technologies has provided formidable improvement in performance and energy for such workloads, alleviating the repeated accesses and data movement between CPU and storage. While many processing in-memory (PIM) works have been proposed to efficiently compute dot products using Kirchoff’s law, such solutions are unsuitable for many analytic workloads where working data is too large and too sparse to efficiently store in memory. This article closely focuses on the peripheral circuit design for diode-selected crossbars and configures the compute-embedded fabric to efficiently compute sparse matrix-vector multiplication (SpMV). On average, our proposed end-to-end SpMV accelerator achieves $7.7\times $ speed up and $4.9\times $ energy-savings compared to the state-of-the-art Fulcrum. [ABSTRACT FROM AUTHOR]

Matrix converters feature low switching loss, small electromagnetic interference filter, and the potential for achieving high power density. With the employment of wide-bandgap devices, such as silicon carbide devices, the converter performance can be further improved. For a safe operation of matrix converters, an overvoltage protection circuit is necessary to limit the voltage stress of the devices during fault conditions. Due to the high switching speed of silicon carbide devices, the topology and layout design of the overvoltage protection circuit is critical to ensure fast and robust protection for the devices. In this article, a detachable overvoltage protection circuit is designed for each phase leg of the matrix converter. The topology and hardware layout design are elaborated. A 15-kW full silicon carbide implemented matrix converter is built, and the designed overvoltage protection circuits are employed and tested. [ABSTRACT FROM AUTHOR]

To analyze oscillation phenomenon caused by the interaction between converters and an AC grid, the impedance/admittance analysis method is a popular solution, in which each electrical component is represented by an external impedance/admittance matrix and a lumped matrix is formed for stability analysis. However, for converter-integrated power systems considering typical collector subsystems (e.g., the radial and the ring collector subsystems in wind farms and PV stations), the impedance network reduction to form the lumped impedance/admittance matrix (LIM/LAM) becomes complicated particularly for a ring collector subsystem, which affects the efficiency of the oscillation analysis. To address this problem, this paper proposes a method that can transform a typical topology of collector subsystems into a pure-parallel topology so that lumped admittance matrix is much easier to be derived. Algorithm complexity analysis confirms its computational advantages. A fifty-converter system is used to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

We study the oblique scattering of arbitrarily polarized plane waves from radially inhomogeneous and bianisotropic cylinders in the general case where all the elements of the four constitutive tensors are nonzero. The analysis relies on an exact reformulation of Maxwell’s equations as a second-kind linear Volterra matrix integral equation. The discretization scheme uses a high order, entire-domain, Nystrom method that employs the Gauss–Legendre–Radau quadrature. The entries of the Nystrom matrix have simple closed-form expressions. The proposed algorithms have exponential convergence and can handle both single-layer and multilayer cylinders with either continuous or sectionally continuous inhomogeneity profiles. [ABSTRACT FROM AUTHOR]

Modern computers keep following the traditional model of addressing memory linearly for their main memory and out-of-core storage. While this model allows efficient row access to row-major 2D matrices, it introduces complexity to perform efficient column access. A common strategy to improve these accesses is to transpose or rotate the matrix beforehand, thus the accessing complexity is centralized in one transformation operation. Further column accesses are performed as row accesses to the transposed matrix therefore they are optimized to the memory model. In this article, we propose an efficient solution to perform in-memory or out-of-core rectangular matrix transposition and rotation by using an out-of-place strategy, reading a matrix from an input file and writing the transformed matrix to another (output) file. An originality of our processing algorithm is to rely on an optimized use of the page cache mechanism. It is parallel, optimized by several levels of tiling and independent of any disk block size. We evaluate our approach on five common storage configurations: HDD, hybrid HDD-SSD, SSD, software RAID 0 of several SSDs, and NVMe. We show that it brings significant performance improvement over a hand-tuned optimized reference implementation developed by the Caldera company and we confront it against the baseline speed of a straight file copy. [ABSTRACT FROM AUTHOR]

Indoor location-based services (LBS) have exhibited large commercial and social values in smart cities, and urgent demands of which have spurred many localization techniques. Existing indoor localization approaches mostly rely on fingerprint techniques, leveraging either spatially discrete fingerprints or temporally consecutive ones for localization. However, these approaches often suffer from large errors or high time overhead in practice due to signal ambiguities or long input sequences. To overcome these drawbacks, this paper proposes a framework utilizing multiple adaptive representations of signal sequences for localization, where each representation indicates a corresponding signal structure with underlying location clues. As an example, the proposed approach takes geomagnetic signal sequences as input and infers location features from two intuitive representations, e.g., spatial and temporal ones. With adaptive signal representations, the proposed approach takes specifically optimized neural networks to extract corresponding location clues respectively and fuses them to generate more distinguishing features for more accurate localization. Furthermore, the ensemble learning mechanism is adopted in the approach and a weighted k-NN based location estimation algorithm is devised to enhance the robustness. Extensive experiments in three different trial sites demonstrate that the proposed approach outperforms state-of-the-art competing schemes by a wide margin, reducing mean localization error by more than 46%. [ABSTRACT FROM AUTHOR]

This paper aims to address two fundamental challenges arising in eigenvector estimation and inference for a low-rank matrix from noisy observations: 1) how to estimate an unknown eigenvector when the eigen-gap (i.e. the spacing between the associated eigenvalue and the rest of the spectrum) is particularly small; 2) how to perform estimation and inference on linear functionals of an eigenvector—a sort of “fine-grained” statistical reasoning that goes far beyond the usual $\ell _{2}$ analysis. We investigate how to address these challenges in a setting where the unknown $n\times n$ matrix is symmetric and the additive noise matrix contains independent (and non-symmetric) entries. Based on eigen-decomposition of the asymmetric data matrix, we propose estimation and uncertainty quantification procedures for an unknown eigenvector, which further allow us to reason about linear functionals of an unknown eigenvector. The proposed procedures and the accompanying theory enjoy several important features: 1) distribution-free (i.e. prior knowledge about the noise distributions is not needed); 2) adaptive to heteroscedastic noise; 3) minimax optimal under Gaussian noise. Along the way, we establish valid procedures to construct confidence intervals for the unknown eigenvalues. All this is guaranteed even in the presence of a small eigen-gap (up to $O(\sqrt {n/\mathrm {poly}\log (n)}\,)$ times smaller than the requirement in prior theory), which goes significantly beyond what generic matrix perturbation theory has to offer. [ABSTRACT FROM AUTHOR]

In this article, a time-invariant polynomial model of fixed-frequency pulsewidth modulation dc–dc converter is proposed. Through normalized coordinate transformation, the time-varying model of the converter is transferred into a time-invariant model, whose state matrix and input matrix are obtained by the addition and multiplication of matrices simply and expressed by the polynomial of duty cycle concisely. The proposed model has the following advantages. Compared with the state-space average (SSA) model, the ripple of the state vector and the switching period are considered, thereby improving the accuracy. Contrary to other time-invariant models, the state matrix and input matrix instead of the state vector are expanded into series. Therefore, neither the number of state vectors nor the order of the matrices increases, and the proposed model has a simple structure similar to the SSA model. In addition, as a time-invariant polynomial model, the calculation and analysis of the proposed model are much simpler than the time-variant exact model. In order to prove the above advantages of the proposed model, the general expression of the proposed model is derived and the proposed model is compared with other models. These analyses and comparisons are verified through the simulation and experimental results. [ABSTRACT FROM AUTHOR]

This letter addresses eigenvalue calculation of linear time-periodic models for small-signal stability analysis of converter dominated power systems. An adaptive truncation order selection method is proposed to achieve a balance between computational accuracy and efficiency. Rigorous theoretical analysis and case studies on a grid-following voltage source converter and a modified IEEE 13-bus system validate the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

Multiactive bridge (MAB) converter is a promising solution for integrating multiple renewable sources, storage, and loads for various applications. However, the MAB converter is challenging to control due to the inherent coupling between the port power flows. To that end, this article presents a decoupling control strategy based on linear active disturbance rejection control. The proposed controller observes the coupling disturbance using a linear extended state observer and subsequently rejects the observed disturbance resulting in dynamic decoupling. Experiments conducted on a 2-kW 100-kHz Si-C-based four-port MAB converter laboratory prototype illustrate the decoupling performance of the proposed control strategy. Compared to the traditional decoupling control strategy, the proposed approach is decentralized and model independent, only requiring information regarding its order. [ABSTRACT FROM AUTHOR]

A novel image processing scheme based on flash memory is proposed as a highly efficient pre-processing unit capable of Discrete Cosine Transform (DCT) operation for image compression and feature extractions. By using matrix splitting algorithms and optimizations of operation bias, the DCT operation is demonstrated successfully based on the 65 nm NOR flash memory. The processing accuracy, as well as its variations, can be well controlled by setting the working points at the saturation region with further circuit optimizations. The data compression rate is ~15.6%, showing that the proposed scheme can provide a fundamental solution to accelerate various neural network training, image recognitions, and retrievals. [ABSTRACT FROM AUTHOR]

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This paper discusses a new approach for building a compact all-in-one matrix converter module based on SiC semiconductors arranged in a common source connection. The used transistors are in the D2PAK package. The design of the module is divided into two parts, namely a power module designed at one-layer aluminum substrate printed circuit board (PCB) to ensure good thermal performance and voltage isolation between the module and heatsink. The second board is responsible for the SiC driving and is mounted at the top of the power PCB and consists of metal-oxide semiconductor field effect transistor (MOSFET) drivers, isolated power supplies, a current direction detection circuit, and current value sensors. In the paper, the proper function of the SiC MOSFET drivers, current direction detection, and current measurement sensors were evaluated. Finally, 3D design together with the final prototype is presented. The modules contain three bidirectional cells for interconnection three input voltage sources and one output phase. The uniqueness and novelty of the presented module are the compactness and easy expandability of the module to achieve higher power outputs and multiphase applications such as five phase machines. [ABSTRACT FROM AUTHOR]

In this article, a novel pre-processing method is proposed for magnetic field approximation based on neural networks. The process of calculating magnetic fields based on neural networks is presented first. In order to save the training time and reduce the estimation error, an excitation distance function, which is inspired by an analytical formula of magnetic potential, is proposed to integrate the input data, such as the geometry, excitations, and boundaries. This pre-processing or roughly reduces the dimension of the input layer by three quarters, while the training process is accelerated by a more integrated input layer. Preliminary experiments show that the predicted results by the proposed pre-processing method are close to the ground truth, with a significant reduction of computation time compared with the traditional finite element method (FEM). [ABSTRACT FROM AUTHOR]