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IPC (Inter-Process Communication) is a widely used operating system (OS) technique that allows one process to invoke the services of other processes. The IPC participants may share the same OS (internal IPC) or use a separate OS (external IPC). Even though a long line of researches has optimized the performance of IPC, it is still a major factor of the run-time overhead of IPC-intensive applications. Furthermore, there is no one-size-fits-all solution for both internal and external IPC. This paper presents SkyBridge, a general communication technique designed and optimized for both types of IPC. SkyBridge requires no involvement of the privileged software (the kernel or the hypervisor) and enables a process to directly switch to the virtual address space of the target process, regardless of whether they are running on the same OS or not. We have implemented SkyBridge on two microkernels (seL4 and Google Zircon) as well as an open-source serverless hypervisor (Firecracker). The evaluation results show that SkyBridge improves the latency of internal IPC and external IPC by up to 19.6x and 1265.7x, respectively. [ABSTRACT FROM AUTHOR]

The demand for real-time data processing has become increasingly attractive in Cyber-Physical Systems(CPSs), especially for data-intensive embedded real-time applications. In order to timely perceive and respond to environmental changes, the basic design requirement in such systems is to provide data service with high freshness. As modern CPSs become more complex, there are a broad set of system mode switch behaviors, some unforeseen, in a dynamic computational environment. However, conventional control algorithms can hardly handle such new scenarios, since most of them assume that the operational behavior is fixed. In this paper, we study the problem of how to maximize the freshness of data in multi-modal systems. We first use a recently proposed new conception, namely Age of Information (AoI) to quantify the freshness of data by combining the AoI metric with real-time constraints. Then, we propose, to our knowledge, the first freshness-aware scheduling solution to settle the problem via deep reinforcement learning(RL). To be specific, we develop an RL framework that can continuously update its scheduling strategies and maximize the freshness of data in the long term. Extensive simulation experiments are conducted and the results demonstrate that the proposed FAS-DQN outperforms other traditional state-of-the-art methods in terms of data freshness. [ABSTRACT FROM AUTHOR]

This paper focuses on the issue of network connectedness (NC) in security-constrained optimal transmission switching problems, which is complicated by branch contingencies and corrective line switching. Two criteria are firstly proposed with the principle of preserving NC as much as possible within reasonable limits. By extending the electrical flow based NC constraints, a proposition is derived to associate different cases of NC with the optimum of a linear program, yielding the mathematical formulation of the NC criteria. By Karush-Kuhn-Tucker conditions, this formulation is further transformed into a tractable version which can be incorporated with existing SCOTS models without affecting the applicability of original solution approaches. Finally, case studies on various networks and SCOTS models demonstrate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Magnetic random-access memory (MRAM) is a promising memory technology due to its high density, non-volatility, and high endurance. However, achieving high memory fidelity incurs high write-energy costs, which should be reduced for large-scale deployment of MRAMs. In this paper, we formulate a biconvex optimization problem to optimize write fidelity given energy and latency constraints. The basic idea is to allocate non-uniform write pulses depending on the importance of each bit position. The fidelity measure we consider is mean squared error (MSE), for which we optimize write pulses via alternating convex search (ACS). We derive analytic solutions and propose an alternating water-filling algorithm by casting the MRAM’s write operation as communication over parallel channels. Hence, the proposed alternating water-filling algorithm is computationally more efficient than the original ACS while their solutions are identical. Since the formulated biconvex problem is non-convex, both the original ACS and the proposed algorithm do not guarantee global optimality. However, the MSEs obtained by the proposed algorithm are comparable to the MSEs by complicated global nonlinear programming solvers. Furthermore, we prove that our algorithm can reduce the MSE exponentially with the number of bits per word. For an 8-bit accessed word, the proposed algorithm reduces the MSE by a factor of 21. We also evaluate MNIST dataset classification supposing that the model parameters of deep neural networks are stored in MRAMs. The numerical results show that the optimized write pulses can achieve 40% write-energy reduction for the same classification accuracy. [ABSTRACT FROM AUTHOR]

The digital implementation of all the control loops of a versatile buck-boost (VBB) dc–dc converter used in a stand-alone photovoltaic application is proposed in this paper to improve existing digital-analog sliding-mode-based implementations. All three control loops: maximum power point tracking (MPPT), fast input voltage regulation, and inner high-bandwidth current control, have been programmed in the same digital signal controller (DSC). A Model Predictive Control (MPC) based algorithm has satisfactorily solved the challenge of implementing the nominal 100 kHz switching frequency current loop. The MPC cost function is distributed throughout the algorithm to achieve three specific goals: the tracking of the reference current (G1), a quasi-constant steady-state switching frequency (G2), and the assurance that the duration of an interval is larger than the time required to calculate it (G3). The third goal requires the current control to toggle between peak- and valley-modes depending on the operating point. The correct fulfillment of these control objectives on the proposed MPC-based algorithm has been validated through simulations and experimental tests performed on a purpose built-prototype. [ABSTRACT FROM AUTHOR]

In this paper, a fault-tolerant control of a symmetrical six-phase induction generator based on a variable structure strategy is experimentally tested and compared with a classical proportional-integral controller. For this, we use a linear feedback sliding mode controller with switched feedback gains in such a way to control the inner current loops of this machine. One main drawback of the classical three-phase induction generator is that it is no longer possible to generate electrical power if only one phase is lost on the stator side. To overcome this issue, we will use a squirrel cage six-phase induction machine that can still operate when at least three phases remain on the stator side. This article proposes to use a variable structure control in order to cope with unbalanced currents and also maintain the generation of power when a loss of the stator's phases occurs. The proposed controller shows its robustness and good regulation performance in healthy and faulty modes. The simulation and experimental tests were carried out with a 24 kW induction machine that represents 1/100 of the electrical power of a real wind turbine. [ABSTRACT FROM AUTHOR]

In this paper a control method for a matrix converter (MC) based on the heterodyne concept from the communication field is presented. The method is used to convert the high frequency of a microturbine generator’s (MTG) output voltage to the utility grid’s frequency. In this control method a frequency modulation (FM) of the MC’s switching frequency is achieved using a DQ0 analysis of the converter’s filtered output voltage with the utility grid’s frequency as a reference. After filtration, the MC achieves a conversion to the reference frequency with a minimal total harmonic distortion (THD) of the output voltage while using a low switching frequency. In addition, the proposed method decouples the output frequency, phase angle and voltage amplitude, which allows them to be controlled separately. This significantly simplifies the required control, and enables a robust and low-cost design. The theoretical analysis, simulation and experimental results of the method are reported. [ABSTRACT FROM AUTHOR]

Multiphase drives with fault-tolerant capability are favored in high-reliability applications. In most fault-tolerant multiphase drives, the fault types and locations must be known prior to the fault-tolerant control. Therefore, fault diagnosis is an indispensable procedure. This paper proposes a generalized method to detect and identify the open-circuit faults (including open-switch and open-phase faults) in star-connected symmetrical multiphase drives with different phase numbers. The selected fault diagnosis signals are calculated solely from simple arithmetical operations of measured phase currents, resulting in easy real-time implementation. As fault detection signals are derived from the physical constraint imposed by the neutral point, the proposed method is naturally robust and not sensitive to operating points, machine transients and harmonics in stator currents. Therefore, a relatively small fault detection threshold can be used and fast detection can also be achieved. After the fault has been detected, the fault type is further identified according to the polarity of the integration of phase currents. Experimental results on nine-phase and five-phase induction machine drives verify the generality, fast diagnosis speed and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Differential power processing (DPP) converters have been developed for photovoltaic (PV) panels to preclude energy yield reduction due to partial shading. In large-scale PV systems comprising numerous series-connected panels, DPP converters with good modularity are preferable because the number of series-connected panels varies depending on applications. This paper proposes a switched capacitor converter (SCC)-based modular DPP architecture for large-scale PV systems. Four panels are grouped as a module, each having a panel-level DPP converter, and modules are connected in series to form a string. The design of the panel-level DPP converter is fixed while the system can be arbitrarily extended by stacking modules, achieving good modularity. Adjacent panel-level DPP converters are dc-coupled, by which modules can be connected using long cables, mitigating installation limitations. The experimental results of the laboratory and field testing demonstrated the energy yield enhancement by 10%–20%, depending on shading conditions. [ABSTRACT FROM AUTHOR]

This paper presents a sigma-modified adaptive control algorithm to enhance the charging profile in a multi-objective electric vehicle (EV) charging installation. The present algorithm takes care of multiple parametric uncertainties and grid non-idealities to provide an instantaneous control updation in order to achieve well-regulated charging dynamics. With the support of renewable energy and battery energy storage (BES), the present algorithm also ensures an uninterrupted charging profile with controller robustness and stability for bi-directional EV charging. The sigma-mod adaptive controller provides an iterative error convergence at each clock interval of supply voltage dynamics to guarantee improved power quality operation in presence of grid distortions. To further improve the reliability of EV charging opportunities, a solar photovoltaic (PV) array in conjunction with the battery energy storage supports the ancillary services through maximum power point operation. Multivariable sliding mode control and rule-based phase-shift adaptation at different stages of power transformation assure faster convergence, parameter uncertainty and controller stability for the bi-directional EV charging operation. A 3.3 kW PV-integrated off-board charging facility is designed and developed as a laboratory prototype to validate the multi-mode charging architecture with minimal grid dependency. [ABSTRACT FROM AUTHOR]

The paper develops two computationally efficient models, namely a detailed equivalent model and an average-value model, with provisions for representation of the critical state of converter blocking, for modular multilevel converters with embedded storage. These models are indispensable in the simulation of dc faults. The developed detailed equivalent model provides accuracy that matches electromagnetic transient (EMT) simulations, with much reduced computational burden; the developed average-value model represents the averaged behavior of the converter by neglecting switching transients. Both models are extensively evaluated in the context of an HVDC system against benchmark results form a detailed switching model developed in PSCAD/EMTDC. The results confirm the validity and accuracy of the models for steady state, transient, and faulted operating conditions including when the converter is blocked in response to a dc fault. [ABSTRACT FROM AUTHOR]

This paper proposes a novel dual input nine-level inverter (DINLI) topology which requires only seven controllable devices. The dual inputs are un-identical DC voltage sources in the ratio 1:3. A simple control scheme is derived by appropriately modifying the phase disposition pulse width modulation technique to generate high-quality 9-level output from the DINLI topology. At any given instant, a maximum of four switches conduct out of which only a maximum of two switches operate at high frequency, bringing down the switching and conduction losses significantly and improving the overall system efficiency. The bidirectional DINLI (BDINLI) topology with reactive power capability can be realized by replacing the unidirectional devices with the controlled switches (i.e., total nine switches). In addition, the proposed DINLI topology does not require extra voltage balancing circuits which further improves the efficiency. The DINLI operation is verified through MATLAB simulations for grid-connected applications and its extension to an n-level, 3-phase application is also investigated. Experiments performed on a 1KVA laboratory prototype to validate the theoretical claims. [ABSTRACT FROM AUTHOR]

Emerging device based spiking neural network (SNN) hardware design has been actively studied. Especially, energy and area efficient synapse crossbar has been of particular interest, but processing units for weight summations in synapse crossbar are still a main bottleneck for energy and area efficient hardware design. In this paper, we propose an efficient SNN architecture with stochastic spin-orbit torque (SOT) device based multi-bit synapses. First, we present SOT device based synapse array using modified gray code. The modified gray code based synapse needs only N devices to represent 2N levels of synapse weights. Accumulative spike technique is also adopted in the proposed synapse array, to improve ADC utilization and reduce the number of neuron updates. In addition, we propose hardware friendly algorithmic techniques to improve classification accuracies as well as energy efficiencies. Non-spike depression based stochastic spike-timing-dependent plasticity is used to reduce the overlapping input representation and classification error. Early read termination is also employed to reduce energy consumption by turning off less associated neurons. The proposed SNN processor has been implemented using 65nm CMOS process, and it shows 90% classification accuracy in MNIST dataset consuming 0.78μJ/image (training) and 0.23μJ/image (inference) of energy with an area of 1.12mm2. [ABSTRACT FROM AUTHOR]

Renewable energy is an advisable choice to reduce fuel consumption and $\rm CO_{2}$ emission. Therein, wind energy and solar energy are the most promising contributors to reach this goal. Although the hybrid wind/solar system has been widely studied, the real-time current sharing based on their maximum capacities is rarely achieved in terms of seconds. Based on this, this paper proposes an accurate current sharing and voltage regulation approach in hybrid wind/solar systems, which is based on distributed adaptive dynamic programming approach. Firstly, the equivalent wind/solar model is built, which is an indispensable preprocessing to achieve the complementary between wind energy and solar energy. Therein, the wind energy and solar energy can output relative current according to their respective capacity ratio, which ensure the maximum utilization ratio of renewable energy source. Furthermore, current sharing and voltage regulation problem is switched into optimal control problem. Under this effect, each source agent aims to obtain the optimal control variable and achieve accurate current sharing/voltage regulation. Moreover, an adaptive dynamic programming approach based on Bellman principle is proposed. It can achieve accurate current sharing and voltage regulation. Finally, the simulation results are provided to illustrate the performance of the proposed adaptive dynamic programming approach. [ABSTRACT FROM AUTHOR]

Channel estimation is one of the main challenges for implementing reconfigurable intelligent surface (RIS)-aided communication system with a large number of antennas at the base station (BS) because RIS is equipped with many passive reflective elements without active transmitting/receiving and signal processing abilities. In this paper, we focus on the channel estimation in a general RIS-aided multi-user mmWave communication system. Specifically, a novel two-phase channel estimation scheme consisting of on-line and off-line phases is proposed to estimate the BS-RIS channel, RIS-user channel, and BS-user channel, respectively. Inspired by the characteristics of few scatterers in mmWave communication systems, the antenna domain channels are converted into the virtual angular domain channels by using the discrete Fourier transform (DFT) matrix. Thus, the estimation problem can be formulated as a compressed sensing (CS) problem, and solved by using efficient vector approximate message passing (VAMP) algorithm with expectation-maximization (EM) to learn unknown parameters and obtain the estimates simultaneously. Simulation results show that, the above algorithm with two choices of prior distributions in the proposed mmWave RIS-aided multi-user system has fast convergence speed and desirable estimation performance. [ABSTRACT FROM AUTHOR]

Personalized venues recommendation is essential to help people find attractive venue to visit as growth of location-based social networks. Existing approaches never distinguish user individual interests from her social preferences, which leads to a bottleneck of modeling user check-in behaviors accurately. In this paper, we find the differences between user interests and her social preferences clearly and investigate the time law of user check-in behaviors in depth. Consequently, we propose a social-period-aware topic model (SPATM) to learn the influence weights of both user interests and her social preferences on making-decision for each check-in time automatically. Especially, we model latent topic by leveraging smaller size of dynamic activities instead of static categories, which can alleviate the data sparsity problem by using more co-occurrent activities information. Moreover, our approach can automatically judge whether a user’s social preference is periodic or aperiodic and learn the periodicity of periodic one. Furthermore, the Alias Sampling based training approach is introduced to improve sampling efficiency. The results demonstrate our proposed model is effective and outperforms the state-of-the-art approaches in terms of effectiveness and efficiency. Besides, SPATM can learn semantically coherent latent topics and geographically dispersed latent social topics which are useful to explain recommendation. [ABSTRACT FROM AUTHOR]

Most microgrid protection schemes found in published literature suffer from a lack of generality in that they work well for the assumed topology, including type and placement of sources. Other generic protection schemes tend to be too complicated, too expensive, or both. To overcome these drawbacks, a topology-agnostic, scalable, and cost-aware protection based on fundamental principles that work in the presence of high penetration of inverter-based resources (IBRs) is developed and tested in this paper. The protection system also implements stable automatic reconfiguration of the healthy sections of the system after clearance of fault, thus increasing resilience by self-healing. To achieve this ambitious goal, stable inverter models are developed that operate in unbalanced networks in grid-connected and islanded modes, even with 100% IBRs, share power without conflicting controls, and can ride through faults while limiting fault currents. The scheme is tested for primary and backup protection and reconfiguration on the IEEE 123-node feeder in grid-connected and islanded modes with 15 IBRs connected to the system. [ABSTRACT FROM AUTHOR]

Different from typical circuit breakers, breakers used to switch AC filters in convertor stations have to operate frequently according to the real-time operation mode and daily load changes. Therefore, the performance of filter breakers decreases very quickly, which leads to frequent accidents. Both preinsertion resistors and controlled switching devices can suppress switching transients. In this paper, a comparative analysis of whether a controlled switching device and preinsertion resistor should be adopted is carried out using PSCAD. The transient is calculated as the combined result of the switching angle and preinsertion resistor value, and the optimal configurations are proposed. After determining the resistor value and whether a controlled switching device should be included, the reference voltage of the arrester should be reevaluated. [ABSTRACT FROM AUTHOR]

This paper proposes a new passive Islanding detection approach for the Inverter Interfaced Distributed Generators (IIDGs) operating under different control modes. First, a novel index is formulated using Root Mean Square (RMS) value of the voltage and the frequency information, acquired at the Point of Common Coupling (PCC) of the target DG. The index is then post-processed by estimating the number of peaks and valleys $(N_{p_{k}-v})$ in a cycle using the sliding window concept, which indicates the occurrence of an event. Finally, the nature of the event, i.e., Islanding or non-Islanding, is decided by exploiting the two statistical features viz., Square of RMS $(S_{RMS})$ of $N_{p_{k}-v}$ and Average Crest Factor $(ACF^{m})$ of the proposed index. The performance of the proposed method (P-IDM) is demonstrated through comprehensive studies in PSCAD/EMTDC for the single-bus and IEEE 34-bus Active Distribution System (ADS). Also, the real-time validation is performed for the IEEE 34-bus using Controller Hardware-in-the-Loop (CHIL) setup comprising of Real-Time Digital Simulator (RTDS) and dSPACE1104. The simulation and hardware results for different test systems indicate that the proposed scheme, being generic in nature, sustains its efficacy under various interface controls of IIDGs. Finally, a comparative assessment with the other existing Signal Processing (SP) based passive methodologies shows the supremacy of the proposed method in terms of accuracy and faster detection. [ABSTRACT FROM AUTHOR]

This paper presents a combined control scheme that consists of two complementary control strategies, namely hierarchical control and autonomous control to handle contingencies in a multi-terminal high voltage direct current (MTDC) system. The proposed hierarchical control considers three optimal targets, i.e., equal or proportional power sharing, minimizations of transmission loss and total DC voltage variation. The primary control layer implements the droop control for voltage source converters (VSCs). While in the secondary control layer, voltage reference setpoints of the VSCs in droop control scheme are calculated by the proposed optimal power flow method with the equal or proportional power sharing as equality constraints. As the hierarchical control relies on communication system, the autonomous control for power sharing can be activated during communication system malfunctioning or rapid power variation caused by renewable energy sources. The combined control strategy can greatly increase the reliability of the MTDC system. The simulation results of a five-terminal MTDC network conducted in the MATLAB/Simulink software verify the performance of the proposed combined control strategy. [ABSTRACT FROM AUTHOR]

Voltage source converters (VSCs) have been extensively used in power systems for interfacing renewable energies and other modern loads. Because of their nonlinear nature, a proper harmonic model of VSC devices must be established when conducting harmonic analyses in power systems. This is especially true for low-order harmonics, which are routinely encountered in present power systems. To this end, an analytical harmonic model that represents the low-order harmonic characteristics of VSCs is developed in this paper. The new model takes both the control loop and power loop (i.e., DC-link capacitor) of the VSC into account through rigorous mathematical derivations. The final result has shown that the VSC can be represented by a harmonically coupled impedance matrix at harmonic frequencies, which can be easily used for harmonic analyses of large-scale power systems. It also shows that the DC-link capacitor has a more noticeable impact on the harmonic impedance of VSCs with a smaller DC-link capacitance and low-order harmonics. The appropriateness of the new model was verified using EMT simulations and lab experiments. A complete procedure to construct the proposed VSC model is also established based on the research findings. [ABSTRACT FROM AUTHOR]

This paper proposes a sound separation methodology based on deep learning neural network (DLNN) to extract useful diagnostic material in non-invasive audio-based On-Load Tap Changer (OLTC) diagnostics. The proposed methodology has been experimentally verified on both artificial mixtures (created by reproducing the targeted data by the speakers placed next to the active transformers) and actual mixtures (recorded by the microphone during OLTC live operation in the field). The results show that the method produces high-quality estimates (correlation to referent fingerprints $\rho > 0.9$) compared to other sound separation methods, e.g. Independent Component Analysis (ICA). The proposed framework can also perform source separation from a monaural mixture (mixture recorded with a single microphone only), which is impossible for ICA methods. Moreover, the results show that DLNN trained with healthy OLTC data produces diagnostically valuable estimates even when fed with a faulty OLTC audio mixture. For that reason, once trained, the DLNN can produce the diagnostic signal estimates from monaural mixtures that can be used with existing vibration-based diagnostic methods. [ABSTRACT FROM AUTHOR]

Line-commutated converters are extensively used as the interface between ac grids and classic HVDC systems. At the inverter side, commutation failure of switches is one of the most common faults that can pose threats to the system operation. Practical and reliable study of such phenomena relies on accurate and efficient converter models for simulations. Recently, a parametric average-value model (PAVM) has been presented for ac–dc rectifiers, which considers the internal faults of the converter. In this paper, the PAVM methodology is extended to the dc–ac inverter systems, including the commutation failure of switches. The proposed PAVM also augments an automatic fault detection technique to determine the faulty switches. Using comprehensive simulation studies, the developed model is verified to accurately predict the commutation failure of switches and reconstruct the waveforms consistent with the detailed switching models of inverters while being computationally more efficient. The proposed PAVM is envisioned to be an efficient and accurate asset for simulation of HVDC systems and inevitable when faults of switches need to be considered. [ABSTRACT FROM AUTHOR]

High penetration level of single-phase solar PVs in low voltage distribution systems has raised concern about the Voltage Unbalance (VU) level. Real-time phase reconfiguration using Dynamic Switching Devices (DSD) has been proposed as a cost-effective solution to mitigate the excessive level of Voltage Unbalance. DSDs are fast power electronics devices that could change the phase connection of a solar PV with minimum disturbances. Most of the proposed methodologies for controlling DSDs are based on a central controller and the assumption of availability of Advanced Metering Infrastructure (AMI) and a communication system. In this paper, we propose a distributed control methodology to control DSDs based on the measurement from the local node only and using the sensitivity of nodal voltage to power injection. Each DSD decides on phase swapping if it rectifies the unbalance index of the local node. We show that decreasing the Voltage Unbalance Factor (VUF) of individual nodes will improve the unbalance situation of the whole feeder. The proposed scheme does not require a communication system nor a central controller. The result of simulations confirms the efficacy of the proposed methodology. [ABSTRACT FROM AUTHOR]

VSC-HVDC systems are being increasingly employed in the power systems. The recently installed HVDC systems have a power capacity similar to traditional power plants. Hence, they are expected to have a similar behaviour as traditional synchronous generators during faults in AC grid, within their limits of course. Recent grid codes require HVDC converter stations to incorporate fault ride-through (FRT) capabilities in order to avoid HVDC converter station disconnection from AC grid for certain fault characteristics. In this paper, two FRT mechanisms are suggested for the two converter stations of an HVDC system. One FRT mechanism is added to the DC voltage control loop of the master converter station, while the other FRT mechanism is added to the active power control loop of the slave converter station. The objective is to ensure the stable operation of the HVDC system during faults that may occur in AC grids located on both sides of the HVDC system. The performance and stability of the suggested FRT mechanisms are tested considering the pre-fault power flow direction and all possible types of balanced and unbalanced faults. Simulation results confirm the effectiveness of the FRT mechanisms and revealed the critical modes during FRT operation. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) and cell-free (CF) massive multiple-input multiple-output (MIMO) are two promising technologies for realizing beyond-fifth generation (5G) networks. In this paper, we study the uplink spectral efficiency (SE) of a practical spatially correlated RISs-aided CF massive MIMO system over Rician fading channels. Specifically, we derive the closed-form expression for characterizing the uplink SE of the system, which shows that increasing the number of RIS elements can improve the system performance. Moreover, the results unveil that the spatial correlation of RIS has a significant impact on the system while leading to the best performance gain at a half wavelength spacing. Finally, the accuracy of our analytical results are verified by Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

Miniaturization and low cost contribute to the development and popularization of wireless power transfer (WPT). Reducing the number of power conversion stages can reduce the volume and cost of the WPT converter, and even make it possible to improve the efficiency. A single-stage WPT converter with constant current (CC) and constant voltage (CV) output and its asymmetric modulation method are proposed in this paper. A direct AC-AC converter is applied to the primary side of the WPT converter to directly convert line-frequency AC to high-frequency AC. The applied direct AC-AC converter that can replace the commonly used multi-stage primary converter reduces the number of circuit devices, thereby reducing the volume and cost of primary converter. The proposed WPT converter can realize zero voltage switching (ZVS) and power factor correction (PFC). In order to achieve CC and CV output, a switchable hybrid compensation topology is applied to the proposed WPT converter. A 720-W experimental prototype was manufactured to verify the rationality of the proposed WPT converter and the correctness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

Mixed-criticality (MC) scheduling becomes popular in real-time systems as it supports different criticality levels in a resource-efficient manner. Although it has been well established (i) how to guarantee MC schedulability offline, existing studies have paid less attention to achieve (ii) how to minimize deadline misses of low-criticality tasks at runtime; in addition, it has not matured yet how to address (ii) without compromising (i). In this paper, we propose $\mathsf{MC{-}FLEX}$ MC - FLEX , which employs a task-level mode transition mechanism (as opposed to system-level one). $\mathsf{MC{-}FLEX}$ MC - FLEX not only determines time instants at which each high-criticality task enters and exits the critical mode in a task level, but also selects time instants and target low-criticality task(s) to be dropped and resumed for each task-level mode switch of individual high-criticality tasks, yielding the achievement of both (i) and (ii). Via simulation results, we demonstrate that the proposed framework reduces the job deadline miss ratio of low-criticality tasks at runtime (by over 54.8% compared to the existing work), without compromising offline MC schedulability. [ABSTRACT FROM AUTHOR]

Erasure coding becomes increasingly popular in distributed storage systems (DSSes) for providing high reliability with low storage overhead. However, traditional random data placement induces massive cross-rack traffic and severely imbalanced load during failure recovery, which degrades the recovery performance significantly. In addition, various erasure codes coexisting in a DSS exacerbates the above problems. In this paper, we propose PDL, a PBD-based Data Layout, to optimize failure recovery performance in DSSes. PDL is constructed based on Pairwise Balanced Design, a combinatorial design scheme with uniform mathematical properties, and thus presents a uniform data layout for mixed erasure codes. Then we propose rPDL, a failure recovery scheme based on PDL. rPDL reduces cross-rack traffic effectively and provides nearly balanced cross-rack traffic distribution by uniformly choosing replacement nodes and retrieving determined available blocks to recover the lost blocks. We implemented PDL and rPDL in Hadoop 3.1.1. Compared with the existing data layout and recovery scheme in HDFS, experimental results show that rPDL achieves much higher recovery throughput, $6.27\times$ 6. 27 × on average for single-node failures, $5.14\times$ 5. 14 × for multi-node failures and $1.48\times$ 1. 48 × for single-rack failures, respectively. It also reduces degraded read latency by an average of 62.83 percent, and provides better support to front-end applications in case of component failures. [ABSTRACT FROM AUTHOR]

This paper considers a cooperative multiple access (CMA) scheme where two full-duplex sources simultaneously send their own messages to a common destination. As part of their cooperation, each of the two sources also receives and relays part of the message from the other source. This paper develops algorithms for computing the optimal power allocation to achieve the maximal network throughput subject to residual self-interference (RSI) at the non-ideal full-duplex sources. As a generalization of a time-division duplex (TDD) scheme, we consider a three-phase CMA (3P-CMA) scheme which treats the TDD scheme as a special case. The throughput of the 3P-CMA scheme consistently exceeds that of the TDD scheme regardless of the RSI power gain. Also shown in this paper is a semi-closed form of the optimal power allocation when the three-phases are constrained to be identical, i.e., resulting in a one-phase CMA (1P-CMA) scheme. The optimal power allocation of the 1P-CMA scheme takes much less time to compute, and its network throughout is close to that of the 3P-CMA scheme when the RSI power gain is low. [ABSTRACT FROM AUTHOR]

This paper investigates the Multilevel Current Source Converter (MCSC) STATCOM. It proposes a new method of modulation. The new modulation method produces less THD and di/dt at the terminals of the MCSC STATCOM when compared to the widely used Phase-Shifted Carrier SPWM (PSC-SPWM). To ensure the inductors' currents remain balanced, a Current Balancing Algorithm (CBA) is presented. The CBA does not require any controls. It relies on assigning optimum switching states to each CSC module in real-time. In addition, two control strategies are presented in this paper. The first one assumes the STATCOM to be a SISO. Therefore, it only requires one PI controller. However, the gains for the controller must be changed if the STATCOM was to transition from capacitive mode to inductive mode, or vice versa. The second control strategy overcomes this problem by implementing a TITO integral state feedback controller. The contributions of this paper are validated via simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive model of modular multilevel converter (MMC) for electromagnetic transient (EMT) simulations. The model is applicable to MMCs with arbitrary numbers of half-bridge and full-bridge submodules. The proposed design includes average value model, arm equivalent model, and detailed equivalent model. It allows smoothly transitioning from one model to another during time-domain simulations depending on the desired accuracy and execution time constraints. Modifications required in conventional MMC models to achieve smooth transitions are presented in the paper. Time-domain initialization methods are developed for each constituting model, including initialization of the appropriate control system blocks. Validity and effectiveness of the proposed adaptive model is demonstrated using EMT simulations of 401-level MMC-HVDC system. [ABSTRACT FROM AUTHOR]

This paper includes some results of switched Boolean control networks. The switched signals considered in this paper is time variant and it follows a certain probabilistic distribution vector. Given a concept of stabilization with stochastic switched signals, we obtained a necessary and sufficient condition for stabilization. Then a state feedback control depending on switched signals is designed to stabilize the system considered. Later we investigate a case when the switched signal $\theta (t)$ is unknown at time $t$ , and what we have is the prediction switched signal $\hat {\theta }(t)$. For a given prediction matrix, a necessary and sufficient condition is given to preserve the stabilization. Except state feedback control, asynchronous pinning control for switched Boolean networks (BNs) is also considered. A necessary and sufficient condition is extended for the stability of BNs with stochastic switched signals. Moreover, algorithms are presented to find the minimal number of pinned nodes based on controlling minimal number of subsystems. Examples are shown to illustrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This paper investigates the robust containment control problem of multiagent systems with heterogeneous uncertainty and nonlinearity while the nonlinear parts have to satisfy the Lipschitz condition. In this paper, both input time-delay and data transmission time-delay between the agents are considered simultaneously and communication topology of the multiagent systems may switch in the steady-state condition. Under the mentioned conditions, the objective of this paper is to make all the followers’ states converge to the convex hull shaped by the leaders’ states with an expected exponential rate. To this end, an appropriate smooth protocol is proposed. Then, a Lyapunov–Krasovskii functional composed of five terms is proposed and the stability condition is denoted by two linear matrix inequalities (LMIs). In addition to the stability assurance, solving the LMIs would obtain the suitable gains for the protocol. Finally, some numerical simulations are given to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

The demand for DC gas-insulated switchgear/gas-insulated transmission line (GIS/GIL) becomes more and more urgent in recent years owing to the rapid development of high voltage direct current (HVDC) transmission systems. Insulators in DC GIS/GIL could easily accumulate a large number of charges on its surface during long-term operation, which might lead to overstressing of polymeric insulation or surface flashover. Therefore, it is of great significance to propose an effective method for dissipating extra surface charges. However, achieving charge dissipation without opening the tank is still a great challenge to SFC6-insulated equipment for a long time. In this paper, a novel method, which is named X-ray based non-contact charge dissipation method (XNCDM) for insulators in SF6-insulated equipment, is proposed. The effects of X-ray irradiation on the charges dissipation and the influences of irradiation dose were experimentally investigated in SF6. The mechanisms underlying are discussed in detail. Results show that surface charges on the insulator can be almost completely dissipated after short-time X-ray irradiation with enough dose, owing to the significant enhancement of electric conduction along the insulator surface and charge neutralization by gas ions near the gas-solid interface. This paper provides a novel technique for realizing rapid surface charge dissipation on the insulator, which is of great significance for a variety of engineering applications of DC GIS/GIL. [ABSTRACT FROM AUTHOR]

This paper investigates the capacity gain of full duplex (FD) self-backhauling over the half duplex (HD) counterpart in downlink cellular systems, and then proposes an opportunistic FD scheme. The first step is to derive the capacity gain of FD self-backhauling over the HD counterpart as a function of the system parameters in a computationally tractable form. Unlike previous studies on the capacity of FD self-backhauling, a practical constraint is imposed so that the end-to-end link achieves a target signal-to-interference-plus-noise ratio (SINR) for a successful link connection. Also, a condition under which FD is more beneficial than HD is derived. Specifically, the minimum allowable self interference cancellation factor and the maximum allowable cell radius for the benefit of FD are derived as an explicit function of system parameters. Their dependencies on the system parameters are investigated and compared with counterparts derived for single-hop point-to-point links. Lastly, to overcome the weak points of FD and HD, this paper proposes a user-wise opportunistic FD (OFD) self-backhauled scheme. To this end, an instantaneous channel gain-based FD/HD switching rule is derived from a condition under which FD cannot instantaneously satisfy the target SINR. We confirm the substantial capacity gain of the proposed user-wise instantaneous OFD over a cell-wise static duplex switching scheme, as well as the fixed duplex (HD or FD) schemes. When compared to the static duplex switching scheme, the proposed OFD is most beneficial at the boundary of HD-preferred and FD-preferred regions. Based on this, a system-level guideline is proposed for selecting the most practical scheme among OFD, FD, and HD by trading off capacity gain and switching overhead. Extensive simulation results are provided to confirm the correctness of the derivations and the related investigations. [ABSTRACT FROM AUTHOR]

This paper deals with the issue of reliable sliding mode control for descriptor systems with semi-Markov parameters using the Takagi–Sugeno fuzzy model, in which an average dwell time approach is utilized to tackle generic uncertain transition rates (TRs). From the analysis of the inner mechanism of switching singular system, a continuous sliding surface function is proposed. Different from continuity with probability one for stochastic systems, the absolute continuity of system solution is a key point in this paper being ensured for application of the average dwell time approach. Then, the mean-square exponential stability of the obtained sliding mode is analyzed based on two types of uncertain TRs. Moreover, a sliding mode controller is constructed to ensure the reachability condition in finite time. Lastly, the method is verified numerically by a single-link robot arm model. [ABSTRACT FROM AUTHOR]

In this paper, we address the adaptive neural tracking control problem for a class of uncertain switched stochastic nonlinear pure-feedback systems with nonlower triangular form. The significant design difficulty is the completely unknown nonlinear functions with all state variables that can neither be directly estimated by radial basis function (RBF) neural networks (NNs) nor be eliminated by the traditional backstepping technique. To achieve the control objective of this paper, a common state-feedback controller for all subsystems is first systematically constructed by using the common coordinate transformation, the variable separation technique, and the universal approximation capability of RBF NNs. Then the stability analysis shows that the semi-global bounded in probability of the whole closed-loop switched system can be obtained and the desired tracking performance can also be insured under a class of switching signals with the average dwell time property. Finally, simulation results are given to demonstrate the effectiveness of the obtained control scheme. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of controller design for normal nonlinear switched systems with unknown dynamics. The situation assumes that the nonlinear component of the system dynamics is unknown and there are extra uncertain terms and external perturbations affecting the system responses. Unlike previous methods that usually apply artificial neural networks to obtain an approximate model for an unknown dynamics, we use simple adaptive laws to surmount such fluctuations as well as to circumvent the steady state errors in the approaches provided by neural networks or fuzzy logics. No information on the bounds and parameters of the uncertain parts is needed. We design a twofold sliding mode control methodology to stabilize the whole switched system with arbitrary switching signals. To handle the consequences of the inherent chattering, a smooth integral type control signal is constructed. It is proved that once the system states attain the developed sliding manifold, the system becomes insensitive to both the lumped uncertainties and the dynamics of the switched system. The common assumption of a known Lyapunov functions for the subsystems is relaxed and the derived adaptive approach provides nonconservative circumstances for guaranteeing the global stability of the equilibrium state. The theoretical results of this paper are generalized for the canonical nonlinear systems with mismatched uncertainties and a novel adaptive sliding manifold is proposed to suppress the effects of the system mismatching uncertain parts. A comparative computer simulation is developed to examine the effective performance of the introduced controllers. [ABSTRACT FROM AUTHOR]

This paper proposes a novel data driven framework for detecting topology transitions in a distribution network. The framework analyzes data from phasor measurement units (PMUs) and relies on the fact that changes in network topology results in changes in the structure and admittance of the network. Using voltage and current phasors recorded by PMUs, the proposed method approximates network parameters using an ensemble-based deep learning model and thus, it does not require any knowledge of network parameters and load models. Using the prediction error of the proposed model, a connectivity matrix which shows the status of switches is constructed. In contrast to other methods, this proposed framework does not require a library of voltage and current transients associated with possible network transitions. It can also detect simultaneous switching actions and is robust to noise and load variations. The model yields a lower error detection rate, and its performance is validated using a modified version of the IEEE 33 bus network and a real feeder located in Queensland, Australia, under full and partial observability conditions. The proposed model has also been compared with another data driven method in terms of inference time and error detection rates. [ABSTRACT FROM AUTHOR]

Free viewpoint videos (FVVs) provide immersive experiences for end-users, and they have been applied in many applications, such as movies, sports, and TV shows. However, the development of quantifying the quality of experience (QoE) of FVVs is still relatively slow due to the high costs of data collection and limited public databases. In this paper, we conduct a comprehensive study on FVV QoE. First, we construct the largest, to the best of our knowledge, FVV QoE database called Youku-FVV from two complex real scenarios, i. e., entertainment and sports. Specifically, Youku-FVV originates from the videos captured by dozens of real cameras arranged annularly. We use these videos to generate virtual viewpoints, which make up FVVs together with real views. In constructing the FVV QoE database, we consider both internal and external influencing factors of QoE, which correspond to FVV generation and playback, respectively. Besides, we make an initial attempt to train an efficient no reference FVV QoE prediction model using this database, where several sparse frame sampling strategies are validated. And we demonstrate the feasibility of striving for the balance between effectiveness and efficiency of FVV QoE prediction. The proposed FVV QoE database and source codes are publicly available at https://github.com/QTJiebin/FVV_QoE [ABSTRACT FROM AUTHOR]

This paper describes new, simple, recursive methods of construction for orientable sequences, i.e. periodic binary sequences in which any $n$ -tuple occurs at most once in a period in either direction. As has been previously described, such sequences have potential applications in automatic position-location systems, where the sequence is encoded onto a surface and a reader needs only examine $n$ consecutive encoded bits to determine its location and orientation on the surface. The only previously described method of construction (due to Dai et al.) is somewhat complex, whereas the new techniques are simple to both describe and implement. The methods of construction cover both the standard ‘infinite periodic’ case, and also the aperiodic, finite sequence, case. Both the new methods build on the Lempel homomorphism, first introduced as a means of recursively generating de Bruijn sequences. [ABSTRACT FROM AUTHOR]

In this paper, we present two new families of APN functions. The first family is in bivariate form $\big (x^{3}+xy^{2}+ y^{3}+xy, x^{5}+x^{4}y+y^{5}+xy+x^{2}y^{2} \big)\,\,\vphantom {_{\int _{\int }}}$ over ${\mathbb F}_{2^{m}}^{2}$. It is obtained by adding certain terms of the form $\sum _{i}(a_{i}x^{2^{i}}y^{2^{i}},b_{i}x^{2^{i}}y^{2^{i}})$ to a family of APN functions recently proposed by Gölo&gcaron;lu. The $\vphantom {_{\int _{\int }}}$ second family has the form $L(z)^{2^{m}+1}+vz^{2^{m}+1}$ over ${\mathbb F}_{{2^{3m}}}$ , which generalizes a family of APN functions by Bracken et al. from 2011. By calculating the $\Gamma $ -rank of the constructed APN functions over ${\mathbb F}_{2^{8}}$ and ${\mathbb F}_{2^{9}}$ , we demonstrate that the two families are CCZ-inequivalent to all known families. In addition, the two new families cover two known sporadic APN instances over ${\mathbb F}_{2^{8}}$ and ${\mathbb F}_{2^{9}}$ , which were found by Edel and Pott in 2009 and by Beierle and Leander in 2021, respectively. [ABSTRACT FROM AUTHOR]

Due to the forecasted fast increasing cellular traffic and the already highly congested licensed spectrum, it is critical to exploit and utilize the unlicensed spectrum resources for the fifth-generation (5G) and beyond networks. A challenging problem is the coexistence of 5G and other networks with fair, reliable, and efficient sharing of the unlicensed spectrum. In this paper, we propose a blockchain-enhanced distributed spectrum sharing scheme for coexisting multiple operators and multiple WiFi APs. We design a novel lightweight and efficient consensus mechanism, named Proof of Strategy (PoG). In this consensus mechanism, the problem of spectrum sharing is used as a consensus puzzle, and the part of the unlicensed spectrum is used as the ‘fee’ of miners. With such a design, the computing overhead of the consensus process is expected to be reduced significantly. We develop a non-cooperative game to analyze the behavior of the miners and obtain a symmetric Bayesian Nash equilibrium under the uniform distribution of mining cost estimation. It can be found mathematically and experimentally that the strategy of the winner tends to maximize the system revenue by sharing the unlicensed spectrum resource. Furthermore, to reduce the impact of heavy interactions on system throughput, the operation of WiFi APs in the proposed scheme can be adaptively switched between ‘contention mode’ and ‘blockchain mode’ according to the network traffic load. The dynamic behavior is constructed as an evolutionary game, and the existence and uniqueness of equilibrium points are proved by theoretical analysis. Simulations demonstrated the fairness and effectiveness of the proposed blockchain-based scheme and the mode switching method for distributed spectrum sharing by heterogeneous wireless networks. [ABSTRACT FROM AUTHOR]

The use of the emerging hybrid analog-digital structure for future millimeter-wave communications has attracted much attention. Although this structure can reduce the power consumption considerably, the spatial covariance matrix (SCM), as the core of subspace-based direction of arrival (DOA) estimation algorithms, cannot be obtained directly. The beam sweeping algorithm (BSA) was proposed for SCM reconstruction from compressed measurements. However, the BSA is computationally intensive owing to the high-dimensional matrix-to-matrix multiplication and matrix inversion. To address this issue, a BSA algorithm with high accuracy and low computational-cost using the submatrix multiplication (BSASM) is proposed in this paper. By appropriately adjusting the weight, which consists of a switch and a phase shifter, connected to each antenna, the SCM can be accurately reconstructed with low-dimensional matrix-to-vector multiplication and 2-dimensional matrix inversion, thus reducing the computational-cost significantly. After SCM reconstruction, various DOA estimation algorithms can be exploited to obtain the DOA information. Simulation experiments are conducted to verify the performance of the proposed algorithm. The results indicate that using a substantially lower computational-cost, BSASM can reconstruct SCM more accurately than BSA. [ABSTRACT FROM AUTHOR]

The effect of reduction in the terminal voltage of a grid-tied inverter together with minimization in total harmonic distortion (THD) of terminal voltage and current, in the presence of dead-band in the switching remains always challenging for the researchers. With high switching frequency, this issue increases by many folds. The grid-tied inverter used for harmonic compensation acts as a shunt active power filter (SAPF). The implementation of the dead-band elimination technique is based on output current polarity detection, suffers from multiple zero-crossing due to the generation of high frequency switching harmonics during SAPF operation. This paper deals with a dead band elimination methodology together with harmonic compensation using SAPF under non-linear and unbalanced loading conditions. Here, SAPF uses a dual fundamental component extraction (DFCE) scheme with modified complex coefficient filter (MCCF) to extract fundamental components for reference current generation to implement an indirect current control PWM scheme. MCCF extracts fundamental components even in the presence of dc offset and unbalancing at the input. For incorporating dead-band elimination in control, exact polarity detection is done separately through SAPF output current estimation using sensed load current, and modified CCF computed reference source current. Since the estimated SAPF output current contains no high-frequency switching harmonics, the dead-band elimination technique can be correctly implemented. To synchronize the zero-crossing of the estimated and actual SAPF current, an adaptive delay control is used. The proposed MCCF based control logic’s performance together with the dead-band elimination technique is validated for SAPF operating under non-linear, unbalance, and dynamic load conditions. The proposed dead-band elimination scheme based SAPF model is developed and simulated using MATLAB/ SIMULINK. The simulation results show a significant reduction in source current harmonics due to the elimination of odd harmonic injection into the system by incorporating dead-band elimination in SAPF operation. The real-time simulation of the proposed method is also validated using OPAL-RT OP4510 real-time platform. [ABSTRACT FROM AUTHOR]

The missing capability of DC fault current limitation is an inherent disadvantage in the typical half-bridge modular multilevel converter (MMC), which restricts its application in long-distance high voltage direct current (HVDC) systems. The full-bridge submodule (FBSM) and clamped double submodule (CDSM) topologies allow for fault current self-clearing, but also suffer from additional hardware cost and power losses. In this paper, an improved submodule topology utilizing the new reverse-blocking insulated gate bipolar transistor (RB-IGBT) is proposed to improve system economy without compromising its performance. The operating principles and DC fault characteristics of the proposed topology are analyzed in details, including comparison with various topologies in terms of cost, losses, fault current clearing speed and thermal. Compared with the traditional CDSM topology, the proposed RBSM can clear DC faults faster with reduced cost of switching devices. A DC fault protection strategy for MMC-HVDC system is also presented. Simulation results under normal operating, permanent and transient fault conditions are carried out to verify the effectiveness of the proposed topology. [ABSTRACT FROM AUTHOR]

The conventional model predictive power control suffers from heavy computational burden and large power ripple. To address the problem, this paper proposes a simplified three-vector-based model predictive direct power control, which can greatly optimize the control set. Firstly, a switching table is designed to exclude the redundant virtual voltage vectors (VVs). Only half of the candidate VVs are retained. Then, the effect of each VV on power is analyzed in detail. The deviation of reactive power is used as the evidence to further simplify the control set. In this way, the prediction behavior is reduced from 12 to 2, which effectively reduces the computational burden. In addition, the concept of power deadbeat is employed to determine the duty cycles of the two virtual VVs and one zero VV. Thus, the power ripples and current harmonics can be considerably suppressed. With this proposed method, the calculation complexity is reduced, and the steady-state performance is improved. The simulation and experimental results are given to verify the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a finite-control-set model predictive direct torque control (FCS-MPDTC) method is proposed to reduce the torque ripple of a segmented switched reluctance motor (SSRM) at the low-speed stage. Firstly, the prediction dynamic model is established, and the phase torque can be predicted by detecting phase current and rotor position signals. Then, the principle of power converter and selection of voltage vectors are introduced and presented. Considering torque ripple reduction, flux tracking performance and copper losses reduction, the cost function with phase torque, the amplitude of flux linkage and phase current, is established to select optimal voltage vector to control the power converter. In addition, the torque sharing function (TSF) is employed to distribute total torque to phase torque for further torque ripple reduction. Finally, the direct torque control (DTC) is selected as the comparison method, performance of MPDTC is verified by simulation and experiment results. It can be found that the proposed MPDTC can achieve lower torque ripple and copper losses, and high robustness. [ABSTRACT FROM AUTHOR]

This paper presents a dual-hysteresis band control method for multi-drive systems based on a nine-switch inverter. The drive system contains two independent three-phase induction motors fed by a nine-switch inverter. Independent control of torque, speed, and stator current of two load stages is achieved. The proposed strategy offers a reliable control operation of both induction machines under individual load profiles. Instead of using independent sets of three-phase voltage source converters, the nine-switch inverter is used to drive separate machines. Thus, the volume and size of the power stage are noticeably reduced due to the use of fewer semiconductors. The theoretical concept and design steps of the proposed method are presented. The performance of the closed-loop independent motor control scheme is experimentally validated using a 3.2 kW lab-scaled nine-switch inverter prototype and Altera Cyclone IV Field-programmable gate array. [ABSTRACT FROM AUTHOR]