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An improved two-stage model predictive current control (MPCC) for three-phase three-level converters in the paper, which can simultaneously achieve common-mode voltage (CMV) reduction, effective dc-link capacitor voltage control, and decreased computational burden, is proposed. Compared to the other current control strategies, it has the capability of handling multiple control objectives and possesses a simple structure. Furthermore, it greatly reduces the CMV since the peak CMVs of all the candidate voltage vectors are constrained to be less than one sixth of the dc-link voltage. In addition, an optimal two-stage voltage vector selection mechanism is employed in the proposed method. It helps to significantly reduce the computational complexity. Simulation and experimental results are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents Space Vector Modulation (SVM) sequences that reduce Common Mode Voltage (CMV) in Dual Three-phase Asymmetrical Induction Motor (DTAIM). At first, two existing SVM techniques such as Reference SVM (RSVM) and CMV1 are studied. Additionally, three new switching sequences are developed as CMV2, CMV3 and DCMV3, which reduce peak magnitude of CMV by 66.8% in comparison with RSVM technique. In SVM techniques, to obtain least CMV, zero vectors are usually replaced by two opposite large Active voltage Vectors (AV) with equal time duration. In such topologies like CMV1, total six AVs are utilized to synthesize the reference vector. The proposed SVM technique CMV2 utilizes only five large AVs to synthesize the reference vector and reduces CMV. Selection of five neighbouring AVs is reflected in reduction of harmonic flux trajectories and stator current ripple in proposed techniques. Additionally, two more switching sequences (CMV3 and DCMV3) are developed related to utilization of specific zero voltage vectors in all sectors (7 and 56) that produce zero CMV. These two switching sequences also provide easy implementation feature during the development of c-code program. In this study, CMV and stator current ripple are considered as performance parameters for different SVM techniques. All SVM techniques are analysed by analytical results, computer simulations, and using prototype test setup of DTAIM fed by Dual Three-phase Voltage Source Inverters (DTVSIs). [ABSTRACT FROM AUTHOR]

This paper presents a different Finite Control Set – Model Predictive Control (FCS-MPC) for grid-connected three-phase bidirectional power inverters. These are typically used in dc or ac renewable-based microgrids (MGs), where bidirectional operation and fast dynamic response is required. The bidirectional grid-connected inverters are an essential part of MG, which inject energy into the ac grid or demand energy from it. The dynamic behavior of the system is a major concern since the current can suddenly change depending on the hierarchical controller. This paper proposes a different cost function using sliding mode theory, which offers a good dynamic response, reduced computational burden, and a parameter-free control model. The operation principle of the proposed controller is given and evaluated using a Hardware-In-the-Loop (HIL) system, but also experimentally with a 1kW laboratory prototype. The final results demonstrate the advantages of using this approach in grid-connected three-phase bidirectional power inverters in terms of dynamic response and reduced computational burden, making this solution technically attractive and viable. [ABSTRACT FROM AUTHOR]

In a previous paper (Part 1) the authors have performed the simulative evaluation of the life lost by HVDC extruded cables subjected to long TOVs occurring in VSC HVDC cable systems. The conclusions were that it cannot be completely ruled out that the field levels and the duration of such TOVs are a potential threat to certain cable designs, and tests other than Load Cycling Type Tests after CIGRÉ Technical Brochure 496 could assess quantitatively the potential threat associated with long TOVs. For these reasons, in this Part 2 superimposed switching impulses applied during Type Tests after TB 496 are analyzed in order to check if such impulses might be equivalent to long TOVs as for their electro-thermal stress effects on extruded insulation. The analysis is similar to that carried out for long TOVs in Part 1, i.e., it consists of: calculating the electric field during superimposed switching impulses; comparing it with the field during long TOVs; calculating with Miner's law of cumulated damage the life lost during superimposed switching impulses and comparing it with the loss of life during TOVs. A brief literature survey of potential high field effects during long TOVs is also reported. [ABSTRACT FROM AUTHOR]

Micro-electromechanical systems (MEMS)-based devices comprise suspended structures. A sacrificial layer is required to realize these structures. Usually, metal and dielectric materials are used as sacrificial layer materials. Metallic sacrificial material has a selectivity problem, whereas dielectric materials require higher deposition temperatures. Hence, in the present paper, photoresist (PR) material is used as the sacrificial layer. PR requires low-temperature processing and has no selectivity issues. Hence, photoresists are preferred as sacrificial layer materials. In the CMOS fabrication process, thin photoresists such as S1818, S1813, and AZ1505 are used. In these photoresists, the processing wafers are placed in a vertical position during patterning, which occupies less space. The recipes of such photoresists are well optimized for a uniform thickness across the wafer. However, special thick photoresists are used as a sacrificial layer for MEMS devices. These thick photoresists reflow in the vertical position and lead to non-uniform thickness; consequently, the yield is decreased. This paper has optimized a special thick photoresist (HiPR 6517) for RF MEMS SPST switches for better yield and uniformity. The measured pull-in voltage and the switch's resonant frequency are 13.00 V and 12.32 kHz, respectively. The fabricated switch offers isolation and insertion loss better than − 35 dB and − 1 dB at 24.5 GHz, respectively. [ABSTRACT FROM AUTHOR]

This paper presents an isolated single-stage on-board electric vehicle charger without an intermediate DC-link. Based on an isolated current-source topology, the converter features soft-switching in semiconductors regardless of load variation for the full AC line voltage range. Moreover, it requires no external snubber or clamp circuits. The power factor correction and voltage regulation are provided by a relatively simple phase shift modulation, while the amount of circulating energy is kept at minimum. The charger is distinguished by its efficiency characteristic – the maximum is achieved in the constant power charging mode. The control method, component stresses, and design constraints of the topology are analyzed. The concept is verified using a 3 kW experimental SiC-based prototype, which reaches a peak efficiency of 96.4%. Moreover, the charger has demonstrated efficiencies above 95% with the THD of 4.1% when operating in constant power mode at the maximal power. [ABSTRACT FROM AUTHOR]

Mobile edge computing becomes a promising technology to mitigate the latency of various cloud services. In addition, network function virtualization (NFV) has been shown a great potential in reducing the operational cost of cloud services while enhancing the flexibility of virtual network function deployments, by implementing dedicated hardware network functions as pieces of software in generic servers. Recently, the GPU acceleration has been investigated to speed up flow processing in virtual network functions (VNFs), by leveraging the parallelism of GPUs. VNFs that need accelerations prefer to stay at cloudlets (locations) equipped with GPUs. However, little attention has been paid for the VNF placement that takes into account GPU-affinity in cloudlets of mobile edge clouds. In this paper, we consider the affinity-aware throughput maximization problem in a mobile edge cloud via leveraging the parallelism on GPUs for user requests with VNF requirements. We consider two types of affinities in the VNF placement: The soft-affinity that allows VNFs to be executed by either CPUs or GPUs in cloudlets; and the hard-affinity that only allows VNFs to be placed to the GPUs of a specified set of cloudlets. We formulate two corresponding VNF placement problems in a mobile edge cloud. Specifically, we first propose an exact solution to the soft-affinity throughput maximization problem by formulating an Integer Linear Program (ILP). We then propose an efficient algorithm for the problem, by proposing a randomized algorithm with a provable approximation ratio for the hard-affinity-aware throughput maximization problem and extending the proposed approximation algorithm to the soft-affinity throughput maximization problem. Furthermore, assuming that user requests arrive into the mobile edge cloud one by one without the knowledge of future arrivals, we devise an online algorithm with a good competitive ratio for this dynamic hard-affinity-aware throughput maximization problem. Finally, we evaluate the performance of the proposed algorithms, through simulations and implementations in a real test-bed. Experimental results show that the performance of the proposed algorithms outperform their existing counterparts and achieve higher throughput. [ABSTRACT FROM AUTHOR]

The electromagnetic repulsion model of 400 V/630 A/12.5 kA fast vacuum transfer switch (FVTS) is established using finite element method. The speed and characteristics of the contact bounce of the FVTS are taken as constraints, and the objective is to keep the reliable opening of the mechanism with allowable bounce. The deceleration of the fast operating mechanism in the process of opening and closing is realized by applying the reverse electromagnetic repulsion force. Moreover, the simulation results demonstrate that the electromagnetic buffer effect is available, and the allowable bounce opening of the operating mechanism has been obtained. Furthermore, this paper compares the buffering effects of three kinds of conditions, such as no electromagnetic buffering, 110 V electromagnetic buffering and 220 V electromagnetic buffering. It can be found that the electromagnetic buffering is a necessary part of the 400 V FVTS, and the dynamic characteristics are the optimal scheme when the 220 V electromagnetic buffering is applied. Based on the results of simulation, a FVTS experimental prototype is developed to prove the effectiveness of the design scheme. [ABSTRACT FROM AUTHOR]

Identifying the location of partial discharges (PDs) and providing clear information on insulation vulnerabilities in power systems can help utility companies to improve their maintenance efficiency. This paper presents a PD monitoring and locating system for medium-voltage switchgears using a set of transient earth voltage (TEV) detectors. A time-of-flight methodology was used to identify the switchgear affected by PD among a row of switchgears. A time sharing access mechanism, which was implemented by multiple high-frequency surface mounting relays integrated into each TEV detector, was applied to automatically identify the site of PD and minimize the number of expensive high-speed acquisition cards. The operation principle and implementation of the modular system were formulated, and the efficiency of the proposed system in identifying the switchgear with PD among three 10 kV metal-clad switchgears was confirmed experimentally. [ABSTRACT FROM AUTHOR]

The implementation of finite-control-set model predictive control (FCS-MPC) in voltage source inverters (VSIs) can make the system suffer from poor current harmonics performance, which may complicate the design of the required AC filter. To overcome this shortcoming, a carrier-based modulated model predictive control (CB-MMPC) strategy is proposed in this paper. This method enables the utilization of existing PWM modulation techniques with FCS-MPC, where a modulation waveform with zero-sequence signal injection is generated and compared to a triangular carrier wave, while optimizing the selection of the switching states. As it is shown, the studied CB-MMPC strategy not only considerably improves the current total harmonic distortion (THD) but also attains the performance of fast current dynamic response and robustness as the traditional FCS-MPC. Herein, the detailed implementation of the CB-MMPC control strategy is given, while considering its application to the current feedback control loop of a three-phase three-wire two-level VSI modulated at constant switching frequency. Finally, PLECS circuit simulation and a 3-kW VSI prototype are used to verify the superiority and the effectiveness of the presented CB-MMPC strategy. This is also benchmarked to the FCS-MPC and dead-beat based controllers. [ABSTRACT FROM AUTHOR]

Conventional model predictive control (MPC) for three-level active neutral point clamped converter (ANPC) utilizes weighting factors to achieve the optimal control of multiple control objectives in a single cost function. However, the selection of these weighting factors has an impact on the performance of the controlled objectives significantly. Tuning of weighting factors is usually tedious and lacks theoretical background. Moreover, the predictive and evaluation process for multiple objectives optimization have to be carried out by enumerating all admissible switching states within one loop. To simplify the complexity of this process and eliminate the effect of weighting factors, this paper proposes a cascaded predictive control scheme for a 3L-ANPC inverter fed induction machine (IM) drive. With the proposed approach, three separate cost functions for three control objectives, stator flux vector, neutral point voltage and device loss distribution are evaluated in a cascaded way, so that the optimization of these control objectives is performed independently. A 3L-ANPC inverter driven IM drive is studied in this paper to verify the effectiveness of the proposed algorithm. Experimental results in different operating conditions confirm that the proposed method achieves satisfactory steady-state and transient performances comparable to the conventional predictive control approach. The weighting factors used in the conventional method are eliminated and the computational effort is reduced by 68% compared to the conventional method without any sacrifice in the drive performance. [ABSTRACT FROM AUTHOR]

Operational performance in the low-voltage distribution network (LVDN) can be undermined by its inherent unbalances, which may become worse as the penetration of rooftop solar continuously increases. To address this issue, load balancing via phase-reconfiguration devices (PRDs), which can change phase positions of residential customers as required, provides a cost-efficient option. However, most reported approaches to control PRDs require that demands of all residential customers are available, which are not viable for many LVDNs without smart meters or advanced metering infrastructure (AMI) installed. To bridging the gap in this field, this paper proposes a novel method to control PRDs purely based on measurable data from PRDs, and its controller. Based on limited information, sensitivity analysis in the network with PRDs is studied, followed by the optimization model that comprehensively considers operational requirements in the network. Moreover, slack variables are introduced to the model, and penalized in the objective function to assure either a strategy that is secure or with minimized violations can always be provided. The model is a challenging mixed-integer non-convex programming (MINCP) problem, which is reformulated as an efficient solvable mixed-integer second-order cone programming (MISOCP) based on exact reformulations or accurate linear approximations. Simulations based on two modified IEEE systems, and a real system in Australia demonstrate that an efficient strategy can be provided to mitigate unbalances in the network. [ABSTRACT FROM AUTHOR]

For Electro-Magnetic-Transient (EMT) simulations of power networks with switches, techniques such as linear interpolation and Critical Damping Adjustment (CDA) are widely used for improving numerical robustness. This paper analyzes the numerical stability of simulations with these techniques. Firstly, it is mathematically shown that the interpolation or CDA step is equivalent to the introduction of additional switching states. Subsequently, Common Quadratic Lyapunov Function (CQLF) theory is used to investigate the numerical stability of the whole simulation considering these new switching states. It is proved that the widely used strategies like linear interpolation and CDA always result a stable simulation if the original switched system is strictly passive in all switching states. Finally, it is shown that the developed approach can be used to determine the stability of other practical interpolation methods. Examples are provided to verify the proposed technique. [ABSTRACT FROM AUTHOR]

Natural calamities always have been a serious threat to energy systems. In this regard, this paper constitutes a stochastic mixed integer linear programming (SMILP) model to enhance the resilience of power distribution systems to deal with disastrous events. In particular, the proposed model is developed to enhance both survivability and restoration capability of distribution systems. In this regard, to increase the preparedness of the power distribution system, the system operator reconfigures the network by utilizing remote-control switches (RCSs), manual switches (MSs), and distributed generations (DGs) before the natural calamity hits. The proposed model contemplates the traveling time of crew teams to the MS sites in the transportation system in order to achieve the best switching sequence. In addition, it pre-positions the crews and mobile emergency generators (MEGs) in staging locations to hasten the likely post-disturbance operations. To do so, likely post-event operations are included in the model using the scenario generation technique. To validate the performance of the developed model a distribution system is employed. The results of simulations confirm the effectiveness of the proposed approach in declining the interruption of electric energy for customers. [ABSTRACT FROM AUTHOR]

In photovoltaic systems, common-mode voltage (CMV) generates leakage current, which shortens the insulation lifespan and causes safety problems. As for neutral-point-clamped (NPC) inverters, zero CMV PWM (ZCMV PWM) can be implemented to eliminate leakage current, but unable to balance neutral-point (NP) voltage in dc side. This article presents a novel modulation technique for NPC PV inverter. The strategy contains ZCMV PWM and another two modulation modes which keeps CMV constant in one switching period, so as to eliminate leakage current. In order to balance NP voltage, NP current is adjusted by selection of optimal modulation mode and the leakage current is still well eliminated during the process of balancing NP voltage. Compared with conventional ZCMV PWM, the proposed scheme can remove both leakage current and NP voltage deviation. The output performance and limitations of the proposed method are also introduced in the paper. Experiments are provided to verify the validity of the proposed method. [ABSTRACT FROM AUTHOR]

In recent years, very high frequency (VHF) converter has attracted much attention. However, with rich parasitic parameters and complex resonance links, there are some great difficulties to the modeling of such systems. Taking the on-off controlled VHF resonant boost converter as an example, this paper presents an accurate modeling and analysis method that considers multiple parasitic parameters. First, the closed-loop VHF converter system is divided into a main network and a parasitic oscillation network. Then, based on the operation analysis, an equivalent circuit model characterized by a time-varying input voltage source and two variable duty-cycle controlled switches is proposed. It worth noting that both the time-varying input and the controlled switches take into account the influences of the parameters. Furthermore, the periodic approximate analytical solution of the output voltage in the on stage is obtained by using the equivalent small parameter method to the proposed circuit model. And then combining the solution of the parasitic oscillation network and on-off state switching conditions, the steady-state waveform of output voltage can be obtained quickly. Finally, a prototype with operating frequency of 21.44 MHz is built to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The capacitor condition monitoring is an important issue for the reliable operation of modular multilevel converters (MMCs) in high-voltage applications. The numerous capacitors make the monitoring for the capacitor condition complex and computation-consuming. This paper proposes a hierarchic capacitor condition monitoring strategy to assure the reliability of high-voltage MMCs. In the strategy, the switching times of the switching signals are counted to detect the condition of the capacitor in each submodule (SM). Then, the subsequent capacitance calculation method is only conducted to the abnormal capacitors indicated by the above condition detection algorithm. Meanwhile, the variations of the measured and reference capacitor voltages are employed to calculate the capacitance in the proposed method. The condition detection algorithm shrinks the scope where the abnormal capacitors locate, which avoids calculating the total capacitances in MMCs. In the proposed capacitance calculation method, the complex operations are further saved. Both the two measures reduce the computation burden effectively. The implementation of the whole monitoring strategy is simple and fit for high-voltage MMCs. Moreover, the strategy has no adverse influence on the normal operation of MMCs. The effectiveness of the proposed strategy is verified by the simulation studies with the professional tool Matlab/Simulink. [ABSTRACT FROM AUTHOR]

High-performance multicast packet switching technologies are evolving to meet the growing demand for scalability on the Internet and datacenters, etc. Implementing a high-performance switch/router relies on a polynomial-time group membership query algorithm within the Packet Forwarding Engines (PFEs) to determine whether a packet is forwarded through an egress. Among these, Bloom filter (BF)-based and Residue Number System (RNS)-based are being considered as two representatives of the membership query algorithms. However, both approaches suffer from some fatal weaknesses such as false-positive probability and time inefficiencies, especially for a carrier-grade PFE with high port-density features. According to similar properties of the RNS, we propose a simplified forwarding algorithm in this paper, named Per-Port Prime Filter Array (P3FA). The simulation results indicate that the P3FA can significantly improve space efficiencies under specific lower egress-diversities conditions. Under the same space constraints, P3FA improves multicast and unicast time efficiency by 1 to 4 orders of magnitude in the port-density 16–1024 range compared to previous works. Although it comes at the expense of hardware cost, it is still acceptable compared to recently improved previous work. [ABSTRACT FROM AUTHOR]

This paper presents a novel active power control scheme for SRMs that are used as S/G units at MEAs; the proposed method uses a vector-controlled SAF, facilitating the acceleration of the SRM during starter mode and the efficient power control of the SRG at various operational points during generator mode. Moreover, an energy storage unit is incorporated in the SAF, aiming at enhancing the SRM's starting torque production and taking full advantage of the SRG's energy generation capability, through the appropriate phases’ magnetization regulation that is imposed by the developed adaptive SAF vector control. In addition, the proposed scheme provides enhanced FRTC during both modes of operation. The mathematical analysis is verified through MATLAB/Simulink simulations, while the performance of the S/G concept under study is evaluated via real-time CHIL tests, with the use of the dSPACE 1202 (MicroLabBox) platform and the 16-bit dsPIC30F4011 microcontroller. [ABSTRACT FROM AUTHOR]

Emerging device-based digital processing-in-memory (PIM) architectures have been actively studied due to their energy and area efficiency derived from analog to digital converter (ADC)-less PIM hardware. However, digital PIM architectures generally need large extra memories to copy parameters, and they also suffer from low computation per memory-cycle efficiencies. In this paper, we present a novel spin-orbit torque magnetic random access memory (SOT-MRAM) based digital PIM architecture to alleviate the extra memory size burden and computation cycle issues. First, we propose the spintronics-assisted logic-in-memory (SLIM) cells to support efficient digital logic operations inside memories, where the voltage-controlled magnetic anisotropy (VCMA) is exploited to enhance the computation per memory-cycle efficiencies. In addition, crossed input source PIM (CRISP) architecture is proposed to extend the merits of SLIM cells by eliminating the extra memories for parameter copying while significantly improving the degree of parallel processing. An intra-memory pipelining scheme is also considered to further increase the throughput of CRISP. The proposed CRISP architecture has been implemented using 28 nm CMOS process, and it presents 1.10 TOPS/W and 0.95 TOPS/mm2, showing considerable improvements of energy efficiency and throughput per area, compared to the state-of-the-art digital PIM architecture. Finally, to evaluate the impact of computation errors induced from the SOT devices and circuits in CRISP architecture, classification accuracy simulations have been performed while applying computation errors. [ABSTRACT FROM AUTHOR]

The modular multilevel converter (MMC), owing to the presence of a large number of submodules (SMs) and energy storing elements, requires a large footprint and initial investment. To address these issues, this paper proposes the switched modular multilevel converter (SMMC). It consists of two major elements; the chain-links (CLs), consisting of cascade connection of SMs as in MMC, and the single-pole-triple-throw (SPTT) switches, which can be realized using either the T-type or NPC-type switch strings. The SMMC works on the principle of connecting all the phase-legs in series and their respective positions are mutually interchanged. It offers a compact structure as the SMs count is reduced to 33% of MMC, which results in a much lower energy storage requirement. Furthermore, it does not have inter-phase circulating current problem and hence the CL inductors can also be avoided. The SMMC structure, operating principles, control, and modulation schemes are explained in detail. A detailed comparison of SMMC with the other major existing converters is carried out to highlight the important features of SMMC. The efficacy of SMMC is validated using PSCAD simulation studies with a 19-level grid-connected SMMC model. A 3-phase 19-level SMMC laboratory prototype is developed to further validate its feasibility. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMCs) in high- voltage applications contain large numbers of power switches, which increases the fault probability inside MMCs. This paper proposes a detection method for the faulty arm containing switch open-circuit failures in high-voltage MMCs to improve the reliable operations of MMCs. The proposed method uses the periodicity of the deviation between the maximum and minimum capacitor voltages to provide the detection reference. To yield a reliable reference, the repetitive signal generator is employed. Then, the fault is identified by the difference between the referenced and measured capacitor voltage deviations. An auxiliary criterion is also designated to avoid the false detection caused by the mutations in MMCs. The proposed method can reduce the difficulty in the selection of thresholds. Moreover, the proposed method is robust in high-voltage MMCs with inferior capacitor voltage balancing performance, which ensures detection rapidity and accuracy. Finally, the feasibility of the method is verified by simulation results in Matlab/Simulink. [ABSTRACT FROM AUTHOR]

Piezoelectrically actuated fast mechanical switches provide a low-loss conduction path in hybrid circuit breakers for protecting medium-voltage direct-current systems. As the desired actuation speed approaches the driving limit of a piezoelectric actuator, excessive vibration starts to dominate its underdamped travel curves, resulting in insulation failures and delayed switching in the fast mechanical switch. To improve the underdamped travel curves into critically damped travel curves, several switching motion control schemes with active damping filters are proposed in this paper. The switching motion controllers are based on an electromechanical model of a fast mechanical switch with experimentally identified parameters. According to hardware implementation tests, the proposed closed-loop control schemes optimized the switch travel curves with a 56% reduction in the undershoot and a 75% reduction in the settling time. Equipped with the critically damped travel curves, the piezoelectrically actuated fast mechanical switch is better suited for sequential submodule operations to reduce the interruption time, the peak current and the fault energy to be absorbed in hybrid circuit breakers. [ABSTRACT FROM AUTHOR]

Uncertainties in power system studies are typically managed by Monte Carlo methods or by applying some worst case assumptions. As the number ofuncertainties increases, there is a need for methods that can estimate statistical parameters from a limited number of calculations. This paper utilizes a method called the Unscented Transform together with Cornish-Fisher expansion to estimate the 2%-value of switching overvoltages using only about one tenth the number of calculations as a Monte Carlo method, with similar accuracy. The uncertainties considered are the energizing instants of the three phases. The method is illustrated through EMT simulations in PSCAD and it is shown to provide a good approximation of the 2%-value in most of the studied cases. [ABSTRACT FROM AUTHOR]

In this paper, we address the finite-time and fixed-time synchronization of a general class of switched neural networks (SNNs) with time delays subject to stochastic disturbances. Considering two types of switching in this class of SNNs: 1) intra-SNN state-dependent switching and 2) inter-SNN Markovian switching, we develop three control laws and derive three sets of sufficient conditions for both finite-time and fixed-time synchronization of SNNs subject to stochastic disturbances. We make two remarks on the effects of control-law parameters on synchronization settling time. Moreover, we derive several upper bounds of synchronization settling time and evaluate their pros and cons. Finally, we elaborate on two numerical examples to illustrate the viability of the theoretical results. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Controlling several joints simultaneously is a common feature of natural arm movements. Robotic prostheses shall offer this possibility to their wearer. Yet, existing approaches to control a robotic upper-limb prosthesis from myoelectric interfaces do not satisfactorily respond to this need: standard methods provide sequential joint-by-joint motion control only; advanced pattern recognition-based approaches allow the control of a limited subset of synchronized multi-joint movements and remain complex to set up. In this paper, we exploit a control method of an upper-limb prosthesis based on body motion measurement called Compensations Cancellation Control (CCC). It offers a straightforward simultaneous control of the intermediate joints, namely the wrist and the elbow. Four transhumeral amputated participants performed the Refined Rolyan Clothespin Test with an experimental prosthesis alternatively running CCC and conventional joint-by-joint myoelectric control. Task performance, joint motions, body compensations and cognitive load were assessed. This experiment shows that CCC restores simultaneity between prosthetic joints while maintaining the level of performance of conventional myoelectric control (used on a daily basis by three participants), without increasing compensatory motions nor cognitive load. [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]

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]

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]

Consistent distribution of shadows on the surface of the shaded PV array enhances the array’s harvested capacity. Therefore, in this paper, an Image processing inspired Chaos Map reconfiguration is proposed to mitigate the effect of shading. The proposed reconfiguration is aimed at achieving uniform row current when compared with the other conventional configurations with physical relocation of panels without changing the electrical connections. The efficacy of the proposed method is tested on Short Wide, Short Narrow, Long Wide and Long Narrow shading conditions on the basis of both software and hardware results. The proposed method enhanced output metrics under partially shaded conditions and gives most effective dispersion of shading over entire PV array. This proposed method is also compared with other existing static reconfiguration techniques for the above said shading conditions and the results show tremendous increment in output power under both hardware and software platforms. The results replicate that the proposed configuration can be generalized for any size of an SPV Array and output parameters can be enhanced by physical relocation under any sort of shading conditions. [ABSTRACT FROM AUTHOR]

The main challenges for Finite Set-model Predictive Torque and Flux Control (MPTC) include huge calculation amount, large torque ripple, and the selection of weighting factor. To deal with these challenges and achieve the fastest torque response, a novel MPTC strategy with virtual voltage vector-based pattern is proposed in this paper. In each control period, a desired voltage vector is computed based on the maximum torque variation rate. The virtual desired voltage vector is combined by using basic voltage vectors with the minimum switching times. The switching pattern between two adjacent control periods is optimized by using a cost function in realtime. Compared with the traditional MPTC approach, the novel strategy has multifaceted improved performances: faster torque response, less calculation amount, lower switching frequency, reduced torque ripple, higher efficiency and no weighting factor. The proposed method is contrasted with traditional MPTC method and a well-known generalized multiple-vector-based MPC method via experiments. [ABSTRACT FROM AUTHOR]