This paper analyzes the stability problem of the grid-connected voltage-source inverter (VSI) with LC filters, which demonstrates that the possible grid-impedance variations have a significant influence on the system stability when conventional proportional-integrator (PI) controller is used for grid current control. As the grid inductive impedance increases, the low-frequency gain and bandwidth of the PI controller have to be decreased to keep the system stable, thus degrading the tracking performance and disturbance rejection capability. To deal with this stability problem, an H∞ controller with explicit robustness in terms of grid-impedance variations is proposed to incorporate the desired tracking performance and the stability margin. By properly selecting the weighting functions, the synthesized H∞ controller exhibits high gains at the vicinity of the line frequency, similar to the traditional proportional-resonant controller; meanwhile, it has enough high-frequency attenuation to keep the control loop stable. An inner inverter-output-current loop with high bandwidth is also designed to get better disturbance rejection capability. The selection of weighting functions, inner inverter-output-current loop design, and system disturbance rejection capability are discussed in detail in this paper. Both simulation and experimental results of the proposed H∞ controller as well as the conventional PI controller are given and compared, which validates the performance of the proposed control scheme.
Current-fed quasi-Z-source inverter has many advantages when it is used in the vehicle motor drive: it has buck-boost function with single stage; it has regeneration capability; it protects the open circuit by itself. This paper is to demonstrate that this inverter also has fast transient response that it only needs several switching cycles to transfer from motoring mode to regeneration mode, which makes it very suitable to be used for HEV or EV motor drive. Theory analysis, simulation results and experimental results are all given to demonstrate it.
The grid-connected inverter works as a controlled current source in grid-connected mode, while operates as a controlled voltage source in standalone mode. So in case of utility faults or intentional islanding, the inverter has to change its control strategy from current control to voltage control. This paper first proposed a multi-loop voltage controller with capacitor differential voltage feedback inner loop and voltage reference feedforward for standlone system especially designed to maintain the voltage continuity and decrease the dynamic response time in transition. However, the turn-off characteristics of the SSR which is used as switch here makes the transition last for a long time up to half a cycle. So in order to force the grid currents through the SSR switches to decrease to zero at much less time and make the voltage fluctuates within permissible levels during SSRs turnoff period, the voltage control based voltage amplitude regulation, instantaneous voltage regulation algorithms and current control based zero current regulation algorithms have been adopted in transition. After disconnection from the grid, the inverter will recover its voltage to a rated level. Simulation and experiments are carried out to verigy the proposed controllers and algorithms.
Intentional islanding describes the condition in which a microgrid, which consists of a load and a distributed generation (DG) system, is isolated from the remainder of the utility system. In this situation, it is important for the microgrid to continue to provide adequate power to the load. Under normal operation, each DG inverter system in the microgrid usually works in constant current (or constant power) control mode in order to provide a pre-set power to the main grid. When the microgrid is cut off from the main grid, each DG inverter system must detect this islanding situation and switch to a voltage control mode. In this mode, the microgrid will provide a constant voltage to the local load. This paper describes a control strategy to implement intentional islanding operation of microgrids. The described method proposes two control algorithms, one for grid-connected operation and the other for intentional islanding operation.
Crowd behavior analysis has recently attracted extensive attention in research. However, the existing research mainly focuses on investigating motion patterns in crowds, while the emotional aspects of crowd behaviors are left unexplored. Analyzing the emotion of crowd behaviors is indeed extremely important, as it uncovers the social moods that are beneficial for video surveillance. In this paper, we propose a novel crowd representation termed crowd mood. Crowd mood is established based upon the discovery that the social emotional hypothesis of crowd behaviors can be revealed by investigating the spacing interactions and the structural levels of motion patterns in crowds. To this end, we first learn the structured trajectories of crowds by particle advection using low-rank approximation with group sparsity constraint, which implicitly characterizes the coherent motion patterns. Second, rich emotional motion features are explicitly extracted and fused by support vector regression to reflect social characteristics. In particular, we construct weighted features in a boosted manner by considering the features' significance. Finally, crowd mood is intuitively presented as affective curves to track the emotion states of the crowd dynamics, which is robust to noise, sensitive to semantic shift, and compact for pattern expressions. Extensive evaluations on crowd video data sets demonstrate that our approach effectively models crowd mood and achieves significantly better results with comparisons to several alternative and state-of-the-art approaches for various tasks, i.e., crowd mood classification, global abnormal mood detection, and crowd emotion matching.
Abstract Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.
$LLC$ and $CLLC$ resonant converters are good candidates for the isolated dc–dc stage in electric vehicle (EV) onboard chargers (OBCs) due to their capability of achieving zero-voltage-switching (ZVS) at full load range. The synchronous rectifier (SR) is usually utilized to reduce the conduction loss and improve the system efficiency compared with the conventional diode bridge rectifier. In this article, a high-dv/dt-immune, fine-controlled, and parameter-adaptive gate driving scheme is presented for GaN-based SR in EV OBCs. A novel self-driven SR drain-to-source voltage sensing circuit is proposed. The circuit provides a low-impedance bypassing path for the displacement current induced by the high dv/dt, which addresses the overvoltage and oscillation issues for the controller input. The detailed operating principles and the design considerations of the novel sensing circuit are discussed as well. Moreover, the adaptive SR ON-time tuning algorithm is implemented, which avoids the influence from the loop stray inductance and the propagation delay in the path and reaches the SR zero-current turn-off moment with fine accuracy. A 3.3-kW, 500-kHz $CLLC$ resonant converter prototype is built to validate the proposed SR gate driving scheme. With the employment of the proposed gate driving scheme, the SR almost achieves zero-current turn-off for the whole operating frequency range. The prototype demonstrates the peak efficiency of 97.6% and the power density of 130 W/in 3 .
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