A Novel Simulation Method for Power Electronics: Discrete State Event Driven Method

In the analysis of power electronics system,it is necessary to simulate ordinary differential equations(ODEs)with discontinuities and stiffness.However,there are many difficulties in using traditional discrete-time algorithms to solve such equations.Kofman and others presented the quantized state systems(QSS)algorithm in the discrete event system specification(DEVS)formalism.The discretization is applied to the state variables instead of time range in QSS.QSS is efficient to solve ODEs,but it is difficulty to be used when simulating actual power electronics systems with controller’s and other events.Based on the idea of this numerical algorithm and discrete event,a Discrete State Event Driven(DSED)simulation method is presented in this paper,which is fit for simulation of power electronics system.The method is developed to deal with non-linearity,stiffness and multi-time scale of power electronics systems.The DSED simulation method includes event definition,module seperation and modeling,event-driven mechanisms,numerical computation based on QSS,and some other operations.Simulation results verified the effectiveness and validity of the proposed method.

Event-driven process execution model for process virtual machine

Current orchestration and choreography process engines only serve with dedicate process languages.To solve these problems,an Event-driven Process Execution Model(EPEM) was developed.Formalization and mapping principles of the model were presented to guarantee the correctness and efficiency for process transformation.As a case study,the EPEM descriptions of Web Services Business Process Execution Language(WS-BPEL) were represented and a Process Virtual Machine(PVM)-OncePVM was implemented in compliance with the EPEM.

Optimal switching policy for performance enhancement of distributed parameter systems based on event-driven control

This paper aims to improve the performance of a class of distributed parameter systems for the optimal switching of actuators and controllers based on event-driven control. It is assumed that in the available multiple actuators, only one actuator can receive the control signal and be activated over an unfixed time interval, and the other actuators keep dormant. After incorporating a state observer into the event generator, the event-driven control loop and the minimum inter-event time are ultimately bounded. Based on the event-driven state feedback control, the time intervals of unfixed length can be obtained. The optimal switching policy is based on finite horizon linear quadratic optimal control at the beginning of each time subinterval. A simulation example demonstrate the effectiveness of the proposed policy.

Smart home architecture based on event-driven DPWS～+

With the advances of electronic information technology and computer network, especially the embedded technology, smart home is no more just a vision but being practical. The interoperability of heterogeneous devices and flexibility of devices＇ usage are two key problems that challenge the implementation of smart home. To deal with these two issues, this paper proposes an event-driven service oriented architecture using device profile for web services （DPWS）. DPWS inherits the advantages of the traditional web services in achieving interoperability without dependence on platform, while improving service discovery and security as well as being optimized for deploying on resource constrained devices. By providing a visual interface for describing a service workflow （SW）, the user can easily customize the actions of devices by services composition. Devices automatically cooperate without user＇s intervention to complete required business logic. This is achieved by fully exploiting the eventing capabilities on DPWS enabled home devices. Finally, a home theater scenario is given to illustrate the event driven mechanism for the SW in the proposed smart home framework.

Internet-based event synchronization communication driven telerobotics

Based on QoS (quality of service) parameters: time delay, jitter, bandwidth and package loss. As time delay in the Internet is variable, it is hard to compensate it by traditional methods. Event synchronization communication driven method is proposed to overcome the negative effects induced by time delay. This method is a non-time based method and it can get rid of the effects of time in the control loop of telerobotics. Stability, transparency and synchronization can be maintained in it by event-driven method. Multimodal enhanced telerobotics is put forward with its feedback including force, video, audio and temperature etc. The use of multimodal feedback improves the efficiency and safety of the whole system. Synchronization in multimodal feedback is hard to ensure and event-driven method is also good for it. Experiments on an Internet-based shaft-hole assemblage system show good results by using event synchronization communication driven method and UDP protocol.

Event-driven timing system based on MRF cPCI hardware for HLS-II

Hefei Light Source(HLS)-II is a vacuum ultraviole(VUV) synchrotron light source. A major upgrade of the light source was finished at the end of 2014. The timing system was rebuilt using compact peripheral component interconnect(cPCI) event-driven hardware to meet synchronization requirements of the machine. In the new system, the c PCI event-driven products manufactured by the micro-research finland(MRF) Oy are employed to achieve about 100 output signals with different interfaces. Device supports and drivers developed for common Experimental Physics and Industrial Control System(EPICS) records are used to access the registers on the timing modules. Five c PCI-bus input/output controllers(IOCs) distributed in different areas of the light source host timing modules for various subsystems. The delay resolution of this system is 9.8 ns for most channels and 9 ps for the channels used for triggering the electron gun and the injection kickers. The measured rms jitter of the output signal is less than 27 ps. Using the bucket chooser, this system enables the HLS-II to fill the storage ring with any designated bunch pattern. Benefitting from this upgrade, brightness and performance of the light source are significantly improved.

EVENT-DRIVEN SIMULATION OF INTEGRATE-AND-FIRE MODELS WITH SPIKE-FREQUENCY ADAPTATION

The evoked spike discharges of a neuron depend critically on the recent history of its electrical activity. A well-known example is the phenomenon of spike-frequency adaptation that is a commonly observed property of neurons. In this paper, using a leaky integrate-and-fire model that includes an adaptation current, we propose an event-driven strategy to simulate integrate-and-fire models with spike-frequency adaptation. Such approach is more precise than traditional clock-driven numerical integration approach because the timing of spikes is treated exactly. In experiments, using event-driven and clock-driven strategies we simulated the adaptation time course of single neuron and the random network with spike-timing dependent plasticity, the results indicate that (1) the temporal precision of spiking events impacts on neuronal dynamics of single as well as network in the different simulation strategies and (2) the simulation time scales linearly with the total number of spiking events in the event-driven simulation strategies.

Event-driven Dynamic and Intelligent Scheduling for Agile Manufacturing Based on Immune Mechanism and Expert System

Based on the biological immune concept, immune response mechanism and expert system, a dynamic and intelligent scheduling model toward the disturbance of the production such as machine fault,task insert and cancel etc. Is proposed. The antibody generation method based on the sequence constraints and the coding rule of antibody for the machining procedure is also presented. Using the heuristic antibody generation method based on the physiology immune mechanism, the validity of the scheduling optimization is improved, and based on the immune and expert system under the event-driven constraints, not only Job-shop scheduling problem with multi-objective can be solved, but also the disturbance of the production be handled rapidly. A case of the job-shop scheduling is studied and dynamic optimal solutions with multi-objective function for agile manufacturing are obtained in this paper. And the event-driven dynamic rescheduling result is compared with right-shift rescheduling and total rescheduling.

Discrete Event Simulation-Based Evaluation of a Single-Lane Synchronized Dual-Traffic Light Intersections

This research involved an exploratory evaluation of the dynamics of vehicular traffic on a road network across two traffic light-controlled junctions. The study uses the case study of a one-kilometer road system modelled on Anylogic version 8.8.4. Anylogic is a multi-paradigm simulation tool that supports three main simulation methodologies: discrete event simulation, agent-based modeling, and system dynamics modeling. The system is used to evaluate the implication of stochastic time-based vehicle variables on the general efficiency of road use. Road use efficiency as reflected in this model is based on the percentage of entry vehicles to exit the model within a one-hour simulation period. The study deduced that for the model under review, an increase in entry point time delay has a domineering influence on the efficiency of road use far beyond any other consideration. This study therefore presents a novel approach that leverages Discrete Events Simulation to facilitate efficient road management with a focus on optimum road use efficiency. The study also determined that the inclusion of appropriate random parameters to reflect road use activities at critical event points in a simulation can help in the effective representation of authentic traffic models. The Anylogic simulation software leverages the Classic DEVS and Parallel DEVS formalisms to achieve these objectives.

运用一站式智能导医平台改善患者就医体验

智能导医是医院智慧服务的重要组成部分。上海市胸科医院借助事件驱动和人工智能技术,以微信公众号为载体,构建了一站式智能导医平台,根据不同患者门诊就医需求,制订个体化就医规划,以任务流形式串联各就诊环节,缩短了患者候诊时间,缓解了导医工作压力,改善了患者就医体验。

事件驱动的云原生应用软件研究

事件驱动是云原生应用的主要驱动力,是实时敏捷数字业务的核心。通过侦听物联网设备、移动应用程序、业务网络和用户行为等事件源,捕获业务事件,驱动服务。事件的捕获、通信、转换和持久化是关键,可以扩展、适配不同类型的服务。消息队列是异步的,消息的发送和接收者不需要同时与消息队列交互,减少了服务间的耦合;如果系统请求流量瞬时剧增,消息队列将缓存请求,提高系统的稳定性和用户体验;事件溯源可以回溯到任何一个事件状态,增强系统的可靠性和容错。CloudEvents是描述事件数据通用格式的规范,提供跨服务、平台和系统的互操作。基于主题和分区将事件路由到不同的服务实例实现分布式并发。事件驱动架构融合微服务和无服务器函数,构建实时、可扩展、高负载和大规模可伸缩的云原生应用软件。

考虑源荷不确定性及用户响应行为的电力系统低碳经济调度

电力系统是未来实现碳中和目标的重要领域,随着源-荷不确定性的加剧,基于确定性模型的低碳经济调度方法无法准确描述不确定因素对碳排放的影响。针对上述问题,该文首先从系统层面构建考虑不确定性的低碳鲁棒优化模型,利用概率模型对源荷不确定因素进行建模,并采用机会约束对目标满足期望的显著性水平进行描述,通过最大化不确定因素的置信水平得出风险规避策略下的鲁棒调度方案。接着从用户层面构建基于事件驱动的用户低碳响应模型,根据系统层计算结果,通过设定事件触发的碳排放阈值定义碳排放超额事件,并以价格形式引导用户的低碳用能行为。最后通过算例分析,验证所提模型能有效量化评估系统的低碳经济调度不确定性水平,充分发挥用户侧降碳能力,实现源荷双侧低碳目标的协同。

基于事件驱动深度强化学习的建筑热舒适控制

住宅暖通空调系统通常耗用大量能源,同时也极大地影响居住者的热舒适性。目前,强化学习广泛应用于优化暖通空调系统,然而这一方法需要投入大量时间和数据资源。为了解决该问题,提出了一个新的基于事件驱动的马尔可夫决策过程(event-driven Markov decision process,ED-MDP)框架,并在此基础上,提出了基于事件驱动的深度确定性策略梯度(event-driven deep deterministic policy gradient,ED-DDPG)方法,通过事件触发优化控制,结合强化学习算法求解最优控制策略。实验结果显示,与基准方法相比,ED-DDPG在提升学习速度和减少决策频率方面表现出色,并在节能和维持热舒适方面取得了显著成果。经过实验验证,该方法在优化住宅暖通空调控制方面展现出强大的鲁棒性和适应性。

基于事件驱动的超图卷积网络的谣言检测方法

依靠社交平台谣言传播链检测谣言是社交网络分析研究中的一个重要课题.但以往的研究大多将这个任务过度简化为依靠评论的传播链检测谣言,忽略了对现实世界新闻帖的复杂用户和事件交互的关注,难以捕捉到这些信息提供的潜在检测线索.针对该挑战,提出了一个事件驱动的超图卷积网络(event-driven hypergraph convolutional network,EHGCN),首次尝试将新闻、用户和事件建模在一个统一的超图卷积网络之中,以提升谣言检测性能.具体而言,基于用户的中心网络构建同质用户圈,以增强用户感知的谣言检测.此外,EHGCN联合利用事件内的主事件和子事件关联以及事件间的不一致性关联来进行谣言检测.在3个真实世界的数据集上进行的实验结果验证了EHGCN相较于现有方法在谣言检测方面的优势.研究也证实EHGCN可以通过获取丰富的用户社交圈和事件信息,在谣言传播早期及时发现谣言.

告警诊断和预测技术研究综述

总结论述了基于图论的故障诊断和定位技术、基于软件定义网络(Software Defined Network,SDN)架构的故障诊断和恢复技术、基于故障追踪的故障预测方法、基于事件驱动的故障预测方法。从故障诊断方法的优点、缺点进行对比分析,从故障预测的模型输入、应用范围、优点和不足等方面进行对比分析,对发展趋势进行分析总结,以实例验证了所总结的故障诊断和预测方法。

基于事件驱动的液流电池控制系统实现方式

液流电池具有充放电循环次数大、容量高及寿命长等优点,是长时大规模储能的理想选择,但是其复杂的结构对电池控制系统的要求较高,传统开发方式难以满足其多样的控制需求,因此提出精准度更高、实时性更好的基于事件驱动技术的液流电池控制系统开发方法。首先针对液流电池稳定性需求高、内部损耗大等问题,提出了主/辅助电堆协同架构,并对该架构系统进行建模分析;然后基于事件驱动技术对控制系统进行模块化设计,包括柔性充放电控制、辅助电堆参与的黑启动控制、基于卡尔曼滤波的电池荷电状态(state of charge,SOC)估计等;最后搭建半实物仿真平台,对所提架构和策略进行验证,证明了该架构和策略能提高系统的能量转换效率和稳定性。

考虑最大通信量的物联网群体访问路由算法

针对因物联网群体用户访问数据量较大、访问频率不稳定,导致访问时延大、效率低的问题,提出一种基于事件驱动的访问路由算法予以解决。考虑到物联网群体数据动态特性强、难捕捉的问题,分析相邻访问节点位置信息、访问频率以及能耗变化与传输时延的关系。设置任意节点的簇首参数,通过物联网群体访问节点拓扑模型,计算簇首到访问点可容纳的最大通信量,作为路由算法的初始参照,采用事件驱动法将访问过程看作事件自然变动过程,结合实际负载情况,得到最终路由决策结果。实验结果表明,无论是干扰环境还是无干扰环境,所提路由算法的访问成功率均较高,且访问时延较低,具有一定的实用价值。

基于事件驱动的无人机吊挂系统在线自适应轨迹规划

本文针对四旋翼无人机吊挂系统空运过程中负载摆角的非线性最优调节问题,提出了一种基于事件驱动的在线自适应轨迹规划策略.在事件驱动的自适应评价网框架下,利用神经网络的逼近学习能力得到吊挂负载摆动抑制的折现最优控制律.同时结合该控制律进一步规划四旋翼无人机的飞行轨迹,实现了对无人机位置的精确调节和吊挂负载摆动的快速抑制,并且显著降低了无人机机载处理器的计算负担.然后采用基于Lyapunov稳定性的分析方法,证明了神经网络输出权值估计误差一致最终有界,并证明了无人机位置跟踪误差和吊挂负载摆动运动的收敛.最后,通过飞行对比实验验证了所提出的轨迹规划策略的有效性.

支持抑制型脉冲神经网络的硬件加速器

现有脉冲神经网络加速器的设计过多关注于硬件层面的功能完备性,缺少算法层面的相关协同优化以保证硬件计算效率。此外,传统的事件驱动型脉冲神经网络加速器没有考虑到脉冲神经元模型中普遍存在的脉冲抖动现象,因此不能实现对抑制型脉冲神经网络的支持。为解决上述问题,采用软硬件结合的方式,提出了一种支持抑制型脉冲神经网络加速器的设计方法。软件优化层面通过对脉冲神经网络计算冗余性的分析,提出了相应的近似计算方法以大幅降低脉冲神经网络的计算量;硬件设计层面提出了解决脉冲抖动问题的计算模块,并在此基础上设计了与近似计算方法相适应的并行计算结构。为验证设计的合理性,在XilinxZC706 FPGA上部署了加速器原型FEAS。在主流数据集上的测试结果显示,相较以往脉冲神经网络的加速器部署,FEAS在保持97.54%原有模型精度的情况下获得超过一个数量级的性能提升。