A Generalized State Space Average Model for Parallel DC-to-DC Converters

The high potentiality of integrating renewable energies,such as photovoltaic,into a modern electrical microgrid system,using DC-to-DC converters,raises some issues associated with controller loop design and system stability.The generalized state space average model(GSSAM)concept was consequently introduced to design a DC-to-DC converter controller in order to evaluate DC-to-DC converter performance and to conduct stability studies.This paper presents a GSSAM for parallel DC-to-DC converters,namely:buck,boost,and buck-boost converters.The rationale of this study is that modern electrical systems,such as DC networks,hybrid microgrids,and electric ships,are formed by parallel DC-to-DC converters with separate DC input sources.Therefore,this paper proposes a GSSAM for any number of parallel DC-to-DC converters.The proposed GSSAM is validated and investigated in a time-domain simulation environment,namely a MATLAB/SIMULINK.The study compares the steady-state,transient,and oscillatory performance of the state-space average model with a fully detailed switching model.

Study of Steady-state Performances for a Novel Line-start Single-phase Permanent Magnet Synchronous Motor With Three Parallel-connected Windings

对于三相感应电动机的单相运行,学者们已经提出了多种实用的接线方式,比如Smith接法、SEMIHEX接法。然而,对于三相异步起动永磁同步电动机的单相运行,很少有合适的接法提出。将并联式接法应用于三相异步起动永磁同步电动机的单相运行,提出了一种新型三绕组并联式异步起动单相永磁同步电动机。分析了三相异步起动永磁同步电动机同步运行时以及起动瞬间的正序、负序阻抗,基于对称分量法,对该接法电机的对称运行条件进行分析,得出了电容的确定方法,并利用遗传算法对电容值进行优化。提出了该新型电机稳态性能的计算方法;设计了一台高功率因数和一台低功率因数三相异步起动永磁同步电动机作为样机,并分别将其改接为三绕组高效单相永磁同步电动机,进行实验研究。实验结果表明,低功率因数的异步起动永磁同步电动机更适合改接成新型三绕组并联式单相永磁同步电动机。由低功率因数三相永磁同步电动机改接成的单相异步起动永磁同步电动机在额定负载下运行时,具有与同容量三相永磁同步电动机相近的效率和更高的功率因数。

并联副回路串级控制系统的稳态分析

分析了过程控制实际应用中,并联副回路串级控制系统能否经过主、副控制器的调节实现主对象的精确跟踪。通过对并联串级控制系统建模,计算其余差从而分析稳态性质,并由此给出了一些工程应用中的建议。理论计算、仿真验证及工程实例均表明该控制方案能达到预期的控制要求,为流程工业过程控制中的同类问题提供解决方案。

WiFi CSI Gesture Recognition Based on Parallel LSTM-FCN Deep Space-Time Neural Network

In this study,we developed a system based on deep space–time neural networks for gesture recognition.When users change or the number of gesture categories increases,the accuracy of gesture recognition decreases considerably because most gesture recognition systems cannot accommodate both user differentiation and gesture diversity.To overcome the limitations of existing methods,we designed a onedimensional parallel long short-term memory–fully convolutional network(LSTM–FCN)model to extract gesture features of different dimensions.LSTM can learn complex time dynamic information,whereas FCN can predict gestures efficiently by extracting the deep,abstract features of gestures in the spatial dimension.In the experiment,50 types of gestures of five users were collected and evaluated.The experimental results demonstrate the effectiveness of this system and robustness to various gestures and individual changes.Statistical analysis of the recognition results indicated that an average accuracy of approximately 98.9% was achieved.

Lower Bounds and a Nearly Fastest General Parallel Branch-and-Bound Algorithm

In this paper, it is supposed that the B&B algorithm finds the first optimal solution after h nodes have been expanded and m active nodes have been created in the state-space tree. Then the lower bound Ω(m+h log h) of the running time for the general sequential B&B algorithm and the lower bound Ω(m/p+h log p) for the general parallel best-first B&B algorithm in PRAM-CREW are proposed, where p is the number of processors available. Moreover, the lower bound Ω(M/p+H+(H/p) log (H/p)) is presented for the parallel algorithms on distributed memory system, where M and H represent total number of the active nodes and that of the expanded nodes processed by p processors, respectively. In addition, a nearly fastest general parallel best-first B&B algorithm is put forward. The parallel algorithm is the fastest one as p = max{hε, r}, where ε = 1/ rootlogh, and r is the largest branch number of the nodes in the state-space tree.

Local Search Heuristics for NFA State Minimization Problem

In the present paper we introduce new heuristic methods for the state minimization of nondeterministic finite automata. These methods are based on the classical Kameda-Weiner algorithm joined with local search heuristics, such as stochastic hill climbing and simulated annealing. The description of the proposed methods is given and the results of the numerical experiments are provided.

Load Dependent Series-Parallel Systems with Common Bus Performance Sharing Mechanism

A series-parallel system was proposed with common bus performance sharing in which the performance and failure rate of the element depended on the load it was carrying. In such a system,the surplus performance of a sub-system can be transmitted to other deficient sub-systems. The transmission capacity of the common bus performance sharing mechanism is a random variable. Effects of load on element performance and failure rate were considered in this paper. A reliability evaluation algorithm based on the universal generating function technique was suggested. Numerical experiments were conducted to illustrate the algorithm.

Exact Computation of Parallel Robot's Generalized Inertia Matrix

According to the definition of the new hypothetical states which have obvious physical significance and are termed as no-gravity static and accelerated states, a method for exact computation of the parallel robot＇s generalized inertia matrix is presented. Based on the matrix theory, the generalized inertia matrix of the parallel robot can be computed on the assumption that the robot is in these new hypothetical states respectively. The approach is demonstrated by the Delta robot as an example. Based on the principle of the virtual work, the inverse dynamics model of the robot is formulized after the kinematics analysis. Finally, a numerical example is given and the element distribution of the Delta robot＇s inertia matrix in the workspace is studied. The method has computationa＇, advantage of numerical accuracy for the Delta robot and can be parallelized easily.

Using Pipeline Instructions by Parallel Simulation of Mathematical Models

Simulation is an important and useful technique helping users understand and model real life systems. Once built, the models can run proving realistic results. This supports making decisions on a more logical and scientific basis. The paper introduces method of simulation, and describes various types of its application. The authors used the method of analysis of the creation and implementation of the programme code. The authors compared parallel instruction of computing defined to pipelined instructions. The power of simulation is that a common model can be used to design a large variety of systems. An important aspect of the simulation method is that a simulation model is designed to be repeated in actual computer systems, especially in multicore processors. For this reason, it is important to minimize average waiting time for fetch and decode stage instructions. The objective of the research is to prove that the parallel operation of programme code is faster than sequential operation code on the multi processor architecture. The system modeling uses methods and simulation on the parallel computer systems is very precise. The time benefit gained in simulation of mathematical model on the pipeline processor is higher than the one in simulation of mathematical model on the multi processors computer system.

直流微电网储能荷电状态协调控制

储能系统采用串并联结构(串联的储能单元为一组,多组并联)可以实现将小容量、低电压等级的储能单元接入直流微电网中,并且可以实现系统扩容和提高端电压。为避免串并联结构的储能单元因荷电状态(state of charge,SOC)和额定容量差别导致个别储能单元提前退运的短板效应,提出一种考虑储能SOC和额定容量的控制方法,实现串联模块间的电压和并联模块间的功率合理分配。考虑到功率分配后期因储能单元间SOC差别较小导致均衡速度较慢的问题,引入变异系数对下垂系数进行动态优化。考虑到升压或扩容导致各组总容量不同,引入容量权重因子,使储能单元达到均衡出力。通过搭建MATLAB/Simulink仿真模型,验证了策略的可行性。

基于FSM的并联谐振中频电源整流逆变调功控制

并联谐振晶闸管中频双控感应加热电源调功系统由整流和逆变两部分构成。调节整流单元的移相角,改变逆变单元的功率因数角都可影响谐振槽路的中频电压的输出,进而控制输出功率。在分析槽路中频逆变电压同晶闸管整流装置的移相角、逆变单元的功率因数角关系的基础上,提出了基于有限状态机(FSM)的并联谐振晶闸管中频电源整流-逆变调功方案。该方案采用控制层与调度层结构。控制层将中频电压作为闭环控制对象,分别以整流环节和逆变环节作为执行单元,设计具有鲁棒稳定性的移相整流控制器和锁相逆变控制器;调度层采用FSM结构,可根据加热工艺需求实现整流-逆变轮换调功和联合调功。该方案已经应用于多台大功率并联谐振晶闸管中频电源中,其可行性和有效性得到验证。

基于有限状态机的电网多源时空数据的区块链追溯方法研究

电网基础数据类型多、变化关系复杂,地理空间、时间周期跨度大,数据追溯困难,该文提出基于区块链技术的电网多源数据追溯方法。根据电网基础数据时空分布及数据流变动性特点,建立了基于区块链的多源数据追溯架构,研究了数据追溯依赖关系及溯源路径结构。提出了基于有限状态机模型的数据溯源的路径结构分析图,及路径构建算法,研究了多源时空数据区块的平行追溯方式。构建了基于有限状态机溯源路径的电网多源时空数据追溯优化流程,研究了多层次溯源数据区块时空序列关联性。工程实例表明,基于区块链、有限状态机可高效灵活追溯电网基础多源时空数据的完整可信分布序列。

基于EtherCAT总线的八轴七联动高级海况环境仿真平台

针对水流模拟海况时存在的运动不受控以及常规海况模拟平台模拟海况等级低,运动自由度不足等问题,提出利用八自由度运动平台模拟高级海况环境进行海浪涌动测试的方法。设计了由直线运动平台、旋转机构和6自由度(6-DOF)并联机构组成的串并联混合八自由度高级海况环境仿真平台,其运动加速度大,自由度多,运动方式多样。基于Ether CAT实时总线技术设计了八轴七联动的运动控制算法,并采用惯量匹配技术抑制抖动和噪声,实现了宽惯量范围的精确、稳定、同步(小于1μs)控制。设计了基于外部信号接收器的实时精密补偿技术和双齿轮消隙技术,提高了速率精度和平稳性,定位精度达到10μm。设计了复合叠加摇摆、文件仿真、复合叠加摇摆与文件仿真叠加运动和实时仿真运动方式,可模拟到五级高海况或将实航数据回灌后模拟水下、水面或机载的运动,用于导航系统的姿态模拟测试。

基于扩张状态观测器的并联直流变换器增强控制策略

为进一步改善并联直流变换器在多种内外部扰动下的动态性能,提出一种基于双闭环扩张状态观测器(ESO)的增强控制策略。该策略将比例调节器与ESO相结合,然后分别应用于公共电压外环和各个电流内环,实现各功率单元的动态均流,也强化对输入电压扰动的抑制能力,且无需额外传感器。首先,根据并联变换器的状态方程,推导内环电流ESO控制的表达式。然后,根据电流闭环极点的分布情况,从理论上分析ESO型电流内环在输入电压扰动抑制方面强于比例积分型电流内环的原因。此外,借助伯德图,给出ESO型电流内环对电感失配的鲁棒性更强并能有效消除动态电流偏差的理论依据。最后,使用三相buck变换器进行不同方案的对比验证,实验结果证明了所提策略在改进动态性能方面的有效性和先进性。

基于逆阻型IGCT器件的固态式直流断路器设计及研制

直流系统是支撑高比例新能源接入与灵活高效用能的重要技术方向。固态式直流断路器(solid state DC circuit breaker,SSCB)具有开断速度极快、无电弧、寿命长等优点,在中低压直流系统的故障保护中得到广泛应用。随着电力电子器件的发展,固态式直流断路器的拓扑结构、工作性能也在不断进步。为此基于逆阻型集成门极换流晶闸管(intergated gate commutate thyristor,IGCT),提出了一种新型的固态式直流断路器结构及设计方法,通流支路采用逆阻IGCT反并联结构实现双向通流,缓冲支路采用金属氧化物避雷器(metal oxide varistor,MOV)-电容结构来抑制过电压,吸能支路采用MOV吸收系统能量。进一步地,给出了关键元器件的参数设计方法,并验证了有效性;设计了性能良好的重力热管散热器,单个模块散热功率可达700 W;提出了主被动结合的控保策略,提高断路器的保护性能。最后,研制了固态式直流断路器样机,可用于750 V以内的低压直流系统,额定通流可达2 kA,可在百微秒内开断10 kA故障电流,成本低、体积小、高可靠,具有良好的应用前景。

机液并联驱动的工程钻机功率分配分析及工程试验

为实现工程钻机动力系统功率的合理分配,提出机液并联驱动系统的功率分配方式。通过分析该系统的工作原理,得出其传动部分的输出转速、转矩及总传动比的特性曲线;在此基础上,运用键合图理论建立系统功率键合图的物理模型,并推导出该系统的状态方程。基于系统功率流及能量的传递,辨识出系统的功率流及能量的传递由系统分配参数与外负载共同决定。通过构建系统各负载的数学模型,经数值计算得出各负载的关系曲线,结合AMESim软件对仿真模型进行数据分析及钻机工程试验,得出机液并联驱动系统在中高转速有着良好的输出特性,此时,系统的功耗低,钻机钻凿效率高。经分析,应用于钻机的机液并联驱动系统及功率分配方式可满足工程基础开挖的需求,同时为工程装备的动力系统设计提供理论支持和技术借鉴。

基于特征矩阵分区等值和自适应插值切换的有源配电网多速率并行仿真方法

现代有源配电网呈现复杂多变、多时间尺度的特征,采用单一仿真速率难以同时兼顾计算效率与精度,对此该文提出基于特征矩阵分区等值和自适应插值切换的有源配电网多速率并行仿真方法。首先,构建系统状态空间矩阵,并基于状态矩阵特征值的量级将系统拆分为多个动态特性差异的子系统,通过将系统的状态矩阵进行分块等效,实现子区域在小步长时刻的独立仿真解算与在大步长时刻的等效补偿,在保证仿真精度的基础上大幅降低了系统仿真规模;然后,针对各区域间数据交互不同步问题,通过倍率步长相量法分析线性插值误差产生原理及主要影响因素,并提出基于二阶泰勒展开式的多步自适应插值仿真算法,可以根据系统频率与仿真步长需求调节相关插值参数,显著降低插值误差;最后,采用改进型IEEE 123节点配电网算例,通过分区等值/插值计算与仿真结果的对比,验证了所提多速率并行仿真方法的可行性与有效性。

基于ESO的分拣并联机器人无标定视觉伺服自适应滑模控制

针对无标定分拣并联机器人需获取精确图像雅可比矩阵的问题,同时为克服图像检测误差、建模误差及外部干扰对无标定视觉伺服系统的影响,提出一种基于扩张状态观测器(extended state observer,ESO)的分拣并联机器人无标定视觉伺服自适应滑模控制方法。通过将表征机器人图像空间与任务空间映射关系的图像雅可比矩阵与系统不确定项集总到同一通道的状态方程,引入ESO对分拣并联机器人视觉伺服系统的集总不确定性进行在线估计,设计一种基于扩张状态观测器的自适应积分滑模控制器,并通过设计自适应律动态调整滑模控制切换增益,以提高视觉伺服系统精度,同时达到抑制滑模控制抖振的效果。采用Lyapunov稳定性理论证明该控制方法的稳定性,最后通过仿真实验验证了所提出视觉伺服自适应滑模控制方法的可行性和有效性。

政绩目标异化与基层治理结构转型

国家战略目标和政策资源输入成为促进基层治理结构转型的重要力量。而基层(县域)体制的能动性使得国家权力在基层的作用发生转向。在此背景下,县域体制主导基层治理体系的核心地位进一步强化,县乡村层级一体化,基层体制支配乡村社会的能力增强;基层治理规则和方式趋于行政化,科层主导的项目资源分配超脱于乡村社会层面,治理形态呈现出去公共性、弱社会动员、泛体制化等特征。国家推进涉农战略落地强化了农民政治认同和绩效合法性。但项目下乡产生了异化现象,使其并不能够有效渗透和建构新的基层社会利益关系与秩序,也难以激活基层社会层面的政治参与、村民自治和民主协商。因而基层治理结构进一步体制化,国家涉农政策的绩效合法性也随之受到影响。

基于时序控制的固态开关串并联高压脉冲技术

针对生物医疗等高压陡脉冲应用需求,设计了基于固态开关串并联高压陡脉冲发生电路,并结合时序控制技术,提出一种脉冲陡化新方法;从理论上分析了脉冲陡化的关键、系统工作的过程以及设计要点。该方法能较好解决开关管增加后杂散参数、布线电感以及导线电感对开关速度的影响。以2 kV高压直流电源、110Ω的负载电阻进行实验,负载脉冲信号的上升沿约为50 ns,下降沿约为70 ns,输出电流幅值约18 A;最小脉宽信号的半高宽为100 ns,系统的最小分辨率为5 ns,可实现步进为5 ns脉宽的灵活调节,最大脉宽则与储能电容有关。