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2021 IEEE 2nd International Conference on Signal, Control and Communication (SCC)最新文献

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STATCOM/APF Control Using Two Proposed DPC Strategies For Power Quality Improvement STATCOM/APF控制采用两种提出的DPC策略改善电能质量
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768395
Kamel Sayahi, Bacha Faouzi
In order to provide electrical energy to consumers in compliance with international standards, electrical energy operators are required to control the quality of this energy from its production to its consumption. For this purpose, several static converters are installed at different grid locations to ensure the transient and permanent stability of the later. FACTs (flexible alternative current transmission systems), active power filters... are based on static converters. These devices ensure the compensation of the reactive power in the grid as well as the elimination of the grid current and voltage harmonics. This paper deals with the direct power control (DPC) of a static power converter installed on the electrical network in two different ways. This converter provides the function of a STATCOM (static compensator) of reactive power and at the same time the function of an active power filter (APF).
为了向消费者提供符合国际标准的电能,电能经营者必须控制电能从生产到使用的质量。为此,在不同的电网位置安装几个静态变流器,以确保后者的暂态和永久稳定性。FACTs(灵活的交流输电系统),有源电力滤波器…都是基于静态转换器。这些装置保证了电网中无功功率的补偿以及电网电流和电压谐波的消除。本文从两种不同的方式研究了电网上静态功率变换器的直接功率控制。该变换器提供无功功率静态补偿器(STATCOM)的功能,同时提供有源功率滤波器(APF)的功能。
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引用次数: 0
Sliding mode control of a Marine Current Turbine driven DFIG-DC conversion system 船用水轮机驱动DFIG-DC转换系统的滑模控制
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768377
Yosra Smai, H. Ben Azza, M. Jemli
This paper presents a marine current turbine (MCT) system based on a Doubly Fed Induction Generator (DFIG) connected to DC-bus. Field Oriented Control (FOC) is the control strategy chosen for the DFIG-DC energy conversion system. In this topology, a diode rectifier is used to connect the stator of the DFIG and the DC-bus, while the rotor is connected to the DC-bus through a PMW inverter. The regulation of the stator frequency and the dc voltage is ensured respectively through the control of d-axis and q-axis rotor currents. First order sliding mode controllers are proposed to control the rotor currents. Simulation and experimental results are presented to show the performance of the proposed control strategy.
介绍了一种基于双馈感应发电机(DFIG)与直流母线连接的船舶电流涡轮(MCT)系统。场定向控制(FOC)是DFIG-DC能量转换系统所选择的控制策略。在这种拓扑结构中,二极管整流器用于连接DFIG的定子和直流母线,而转子通过PMW逆变器连接到直流母线。通过对d轴和q轴转子电流的控制,分别保证定子频率和直流电压的调节。提出了一阶滑模控制器来控制转子电流。仿真和实验结果验证了所提控制策略的有效性。
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引用次数: 1
Impact of the MMC level number to reduce THD rate and improve the power quality transmitted to the electrical grid 影响MMC等级数,降低THD率,提高输往电网的电能质量
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768340
Mansour Baazouzi, F. Bacha
The High Voltage Direct Current (HVDC) power systems has an important role in transmitting high power among long distances with respect to the transportation of the AC high voltage (HVAC). The HVDC grid has a set of advantages such as robustness against disturbances and low power losses compared to the AC system and the connection between two AC power grids. Modular Multi-Level Converter (MMC) is more suitable kind of topology compared to other topologies used in HVDC applications. The increasing number of submodules (SM) presents a challenge for researchers in terms of ordering complexity. In this paper, two pulse width modulation techniques are compared in the quality of currents and voltages to the filter level, which presents one of the major problems of the MMC converter. The simulation was performed using MATLAB/Simulink software and the presented simulation results prove the performance of the proposed control systems. The output voltage waveforms and the total harmonic distortion (THD) rate of the proposed system are improved without the need for a filter.
高压直流(HVDC)电力系统在交流高压(HVAC)输电中具有长距离大功率传输的重要作用。与交流系统和两个交流电网之间的连接相比,高压直流电网具有一系列优点,例如抗干扰的鲁棒性和低功率损耗。模块化多电平变换器(MMC)是一种较适合于高压直流应用的拓扑结构。随着子模块数量的不断增加,排序复杂性对研究人员提出了挑战。本文比较了两种脉宽调制技术对滤波器级电流和电压的质量,提出了MMC变换器的主要问题之一。利用MATLAB/Simulink软件进行了仿真,仿真结果验证了所提控制系统的性能。在不需要滤波器的情况下,该系统的输出电压波形和总谐波失真(THD)率得到改善。
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引用次数: 1
Flow-Loop Testing of Online Oil-in-Water UV-Fluorescence-Based Measurement 在线水包油紫外荧光测量的流环测试
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768363
Stefan Jespersen, D. Hansen, Zhenyu Yang, S. Andersen
The online monitoring of Oil-in-Water (OiW) concentration in dynamic flow-loops using UV-Fluorescence-based sensors is investigated. Though the OiW sensors can be carefully calibrated in the static condition, many dynamic flow conditions can still impact their real-time measurement. In order to examine the considered OiW sensor’s capability in handling dynamic flows, an extensive experimental study has been committed, which considers the following aspects, such as (i) different flow-loop configurations, e.g., standalone-loops and cyclone-in-loop; (ii) different online sampling mechanisms, e.g., (direct) in-line measurement and (indirect) side-stream measurement; (iii) different flow-rates of total stream or side-stream under different configurations and sampling mechanisms; (iv) impacts of air bubbles and pressure-pumps. The experimental results show that the considered OiW sensor can provide quite reasonable dynamic measurements in general. However this sensor’s measurement can be very sensitive to different flow regimes, impurities (incl. air) in the measured stream as well as upstream (nearby) operating conditions. These observations could inspire automation researchers and industrial operators to create some innovative sensor fusion method(s), to combine this OiW measurement with other available measurements in the produced water treatment processes for better control of the de-oiling hydrocyclone system.
研究了利用紫外荧光传感器在线监测动态循环中水中油(OiW)浓度的方法。虽然OiW传感器可以在静态条件下仔细校准,但许多动态流动条件仍然会影响其实时测量。为了检验所考虑的OiW传感器处理动态流动的能力,已经进行了广泛的实验研究,其中考虑了以下方面,例如(i)不同的流环配置,例如,独立环路和旋风环;(ii)不同的在线采样机制,例如(直接)在线测量和(间接)侧流测量;(iii)在不同配置和采样机制下,总流和侧流的流量不同;(iv)气泡和压力泵的冲击。实验结果表明,该传感器总体上可以提供相当合理的动态测量。然而,该传感器的测量对不同的流动状态、被测量流中的杂质(包括空气)以及上游(附近)的操作条件非常敏感。这些观察结果可以启发自动化研究人员和工业操作员创造一些创新的传感器融合方法,将OiW测量与采出水处理过程中的其他可用测量相结合,以更好地控制除油旋流器系统。
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引用次数: 0
Emotion Recognition using Speech Data with Convolutional Neural Network 基于卷积神经网络的语音数据情感识别
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768372
M. H. Pham, F. Noori, J. Tørresen
Identifying emotion from speech has a wide range of applications and has drawn special interests in research to improve the human-computer interaction experience. Traditional machine learning approaches usually face the challenge of selecting the optimal feature set for each application. Deep learning, on the other hand, allows end-to-end development of the models and inherent feature extraction. In this study, we evaluate the performance of Convolutional Neural Network on different kinds of spectral features of acoustic signal collections, from two popular open databases Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) and Berlin Database of Emotional Speech (EmoDB). Two-to-eight classes of emotions (RAVDESS) and two-to-seven classes of emotions (EmoDB) are identified by the deep learning model. The results, in terms of unweighted average recall, are 0.888 (two classes) and 0.694 (eight classes) for the RAVDESS dataset. The corresponding results for the EmoDB dataset are 0.993 (two classes) and 0.764 (seven classes)
从语音中识别情感具有广泛的应用,并在改善人机交互体验的研究中引起了特殊的兴趣。传统的机器学习方法通常面临着为每个应用选择最优特征集的挑战。另一方面,深度学习允许端到端的模型开发和固有特征提取。在这项研究中,我们评估了卷积神经网络在两个流行的开放数据库——Ryerson情绪语音和歌曲视听数据库(RAVDESS)和Berlin情绪语音数据库(EmoDB)——的不同类型声信号收集光谱特征上的性能。深度学习模型可以识别2 - 8类情绪(RAVDESS)和2 - 7类情绪(EmoDB)。在未加权平均召回率方面,RAVDESS数据集的结果是0.888(两个类)和0.694(八个类)。EmoDB数据集对应的结果是0.993(两个类)和0.764(七个类)。
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引用次数: 4
DTC-SVM Control for Induction Motor Drives Fed by Sparse Matrix Converter 稀疏矩阵变换器异步电机驱动的DTC-SVM控制
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768397
Abdessami Soyed, K. Ameni, O. Hasnaoui, F. Bacha
This paper proposes a space vector modulated direct torque control strategy for induction motor drives fed by a three phase Sparse Matrix Converter (SMC). For the rectifier stage, a space vector modulation strategy is employed. For the inverter, a direct torque control method with a fixed switching frequency is proposed. The performance of the proposed drive system is evaluated by numerical simulation using Matlab/Simulink environment. The simulation results are used to verify the effectiveness of the proposed strategy and support the analytical results.
提出了一种以三相稀疏矩阵变换器(SMC)为馈源的异步电动机空间矢量调制直接转矩控制策略。整流级采用空间矢量调制策略。针对逆变器,提出了一种固定开关频率的直接转矩控制方法。在Matlab/Simulink环境下对该驱动系统的性能进行了数值仿真。仿真结果验证了所提策略的有效性,并支持了分析结果。
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引用次数: 2
Rule-Based power sharing strategy for a fuel cell-supercapacitor vehicle 基于规则的燃料电池超级电容器车辆功率共享策略
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768359
Hajer Marzougui, Ameni Kadri, F. Bacha
To meet increasing demands for fuel, alternative vehicles have been developed recently. Electrical hybrid vehicles are one of these alternatives and an important part of them is their energy storage systems which are used to relieve the main source which is generally a fuel cell. To ensure energy storage, the supercapacitor is considered as an interesting device because of its high power density compared to batteries. The hybridization of the main source with another source like energy storage device allows to improve the dynamic response, especially, during transient states. However, it will be necessary to apply an energy management strategy to share the energy flow between sources responding to load demand. Besides, the proposed energy management algorithm must allow us to ensure optimum hydrogen consumption. In this context, this paper deals with an energy management strategy which is based on deterministic rules. Thus, it is called rule-based strategy and it is used to share the power flow in a hybrid electric vehicle powered by a fuel cell and a supercapacitor. Simulation results under Matlab-Simulink environment prove the efficiency of the proposed energy management algorithm.
为了满足日益增长的对燃料的需求,替代汽车最近得到了发展。电动混合动力汽车就是其中一种替代品,其重要组成部分是其能量存储系统,用于缓解主要能源,通常是燃料电池。为了确保能量储存,超级电容器被认为是一种有趣的设备,因为它比电池具有更高的功率密度。主源与其他源(如储能装置)的杂化可以改善动态响应,特别是在瞬态期间。然而,有必要应用能源管理策略来共享响应负载需求的源之间的能量流。此外,所提出的能源管理算法必须允许我们确保最佳的氢消耗。在此背景下,本文研究了一种基于确定性规则的能源管理策略。因此,它被称为基于规则的策略,并被用于燃料电池和超级电容器驱动的混合动力汽车的功率流共享。Matlab-Simulink环境下的仿真结果证明了所提能量管理算法的有效性。
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引用次数: 0
Vendor-Independent Software-Defined Networking 独立于供应商的软件定义网络
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768368
Santiago Pagola Moledo, Abhimanyu Rawat, A. Gurtov
Software-Defined Networking (SDN) is an emerging trend in networking that offers several advantages such as smoother network management over traditional networks. By decoupling the control and data planes from network elements, a huge amount of new opportunities arise, especially in network virtualization. In cloud datacenters, where virtualization plays a fundamental role, SDN presents itself as the perfect candidate to ease infrastructure management and to ensure correct operation. Even if the original SDN ideology advocates openness of source and interfaces, multiple networking vendors offer their proprietary solutions. In this work, an open-source SDN solution, named Tungsten Fabric, is evaluated in a virtualized datacenter and several SDN-related industry use-cases are examined. The main goal of this work is to determine whether Tungsten Fabric can deliver the same set of use-cases as proprietary solutions.
软件定义网络(SDN)是一种新兴的网络趋势,与传统网络相比,它具有更流畅的网络管理等优点。通过将控制和数据平面与网络元素解耦,出现了大量的新机会,特别是在网络虚拟化方面。在云数据中心中,虚拟化扮演着重要的角色,SDN是简化基础设施管理和确保正确操作的完美选择。即使最初的SDN思想提倡源代码和接口的开放,许多网络供应商也提供了他们的专有解决方案。在这项工作中,一个名为Tungsten Fabric的开源SDN解决方案在虚拟化数据中心中进行了评估,并检查了几个与SDN相关的行业用例。这项工作的主要目标是确定Tungsten Fabric是否可以交付与专有解决方案相同的用例集。
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引用次数: 0
A Low-Power Maximally-Flat Transconductor in Subthreshold CMOS 一种亚阈值CMOS低功耗最平坦型晶体管
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768344
L. Fekih-Ahmed
A new CMOS wide linear range fully-differential transconductor is proposed. The transconductor employs 5 unbalanced differential pairs with transistor aspect ratios chosen optimally using Padé-type approximation theory. It achieves a linear range of 86mV for a voltage supply of 1V. The total harmonic distortion does not exceed 2% for peak to peak voltages as high as 0.2V and frequencies as high as 1MHz. Monte Carlo simulations revealed that the linear range of the suggested transconductor is not prone to parameter variations.
提出了一种新型CMOS宽线性范围全差动变换器。该晶体管采用5个不平衡差分对,晶体管宽高比采用pad型近似理论优选。它在1V电压下实现了86mV的线性范围。峰值电压高达0.2V,频率高达1MHz时,总谐波失真不超过2%。蒙特卡罗模拟表明,所建议的晶体管的线性范围不容易受到参数变化的影响。
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引用次数: 1
Cooperative multi-swarm particle swarm optimization based on adaptive and time-varying inertia weights 基于自适应时变惯性权值的协同多群粒子群优化
Pub Date : 2021-12-20 DOI: 10.1109/scc53769.2021.9768349
Sami Zdiri, Jaouher Chrouta, A. Zaafouri
Optimization of particle swarms is a stochastic optimization method based on swarm intelligence applied in many fields of endeavor to solve technical, scientific and economic problems. Due to its ease of application, it has gained great importance in recent years. As the swarm may lose its diversity and lead to premature convergence, it is very easily trapped in local optima. To solve this problem, we propose, in this research work, an cooperative multi-swarm particle swarm optimization algorithm called cooperative multi-swarm particle swarm optimization (C-MsPSO). The introduced algorithm divides the entire population into four cooperative sub-swarms with an adaptive and time-varying inertia weight. The particles of each sub-swarm share the best overall optimum to ensure the cooperation between the four sub-swarms . On the other hand, the adaptive and time-varying inertia weight is used to create search potential and effectively maintain a balance between the local research (exploitation) and the global (exploration). To show the efficiency of the developed C-MsPSO algorithm, several uni-modal and multi-modal benchmark test functions are considered. The introduced algorithm demonstrates surprising efficiency and precision in identifying the optimal solution.The experimental results reveal that C-MsPSO outperforms the other PSO algorithms on twelve reference functions.
粒子群优化是一种基于群体智能的随机优化方法,应用于许多努力解决技术、科学和经济问题的领域。由于其易于应用,近年来得到了极大的重视。由于群体可能失去多样性,导致过早收敛,很容易陷入局部最优。为了解决这一问题,本文提出了一种协同多群粒子群优化算法,称为协同多群粒子群优化算法(cooperative multi-swarm particle swarm optimization, C-MsPSO)。该算法采用自适应时变惯性权值将整个种群划分为4个协同子群。每个子群的粒子共享最优的整体最优,以保证四个子群之间的协作。另一方面,利用自适应时变惯性权值创造搜索潜力,有效保持局部研究(开发)与全局(探索)的平衡。为了证明所开发的C-MsPSO算法的有效性,考虑了几种单峰和多峰基准测试函数。所引入的算法在识别最优解方面显示出惊人的效率和精度。实验结果表明,C-MsPSO算法在12个参考函数上优于其他PSO算法。
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引用次数: 3
期刊
2021 IEEE 2nd International Conference on Signal, Control and Communication (SCC)
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