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2019 2nd International Conference on Power and Embedded Drive Control (ICPEDC)最新文献

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Comparative analysis of fuel cell based positive and negative output superlift converter 基于燃料电池的正、负输出超升力转换器的比较分析
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036694
A.J Nirmitha, V. Chamundeeswari, Jennifer Dania T
In the revolutionary world involving various power electronic devices, DC-DC converters has created a great impact. The two converters namely positive output superlift converters(POSLC) and negative output superlift converters(NOSLC) are taken for analysis in this work.It is fed from a source of fuel cell. Fuel cells are eco-friendly,noise free device providing lower heat transmission making them reliable for various applications. The converter circuits are simulated and the results are verified.
在涉及各种电力电子器件的革命世界中,DC-DC变换器产生了巨大的影响。本文采用正输出超升力变换器(POSLC)和负输出超升力变换器(NOSLC)两种变换器进行分析。它由燃料电池供电。燃料电池是一种环境友好、无噪音的设备,传热率低,适用于各种应用。对变换器电路进行了仿真,并对仿真结果进行了验证。
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引用次数: 0
Closed-loop Performance and Analysis of a Real Time Non-linear Bioreactor Process 实时非线性生物反应器过程的闭环性能与分析
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036666
X. Joanofarc, D. Nivedhika, S. Patnaik, R. Panda
The bioreactor, a multivariable system, is the principle organ of biochemical Industrial processes where active microbial cells are grown and utilized for various useful biological products. To attain optimal growth of microbial cells a constructively designed bioreactor with an appropriate control method is essential. Nonlinearity is also an underlying property of the bioreactor that degrades the growth parameters and affects the biomass growth and its performance. IMC-PID based on Laurent series is employed in this paper for a real time bioreactor with the essential knowledge of its reaction kinetics and a complete understanding of its working. This paper explores the steady state and dynamic nonlinear behaviour of a typical bioreactor elaborately. To start with, an example of a multivariable fed-batch process of E.coli fermentation is considered for which the Relative Gain Array (RGA) and directional sensitivity are analyzed that provides proper I/O pairing. The Strongest input-output pair is identified and a nonlinear model is arrived using the SISO real time data. For fed batch E.coli fermentation, the closed loop performances are analysed using IMC-PID Laurent series method. Finally, the closed loop results are then validated by conducting real time experiments.
生物反应器是一个多变量系统,是生物化学工业过程的主要器官,活性微生物细胞在其中生长并用于各种有用的生物产品。为了达到微生物细胞的最佳生长,一个具有适当控制方法的建设性设计的生物反应器是必不可少的。非线性也是生物反应器的一个潜在特性,它降低了生长参数,影响了生物量的生长及其性能。本文将基于Laurent级数的IMC-PID用于实时生物反应器,对其反应动力学有了基本的了解,并对其工作有了完整的了解。本文详细探讨了典型生物反应器的稳态和动态非线性行为。首先,考虑了一个多变量间歇发酵过程的例子,分析了相对增益阵列(RGA)和方向灵敏度,以提供适当的I/O配对。利用SISO实时数据识别出最强输入输出对,并建立非线性模型。采用IMC-PID洛朗级数法对间歇式大肠杆菌补料发酵的闭环性能进行了分析。最后,通过实时实验对闭环结果进行验证。
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引用次数: 1
Developing Multi-Agent Based Micro-Grid Management System in JADE 基于多智能体的JADE微网管理系统的开发
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036562
H. Priyadarshana, K.T.M.U. Hemapala, W.D.A. S Wijayapala, V. Saravanan, M.A. Kalhan S. Boralessa
This paper presents an implementation of a Multi-Agent based Energy Management System for a micro grid with JADE (Java Agent Development Framework). The MAS is applied for a micro grid consisting of different distributed energy sources such as solar PV system, wind power system, diesel generator system, storage system, and critical and noncritical loads. Different agents are developed on JADE framework and they are given responsibilities of relevant DES’s (Distributed Energy Source) and loads. A runtime environment for Agents are created and a dynamic simulation model developed through JADE considering the intermittent qualities of renewable energy sources. The case studies presented on this paper are modeled on JADE platform. Developing MAS in JADE runtime environment using AOP (Agent-Oriented Programming) helps agents to operate with all their autonomous, rational, reactive, and proactive qualities. The use of MAS concept in micro grids improves its efficiency in various aspects. The MAS based micro grid management system implemented in JADE platform and can be used to carry out various simulations to study about agent behaviors in different environments and different system objectives. The main purpose of the paper is to prove the possibility of using multi-agent concept in micro grid energy management systems.
本文利用Java Agent开发框架(JADE)实现了一个基于多Agent的微电网能源管理系统。MAS适用于由不同分布式能源组成的微电网,如太阳能光伏系统、风力发电系统、柴油发电系统、存储系统以及临界和非临界负荷。在JADE框架上开发不同的agent,并赋予它们相应的DES (Distributed Energy Source)和负载的职责。考虑可再生能源的间歇性特性,通过JADE建立agent运行环境和动态仿真模型。本文的案例研究是在JADE平台上建模的。使用AOP(面向代理的编程)在JADE运行时环境中开发MAS,可以帮助代理以其所有自主的、理性的、反应性的和主动的特性进行操作。MAS概念在微电网中的应用,在各个方面提高了微电网的效率。基于MAS的微网管理系统在JADE平台上实现,可以进行各种仿真,研究不同环境和不同系统目标下智能体的行为。本文的主要目的是为了证明多智能体概念在微电网能源管理系统中应用的可能性。
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引用次数: 1
Topological Study of Derived Converters- A review 衍生变换器的拓扑研究综述
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036711
Partha Sarathi Subudhi, S. Krithiga
Development in power converter research area has given birth to many derived converter systems. A derived converter is invented by employing the advantages of available conventional converters. The derived converters carry many advantages compared to the conventional converters such as: lesser operational loss, single stage power conversion, simplified control circuit, usage of less number of power electronic components, less manufacturing cost and compact design in order to fit for most of the power electronic applications. Derived converters play a major role in integrating renewable energy system to the present smart home system. This paper focuses on the review of different derived converters available with their control strategies and their advantages and limitations.
随着功率变换器研究领域的发展,衍生出了许多变换器系统。利用现有传统变换器的优点,发明了一种衍生变换器。与传统变换器相比,衍生变换器具有许多优点,如:运行损耗小,单级功率转换,简化控制电路,使用较少数量的电力电子元件,制造成本低,设计紧凑,以适应大多数电力电子应用。衍生变流器在将可再生能源系统集成到当前的智能家居系统中发挥着重要作用。本文主要综述了现有的各种衍生变换器及其控制策略,以及它们的优点和局限性。
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引用次数: 1
Histogram Visualization of Smart Grid data using Mapreduce algorithm 基于Mapreduce算法的智能电网数据直方图可视化
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036693
Ashika Dev Teres
This research emphasis the utility of Big Data analytics, as an upcoming trend, in smart grid data. Large datasets are handled using a relatively newer technology called big data analytics. Volume, variety, velocity, veracity, value, and complexity are the six main characteristics of big data. Smart grids have begun to generate tremendous volume of data which is exponentially increasing with the day and possess majority of the big data characteristics. Earlier researches on big data for smart grids has emphasis only on necessities, design, concepts, problems, challenges and further research directions but this work focus on developing solutions for processing the massive data sets. As a study a residential electricity demand profile with 10 million records is considered and the ‘mapreduce’ function in MATLAB is used for dimensionality reduction. Histograms of power consumption pattern with ‘mapreduce’ helps to visualize huge sets of data without the need to load all the observations instantaneously into memory. This will help in further analysis power consumption pattern and predicting the future power demand and short term /long term load forecasting
本研究强调了大数据分析在智能电网数据中的应用,这是一个即将到来的趋势。处理大型数据集使用一种相对较新的技术,称为大数据分析。数量、种类、速度、准确性、价值和复杂性是大数据的六大主要特征。智能电网已开始产生巨大的数据量,且数据量呈指数级增长,具备了大数据的大部分特征。早期关于智能电网大数据的研究主要侧重于需求、设计、概念、问题、挑战和进一步的研究方向,而本工作则侧重于开发处理海量数据集的解决方案。作为研究,考虑了1000万条记录的住宅电力需求曲线,并使用MATLAB中的“mapreduce”函数进行降维。使用“mapreduce”的功耗模式直方图有助于可视化大量数据集,而无需将所有观察结果立即加载到内存中。这将有助于进一步分析电力消耗模式,预测未来的电力需求和短期/长期负荷预测
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引用次数: 3
Speed Control of BLDC Motor Using Neural Network Controller and PID Controller 基于神经网络控制器和PID控制器的无刷直流电动机速度控制
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036695
Archana Mamadapur, G. Unde Mahadev
The primary aim of this paper is to control the speed of brushless DC motor using Artificial Neural Network (ANN) controller and PID controller. Detailed analysis is performed based on the simulation results of both the methods. A neural control based speed control system of brushless DC motor is designed by analyzing the mathematical model of BLDC motor. Plant model identification is done in Simulink software of MATLAB to identify the ANN block of BLDC motor drive system. Reference control model is designed to give the ideal values of control parameters when the control system responds to the command signal. The performance results of PID controller and ANN controller are compared with reference model output of BLDC motor drive system in MATLAB Simulink environment. Comparative study concludes that ANN based speed control method eliminates the overshoot, reduces the settling time of the system response. It is observed that the ANN based simulation results are closer to the ideal reference control model response than PID based.
本文的主要目的是利用人工神经网络(ANN)控制器和PID控制器对无刷直流电动机进行转速控制。根据两种方法的仿真结果进行了详细的分析。通过分析无刷直流电动机的数学模型,设计了一种基于神经网络控制的无刷直流电动机速度控制系统。在MATLAB的Simulink软件中对无刷直流电机驱动系统的人工神经网络模块进行辨识。设计参考控制模型,给出控制系统响应指令信号时控制参数的理想值。在MATLAB Simulink环境下,将PID控制器和人工神经网络控制器的性能结果与无刷直流电机驱动系统的参考模型输出进行了比较。对比研究表明,基于人工神经网络的速度控制方法消除了超调,缩短了系统响应的稳定时间。结果表明,基于人工神经网络的仿真结果比基于PID的仿真结果更接近理想参考控制模型的响应。
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引用次数: 16
Evolutionary Algorithm based Controller Design for Grid tie Inverter to improve the Quality of Power System 基于进化算法的并网逆变器控制器设计以提高电力系统质量
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036674
K. Vijayakumar, G. Vishnuvarthanan, Eugene Yu-Dong Zhang
The core objective of this paper is to increase the overall efficacy of the inverter operation by designing a new controlling strategy by realizing a novel Monkey King Evolution Algorithm (MKEA). Providing an appropriate controller for grid connected inverter without affecting its output is the main motive of this work. During simulation, the effectiveness of the controller is investigated by the analysis of phase voltage, phase current, active power, reactive power, apparent power, grid voltage, and output voltage.
本文的核心目标是通过实现一种新的猴王进化算法(Monkey King Evolution Algorithm, MKEA)来设计一种新的控制策略,从而提高逆变器的整体运行效率。在不影响并网逆变器输出的前提下,为并网逆变器提供合适的控制器是本研究的主要动机。在仿真过程中,通过对相电压、相电流、有功功率、无功功率、视在功率、电网电压和输出电压的分析,考察了控制器的有效性。
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引用次数: 1
A Study on Segmentation and Evaluation of Leukocyte Section 白细胞切片分割与评价的研究
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036581
J. Infanta, A. Shalini, N. M. Raja, B. Anusha
Clinical image assessment plays an imperative part in the assessment of the illness in humans. Hence, in most of the disease cases, a suitable procedure is followed to record the bio-medical image in a controlled environment, which further can be evaluated by an experienced doctor or a suitable Computed-Assisted-Diagnosis (CAD) system to confirm the severity of disease; for planning suitable treatment process. In this work, a morphological operation based CAD system is developed to examine the leukocyte segment from the RGB-scale blood smear image. The presentation of developed CAD is evaluated with the other leukocyte examination procedures existing in the literature. The outcome of this work substantiate that, proposed approach is fast and efficient in extracting the leukocyte section from the blood-smear picture with improved accuracy. In this work, the validation of the proposed technique is experimentally authorized with the benchmark LISC database and the results obtained with the proposed study offers an overall accuracy of > 97.96% compared to the related existing techniques.
临床影像评估在人类疾病评估中起着至关重要的作用。因此,在大多数疾病病例中,遵循适当的程序在受控环境中记录生物医学图像,由经验丰富的医生或适当的计算机辅助诊断(CAD)系统进一步评估以确认疾病的严重程度;规划合适的处理工艺。在这项工作中,我们开发了一个基于形态学操作的CAD系统来检查rgb级血液涂片图像中的白细胞片段。用文献中已有的其他白细胞检查程序来评估发展中的CAD的表现。研究结果表明,该方法能够快速有效地从血液涂片图像中提取白细胞切片,提高准确性。在这项工作中,我们用LISC基准数据库对所提出的技术进行了实验验证,与现有相关技术相比,所提出的研究结果的总体准确性> 97.96%。
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引用次数: 0
Optimized Biodiesel Production from Crotalaria juncea L. oil for usage in Compression Ignition Engine 压缩点火发动机用芥菜油优化生产生物柴油
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036540
J. Godwin, H. Venkatesan, S. Seralathan, Premkumar T Micha
Biodiesel being the trend in replacing the conventional diesel fuel in considerate with the depletion of fossil fuel. Crotalaria juncea L. were selected as the source because availability is one of the major considerations for the fuel cost. India contributes 27% of Crotalaria juncea L. seeds among the world population. On extracting the oil from the seeds the FFA value was found to be $gt 2$% hence the two stage trans-esterification process was incorporated. The process parameters for the trans-esterification process were investigated for the optimum reaction values. On experimentation it was detailed that the molar ratio of 0.91 v/v, catalyst concentration of 0.94 wt % and reaction time of 120 min were the optimal process parameter values which gave the maximum biodiesel yield of 98.1 %. To validate the result, Bayesian regularized algorithm incorporated in Artificial Neural Network (ANN) model was utilized for the optimization of process parameters. The model was validated with performance evaluation. After predicting the process parameters it was found that the ANN predicted values were in correlation with experimental values.
随着化石燃料的日益枯竭,生物柴油是替代传统柴油的发展趋势。选择芥菜作为燃料来源,因为可获得性是燃料成本的主要考虑因素之一。印度贡献了世界上27%的芥菜种子。在从种子中提取油时,发现FFA值为$ gt $ 2 %,因此采用了两段反式酯化过程。研究了反式酯化反应的工艺参数,确定了最佳反应值。实验结果表明,在摩尔比0.91 v/v、催化剂浓度0.94 wt %、反应时间120 min的条件下,生物柴油收率可达98.1%。为了验证结果,利用人工神经网络(ANN)模型结合贝叶斯正则化算法对工艺参数进行优化。通过性能评价对模型进行了验证。通过对工艺参数的预测,发现人工神经网络的预测值与实验值具有较好的相关性。
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引用次数: 0
Performance Evaluation of Nature Inspired Algorithms for MPPT in Solar PV Systems with Partial Shading 部分遮阳太阳能光伏系统中MPPT自然启发算法的性能评价
Pub Date : 2019-08-01 DOI: 10.1109/ICPEDC47771.2019.9036599
R. Subha, S. Himavathi
Nature inspired algorithms have been found to be powerful in solving complex optimization problems due to the intelligence embedded in them. Some of these algorithms have also been used in tracking the maximum power point (MPP) in a partially shaded photovoltaic (PV) array. This paper evaluates the capability of five algorithms inspired from nature in tracking maximum power point under partial shading. The performance of the algorithms are compared in terms of their tracking accuracy, convergence time and implementation complexity to find the most suitable method for MPP tracking.
受自然启发的算法被发现在解决复杂的优化问题方面是强大的,因为它们嵌入了智能。其中一些算法也用于跟踪部分遮阳光伏(PV)阵列的最大功率点(MPP)。本文评估了五种受自然启发的算法在部分遮阳下跟踪最大功率点的能力。比较了各算法的跟踪精度、收敛时间和实现复杂度,找到了最适合MPP跟踪的方法。
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引用次数: 0
期刊
2019 2nd International Conference on Power and Embedded Drive Control (ICPEDC)
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