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2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)最新文献

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Research on Bidirectional DC/DC Converter Based on Passive Control 基于无源控制的双向DC/DC变换器研究
X. Tang, Juan Li, Qihong Chen, Liyan Zhang
In order to improve the response speed and dynamic performance of bi-directional DC/DC converter, a passive controller is used to control the bi-directional DC/DC converter in electric vehicle. Based on its working characteristics, an EL model of bi-directional DC/DC converter is established to verify the passivity of the system, and then passive controller is designed. By using MATLAB/Simulink to simulate, the performance of the system controlled by passive controller and PI controller is analyzed and compared, the results show that passive controller has better control effect, and the scheme that passive controller applied in bidirectional DC/DC converter is feasible.
为了提高双向DC/DC变换器的响应速度和动态性能,采用无源控制器对电动汽车双向DC/DC变换器进行控制。根据其工作特点,建立了双向DC/DC变换器的EL模型,验证了系统的无源性,并设计了无源控制器。通过MATLAB/Simulink仿真,对被动控制器和PI控制器控制的系统性能进行了分析和比较,结果表明被动控制器具有更好的控制效果,并且被动控制器应用于双向DC/DC变换器的方案是可行的。
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引用次数: 2
Design of A Double-blockchain Structured Carbon Emission Trading Scheme with Reputation 具有信誉的双区块链结构碳排放交易方案设计
Xufeng Liang, Y. Du, Xu Wang, Yuliang Zeng
This paper proposes a double-blockchain structured trading scheme (DBR-ETS) in carbon emission permits secondary market and introduces the enterprises' reputation, which is used to urge enterprises to actively invest in carbon emission reduction, and ultimately achieve carbon emission reduction in the overall society. The application of blockchain technology guarantees the security and privacy of distributed system. The confirmation chain and financial chain in the double-blockchain structure divide the transaction into two relatively independent processes, which can not only alleviate the transaction redundancy in the system but also improve the security of the system through the mutual verification of the two chains. The reputation-based transaction fee mechanism allows enterprises to promote their reputation by increasing investment in emission reduction. In the case study, we verified the superiority of the double-blockchain structure and the effect of the transaction fee mechanism on emission reduction.
本文提出了碳排放许可二级市场的双区块链结构化交易方案(DBR-ETS),并引入企业信誉,以此来促使企业积极投入碳减排,最终实现全社会的碳减排。区块链技术的应用保证了分布式系统的安全性和保密性。双区块链结构中的确认链和金融链将交易划分为两个相对独立的过程,既可以缓解系统中的交易冗余,又可以通过两条链的相互验证提高系统的安全性。基于信誉的交易费用机制,允许企业通过增加减排投入来提升企业信誉。在案例研究中,我们验证了双区块链结构的优越性和交易收费机制对减排的效果。
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引用次数: 15
On Theoretical Analysis of Single Hidden Layer Feedforward Neural Networks with Relu Activations 带Relu激活的单隐层前馈神经网络的理论分析
Guorui Shen, Ye Yuan
During past decades, extreme learning machine has acquired a lot of popularity due to its fast training speed and easy-implementation. Though extreme learning machine has been proved valid when using an infinitely differentiable function like sigmoid as activation, existed extreme learning machine theory pays a little attention to consider non-differentiable function as activation. However, other non-differentiable activation function, rectifier linear unit (Relu) in particular, has been demonstrated to enable better training of deep neural networks, compared to previously wide-used sigmoid activation. And today Relu is the most popular choice for deep neural networks. Therefore in this note, we consider extreme learning machine that adopts non-smooth function as activation, proposing that a Relu activated single hidden layer feedforward neural network (SLFN) is capable of fitting given training data points with zero error under the condition that sufficient hidden neurons are provided at the hidden layer. The proof relies on a slightly different assumption from the original one but remains easy to satisfy. Besides, we also found that the squared fitting error function is monotonically non-increasing with respect to the number of hidden nodes, which in turn means a much wider SLFN owns much expressive capacity.
在过去的几十年里,极限学习机以其快速的训练速度和易于实现的特点获得了广泛的应用。虽然极限学习机在使用sigmoid等无穷可微函数作为激活时已经被证明是有效的,但是现有的极限学习机理论很少关注不可微函数作为激活。然而,与之前广泛使用的s型激活相比,其他不可微的激活函数,特别是整流线性单元(Relu),已被证明能够更好地训练深度神经网络。今天,Relu是深度神经网络最流行的选择。因此在本文中,我们考虑采用非光滑函数作为激活的极限学习机,提出一个Relu激活的单隐层前馈神经网络(SLFN)在隐层提供足够的隐藏神经元的条件下,能够以零误差拟合给定的训练数据点。这个证明所依赖的假设与最初的假设略有不同,但仍然很容易满足。此外,我们还发现,平方拟合误差函数对于隐藏节点的数量是单调不增加的,这意味着更宽的SLFN具有更大的表达能力。
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引用次数: 6
Design of Automatically Conveying Materials Control System Based on TIA portal Configuration Software 基于TIA门户组态软件的自动输送物料控制系统设计
Kou Zuxing, Zhang Wei, Zhang Libao
In this paper, the automatic control system is composed of TIA portal configuration software and SIEMENS PLC. The SIEMENS PLC S7-300 module acts as the main control unit, Two kinds of materials, dimethyl sulfate and liquid alkali, were put into 9 and 5 metering tanks respectively. Configuration by using the upper computer software TIA portal, WinCC screen can real-time monitor and control the feeding of each measuring tank in the post. At the same time, the feeding quantity of each measuring tank in the post can be automatically stored in the SQL Server 2005 database. With the help of PC software, the data in the database can be invoked, real-time queries can be carried out in the form of electronic reports, and prints can be exported at any time. The company can greatly improve the production efficiency, improve the stability and accuracy of each beating, reduce the impact of human factors on the safety of beating in the process of beating, and reduce the safety risk.
本文的自动控制系统由TIA门户组态软件和SIEMENS PLC组成。西门子PLC S7-300模块作为主控单元,将硫酸二甲酯和液碱两种物料分别放入9个计量槽和5个计量槽中。通过上位机配置软件TIA门户,WinCC屏幕可以实时监控各测槽的进料情况。同时,各计量槽在岗位上的进料量可自动存入SQL Server 2005数据库。借助PC软件,可调用数据库中的数据,以电子报表的形式进行实时查询,并可随时输出打印件。公司可以大大提高生产效率,提高每次打浆的稳定性和准确性,减少打浆过程中人为因素对打浆安全的影响,降低安全风险。
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引用次数: 1
Container number localization based on SSD algorithm 基于SSD算法的集装箱编号定位
Bingqian Ding, Jianming Guo, Junhong Hu
After R-CNN and other classical frameworks were proposed, deep learning based target positioning framework has gradually become the mainstream. The SSD (Single Shot MultiBox Detector) framework model was used to locate the container number. By comparing the locating effects of different labeling methods for training samples, the basic unit that label as Single row or Single column is much better. With the actual size and proportion of the container number as reference, that modifying the feature layers which are used in SSD frame to generate the default box and adjusting the size of the feature map could adapt to the localization better. The result show that in the complex container number scenario, the accuracy based on SSD network to detect container number reaches 78%.
在R-CNN等经典框架被提出后,基于深度学习的目标定位框架逐渐成为主流。采用SSD (Single Shot MultiBox Detector)框架模型定位箱号。通过比较不同标记方法对训练样本的定位效果,标记为单行或单列的基本单元定位效果要好得多。以集装箱号的实际尺寸和比例为参考,修改SSD帧中使用的特征层生成默认框,调整特征图的大小,可以更好地适应定位。结果表明,在复杂箱号场景下,基于SSD网络的箱号检测准确率达到78%。
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引用次数: 0
Gaussian Kernel Least Mean Square Algorithm With Improved Novelty Criterion 改进新颖性准则的高斯核最小均方算法
Fuping Wang, Yixin Su, Zhiwen Leng, Yue Qi
The kernel-based adaptive algorithm has been widely applied to noise cancellation, but the computational complexity of kernel function causes it can't perform well in embedded real-time control system. This paper proposes a design of the Gaussian kernel least mean square algorithm with improved novelty criterion, which aims to reduce computational load with universal approximation and fast convergence speed. The methodology slows down the growth rate of the network by multiple operations on the training set. It finds out the filter parameter from the collection data by improved novelty criterion, so the filter network has a much smaller scale and computation complexity, which allow it to be used in the embedded real-time control system.
基于核的自适应算法在噪声消除中得到了广泛的应用,但由于核函数的计算量大,使得该算法在嵌入式实时控制系统中表现不佳。本文提出了一种改进新颖性准则的高斯核最小均方算法设计,以通用逼近和快速收敛来减少计算量。该方法通过对训练集进行多次操作来减缓网络的增长速度。采用改进的新颖性判据从采集的数据中找出滤波参数,使滤波网络具有更小的规模和计算量,可用于嵌入式实时控制系统。
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引用次数: 0
Research on Digital Marketing Strategies of Fast Fashion Clothing Brands Based on Big Data 基于大数据的快时尚服装品牌数字化营销策略研究
Y. Liu, Taoye Zhang
With the rapid development of fast fashion brands in today's market, a large number of international fast fashion brands have entered the clothing market in China, which has enabled Chinese consumers to experience something entirely new by means of digital marketing strategies, thus making China's fast fashion clothing brands in an inferior position. ZARA, HM, UNIQLO and other leading fast fashion brands have developed rapidly in China, which is inseparable from their marketing strategies. Therefore, this paper firstly summarizes fast fashion brand, big data and digital marketing, collects data released by authoritative agencies, and analyses the necessity of fast fashion brands entering the digital stage. Secondly, the successful cases of digital marketing of representative fast fashion brands are studied in detail. Finally, by summing up the enlightening conclusions of the study, this paper puts forward some suggestions on the development strategy of digital marketing for fast fashion brands in China, and creates some marketing strategies suitable for the development of Chinese enterprises themselves.
随着快时尚品牌在当今市场的快速发展,大量的国际快时尚品牌进入了中国的服装市场,这使得中国消费者通过数字营销策略来体验全新的东西,从而使中国的快时尚服装品牌处于劣势地位。ZARA, HM, UNIQLO等领先的快时尚品牌在中国发展迅速,这与他们的营销策略是分不开的。因此,本文首先对快时尚品牌、大数据和数字营销进行总结,收集权威机构发布的数据,分析快时尚品牌进入数字化阶段的必要性。其次,详细研究了具有代表性的快时尚品牌数字化营销的成功案例。最后,通过总结研究的启示结论,对中国快时尚品牌的数字营销发展策略提出一些建议,并创造出一些适合中国企业自身发展的营销策略。
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引用次数: 5
A Hough Line Detection Based Glass Surface Defects Recognition Algorithm 基于霍夫线检测的玻璃表面缺陷识别算法
Zifan Li, Hua Zhou
This paper proposes a defect detection algorithm based on defects feature on the glass surface. The process of defects recognition can be divided into five parts. First, median filter is used to eliminate the noise jamming of the glass image. Then laplacian sharping method is applied to enhance the image contrast. After that, the image is segmented by threshold to extract defects. In order to solve the problem of the noise in binary image processing, this paper uses morphological closure operation to remove the tiny connected areas. Finally, scratches are detected by Hough transform. The results of experiment verified that, compared with traditional methods, image processing based on the proposed method has higher detection efficiency and accuracy.
提出了一种基于玻璃表面缺陷特征的缺陷检测算法。缺陷识别的过程可分为五个部分。首先,采用中值滤波消除玻璃图像的噪声干扰。然后采用拉普拉斯锐化方法增强图像对比度。然后,对图像进行阈值分割,提取缺陷。为了解决二值图像处理中的噪声问题,本文采用形态学闭合运算去除微小的连通区域。最后利用霍夫变换检测划痕。实验结果证明,与传统方法相比,基于该方法的图像处理具有更高的检测效率和精度。
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引用次数: 1
Research on Structural Measuring Point Optimization Method Based on Improved Particle Swarm Optimization 基于改进粒子群算法的结构测点优化方法研究
Guan Lu, Tongyang Feng, Xinyong Ma, Yiming Xu
Aiming at the problem of too many measuring points and difficult optimization in the process of I-beam structure stress state analysis, an improved particle swarm optimization algorithm based on simulated annealing and genetic algorithm is proposed, which considers the identification error of stress state and the optimization of measuring points comprehensively to screen the measuring points. Firstly, the initialization, selection, crossover and mutation of genetic algorithm are integrated into particle swarm optimization; secondly, the idea of simulated annealing is introduced into the mutation part. The improved particle swarm optimization algorithm improves the premature and poor local optimization of the standard particle swarm optimization algorithm. Compared with the standard particle swarm optimization, the improved particle swarm optimization has better stability, stronger anti-premature ability and 60% higher accuracy. The simulation results of measuring point selection and stress state identification of I-beam show that the improved particle swarm optimization algorithm has high efficiency in the process of point selection of stress state identification. The error of force state identification to select points is less than 3%. In engineering application, it provides a better method for stress state identification.
针对工字钢结构应力状态分析过程中测点多、优化难的问题,提出了一种基于模拟退火和遗传算法的改进粒子群优化算法,综合考虑应力状态识别误差和测点优化,对测点进行筛选。首先,将遗传算法的初始化、选择、交叉和变异融入到粒子群优化中;其次,在突变部分引入了模拟退火的思想。改进的粒子群优化算法改善了标准粒子群优化算法局部寻优过早和较差的问题。与标准粒子群算法相比,改进后的粒子群算法稳定性更好,抗早熟能力更强,准确率提高60%。工字钢测点选择和应力状态识别的仿真结果表明,改进的粒子群算法在应力状态识别的测点选择过程中具有较高的效率。力状态识别对选择点的误差小于3%。在工程应用中,为应力状态识别提供了较好的方法。
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引用次数: 0
Planar formation control using tensegrity structures and experiments 平面编队控制的张拉整体结构和实验
Qingkai Yang, Yunlong Pan, Bo Zhou, H. Fang
This paper presents a framework on how to achieve prescribed planar formations using the concept of tensegrity structures. Given a group of robots with desired formation shape, we first design the underlying interaction topology based on the Polygon Theorem, yielding a super stable structure along with the robots' configuration. Then some basic control laws are introduced for mobile robots to model the interplay relationship between the neighbouring nodes in a self-equilibrated tensegrity structure. To fully validate the effectiveness of the tensegrity-motivated formation control strategy, we carry out not only numerical simulations but also experiments on two types of mobile robot platforms, wheeled mobile robots and unmanned aerial vehicles (UAVs).
本文提出了如何使用张拉整体结构的概念来实现规定的平面结构的框架。给定一组具有所需队形的机器人,我们首先基于多边形定理设计了底层交互拓扑,得到了一个超稳定的结构和机器人的构型。在此基础上,引入了移动机器人的基本控制律,对自平衡张拉整体结构中相邻节点之间的相互作用关系进行了建模。为了充分验证张拉整体编队控制策略的有效性,我们不仅进行了数值模拟,还在轮式移动机器人和无人机两种移动机器人平台上进行了实验。
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引用次数: 0
期刊
2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)
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