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Chinese Automation Congress

作者： Kongtao Zhu Xiwei Liu Hongxue Yang Beijing Polytechnic College of Telecom. Eng. Beijing China The State Key Laboratory of Management and Control for Complex Systems Qingdao Academy of Intelligent Industries Qingdao Beijing China

Generative adversarial networks (GANs) coming from the game theory allow machines to learn deep representations without extra training data. By training two adversarial networks, including a generator and a discriminator, GANs could get the distribution of the real samples. This capability makes it a prospect learning method in image synthesis, image recognition, image translation etc. In this paper, we survey the state of the art of GANs by categorizing the GANs into four classifications on the basis of GANs' functions and list two application domains: vision computing & natural language processing (NLP) regarding to GANs' applications.

关键词： Generative adversarial networks Vision computing Natural language processing (NLP)

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Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

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International Journal of systems Science 2017年第14期48卷 3118页

作者： Meng, Su Chen, Jie Sun, Jian Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing P.R. China

This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.

关键词： Non-uniform sampling time-varying delay networked control systems output feedback control stability

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A robust and adaptive interharmonics detection method

A robust and adaptive interharmonics detection method

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2017 IEEE Conference on Energy Internet and Energy system Integration, EI2 2017

作者： Jin, Zongshuai Zhang, Hengxu Shi, Fang Shi, Xiaohan Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education School of Electrical Engineering Shandong University Jinan China

ISBN: (纸本)9781538614273

In the active distribution network (ADN), the interharmonic distortion level is aggravated due to the growing penetration of distributed generations and wide application of power electronic loads. The interharmonics, even at a low amplitude level, can cause power quality problems, deteriorate the measurement accuracies of the advanced metering infrastructures, and increase the possibilities of power system oscillations. In this paper, an interharmonic detection method is proposed to effectively detect the interharmonic components of the power system even with the extremely noisy signals using a totally data dependent threshold. This adaptive threshold is determined iteratively based on the statistical character of the background noise bins. Case studies show that the adaptive threshold is robust with severely noisy signal for both the steady-state and dynamic interharmonic conditions. © 2017 IEEE.

关键词： Iterative methods

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DC Motor Speed control Based on system Identification and PID Auto Tuning 36

DC Motor Speed Control Based on System Identification and PI...

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第36届中国控制会议

作者： Wei-Jie Tang Zhen-Tao Liu Qian Wang School of Industrial Automation Beijing Institute of Technology School of Automation China University of Geosciences Hubei key Laboratory of Advanced control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Speed control mode of a DC motor without knowing the specific parameters of the motor is *** approximate mathematical model of the control system is obtained by the system identification when the output of the system is measured by loading the specific input *** PID control algorithm is adopted and the P,I,and D parameters are obtained by auto *** in the loop（HIL） experiments are carried out on MATLAB and Arduino platform,in which the experimental results demonstrate the feasibility of the proposal.

关键词： DC motor system Identification PID control HIL Experiment Automatic Code Generation

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A Soft-Sensing Model for Oxygen-Content in Flue Gases of Coal-Fired Power Plant Based on Neural Network

A Soft-Sensing Model for Oxygen-Content in Flue Gases of Coa...

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第37届中国控制会议

作者： Xin Chen Jingcheng Wang Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University

As the main force of power generation in China, coal-fired power plants have great significance for energy conservation and emission reduction. The oxygen content in flue gases is an important index to reflect the combustion efficiency of the boiler, and the accurate monitoring is an effective way to improve combustion efficiency. Based on the BP neural network, a soft-sensing model for oxygen content in flue gases is proposed in this paper, this article, taking a boiler combustion system of 600 MW coal-fired power plant unit in Jiaxing, Zhejiang as the research object, through real-time measurement data of DCS system, a flue gases oxygen content model is established, and this model has realized the soft measurement to flue gases oxygen content, the simulation results prove the validity of the soft sensing model. This model has great significance to the monitoring of the oxygen content in flue gases of boiler combustion system and the further study of combustion optimization on this basis.

关键词： BP Neural Network Flue Gases Oxygen Content Soft Sensing Model

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key Technologies of Time-Sensitive Networking and Its Application

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IOP Conference Series: Materials Science and Engineering 2020年第4期782卷

作者： Qing Li Dong Li Xinbo Sun Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang 110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110016 China University of Chinese Academy of Sciences Beijing 100049 China

Network is the core element of many industrial and automation systems. In the future, more attention will be paid to convergent and unified network. Time-critical traffic and non-time-critical traffic need to share communication channels. The goal of the IEEE TSN task group is to extend the existing Ethernet standard to achieve a degree of certainty that meets the hard-real-time requirements of modern control networks in the industrial automation and automotive industries. Time sensitive network (TSN) is characterized by low jitter, low delay and deterministic transmission. It can transmit critical and non-critical traffic in the same network, which is very suitable for time- critical applications with high requirements on transmission delay. This paper briefly summarizes the key components of TSN, studies the key technologies, and carries out a simple traffic scheduling experiment on the switch based on 802.1Qbv function, and finally analyzes the application of TSN in industrial automation and automobile industry.

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UKF based Fault Detection and State Estimation for Nonlinear systems with Correlated Noise 36

UKF based Fault Detection and State Estimation for Nonlinear...

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第36届中国控制会议

作者： Hongxue Chen Liping Yan Yuanqing Xia Mengyin Fu Bo Xiao Guangzheng Hu Huifang Li Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781538629185

State estimation and fault diagnosis are essential topics for dynamic *** Kalman fllter（UKF） has been widely applied in nonlinear *** classical UKF algorithm is built on the premise that process noise and measurement noise is *** practical problems,this assumption is not always *** addition,due to the limitation of communication and sensor fault,etc.,data missing or unreliable measurements will happen ***,it is very important to study the state estimation of nonlinear systems with unreliable measurements and correlated *** this paper,an UKF based state estimation algorithm with unreliable observations under correlated noise is presented.A numerical example is given to show the feasibility and effectiveness of the presented algorithm.

关键词： fault detection state estimation correlated noise nonlinear system

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A smooth double proximal primal-dual algorithm for a class of distributed nonsmooth optimization problem

arXiv

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arXiv 2018年

作者： Wei, Yue Fang, Hao Zeng, Xianlin Chen, Jie Pardalos, Panos M. School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China Industrial and Systems Engineering University of Florida

This technical note studies a class of distributed nonsmooth convex consensus optimization problem. The cost function is a summation of local cost functions which are convex but nonsmooth. Each of the local cost functions consists of a twice differentiable (smooth) convex function and two lower semi-continuous (nonsmooth) convex functions. We call this problem as single-smooth plus double-nonsmooth (SSDN) problem. Under mild conditions, we propose a distributed double proximal primal-dual optimization algorithm. The double proximal operator is designed to deal with the difficulty caused by the unproximable property of the summation of those two nonsmooth functions. Besides, it can also guarantee that the proposed algorithm is locally Lipschitz continuous. An auxiliary variable in the double proximal operator is introduced to estimate the subgradient of the second nonsmooth function. Theoretically, we conduct the convergence analysis by employing Lyapunov stability theory. It shows that the proposed algorithm can make the states achieve consensus at the optimal point. In the end, nontrivial simulations are presented and the results demonstrate the effectiveness of the proposed algorithm. Copyright © 2018, The Authors. All rights reserved.

关键词： Cost functions

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Mathematical model of brain tumour growth with drug resistance

arXiv

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arXiv 2020年

作者： Trobia, José Tian, Kun Batista, Antonio M. Grebogi, Celso Ren, Hai-Peng Santos, Moises S. Protachevicz, Paulo R. Borges, Fernando S. Szezech, José D. Viana, Ricardo L. Caldas, Iberê L. Iarosz, Kelly C. Department of Mathematics and Statistics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Shaanxi Key Lab of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’anPR710048 China Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenAB24 3UE United Kingdom Xi’an Technological University Xi’anPR710021 China Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Faculdade de Telêmaco Borba FATEB Telêmaco BorbaPR84266-010 Brazil

Brain tumours are masses of abnormal cells that can grow in an uncontrolled way in the brain. There are different types of malignant brain tumours. Gliomas are malignant brain tumours that grow from glial cells and are identified as astrocytoma, oligodendroglioma, and ependymoma. We study a mathematical model that describes glia-neuron interaction, glioma, and chemotherapeutic agent. In this work, we consider drug sensitive and resistant glioma cells. We show that continuous and pulsed chemotherapy can kill glioma cells with a minimal loss of neurons. © 2020, CC BY.

关键词： Tumors

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Fault Location in Active Distribution Network Based on Convariance Matrix and PMU Data

Fault Location in Active Distribution Network Based on Conva...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Xiangnv Wang Linlin Zhang Fang Shi Hengxu Zhang Yong Zhang Jian Zhou The Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China State Grid Shanghai Municipal Electric Power Company Shanghai China

Fault diagnosis and location of distribution network is a difficult problem. With the integration of the distributed generation, the multi-source of the fault current makes the problem more complex. This paper proposes a fault diagnosis method based on synchronized measurement information matrix, which includes two procedures: 1) to detect the occurrence of the fault; 2) to locate the fault section and determine the fault type. Firstly, the local covariance matrix is defined by introducing sliding window based on synchronous phasor information. Then, a local information covariance matrix is constructed by taking each PMU's data as a sample at a certain moment to detect the occurrence of the fault. The fault segment is located and the fault type is determined via improving the local covariance matrix. Finally, a simulation example is used to verify the effectiveness and reliability of the proposed method.

关键词： Covariance matrices Phasor measurement units Symmetric matrices Current measurement Fault location Fault currents

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