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第30届中国控制与决策会议

作者： Le Wei Peichen Xu School of Control and Computer Engineering North China Electric Power University

Maintaining the normal boiler drum water level is a necessary condition for stable operation of the *** boiler drum water level fluctuations do not exceed 30 mm?50 mm *** flow characteristics refers to the relationship between the valve flow and the valve *** the drum opening is controlled by adjusting the opening of the control valve,the non-linearity of the valve can affect the control quality of the control *** this paper,by using matlab2013 a to build a simulation model,the control of boiler drum water level based on nonlinear valve characteristics compensation is *** to the flow characteristics of non-linear valve,the compensator based on polynomial curve fitting method is designed to compensate the valve opening *** results verify the feasibility of this method.

关键词： Boiler drum water level valve flow characteristics curve fitting

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Model predictive load frequency control of isolated micro-grid with electrical vehicles

Model predictive load frequency control of isolated micro-gr...

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第37届中国控制会议

作者： Junjun Pan Shaoyuan Yu Miaomiao Ma School of Control ＆ Computer Engineering North China Electrical Power University

Electrical vehicles（EVs） can be used as mobile energy storage units, which could be an effective solution for LFC in an isolated micro-grid. This paper design the load frequency controller based on model predictive control（MPC） for micro-grid with electrical vehicles. The MPC controller is designed by minimizing the objective function. Meanwhile, the limitations of the output power increment and the output power increment rate of each subsystem are also considered in this paper. The simulation results show that when the system is subjected to a load step fluctuation, the proposed MPC can reasonably allocate the output of each subsystem, and quickly eliminate the frequency fluctuation, while respecting the equivalent EVs and diesel power system constraints.

关键词： Load frequency control Model predictive control Constraints Micro-grid Electrical vehicle

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Improved AHP Based on Moody Chart Method and Its Application in the Evaluation of Thermal Power Plant Operation

Improved AHP Based on Moody Chart Method and Its Application...

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第30届中国控制与决策会议

作者： Le Wei Wei Yao School of Control and Computer Engineering North China Electric Power University

The evaluation of operation status of thermal power plant plays a important role to measure whether a power plant has a good development. The traditional method of analytic hierarchy process has disadvantage in the assignment of judgment matrix, this paper tried to improve the method and applied the modified method to five thermal power plants based on Moody Chart method, and the score of economic indicators of the five power plants is calculated by both methods. The calculation of the example shows the advantage of simplicity and maneuverability in the improved method,and the case verifies the rationality of it.

关键词： The operation of thermal power plants Evaluation Analytic Hierarchy Process(AHP) Moody Chart method

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Ordinary Kriging Applied to Fluid Measurement

Ordinary Kriging Applied to Fluid Measurement

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2018 3rd International Conference on Materials Science,Machinery and Energy engineering(MSMEE 2018)

作者： Mengyuan Wang Shi Liu Yubo Liang H.I.Schlaberg School of control and computer engineering North China Electric Power University

The identification of flow pattern is a basic and important issue in multiphase systems. However, it is difficult to discern due to the complexity of two-phase flows. In this paper, ordinary Kriging（OK） is applied to reconstructed the two-phase flow patterns using some accurate data. Three typical flow patterns are preset to verify the effectiveness of the method and two quality assessments are used to verify it. Computational results demonstrate that two-phase flow patterns can be reconstructed successfully. The method is feasible for fluid measurement applications.

关键词： ordinary Kriging sensor optimization flow pattern

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Image Classification Based on Support Vector Machines

Image Classification Based on Support Vector Machines

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2018 8th International Conference on Education and Sports Education (ESE 2018)

作者： Zijun Wu North China Electric Power University School of Control and Computer Engineering

In today's society,there are a large number of picture information resources,and images are increasingly being studied in many fields,so it is very important to classify,utilize and manage images *** paper mainly studies image classification by using support vector machine(SVM),and it includes the following aspects:introducing the basic theory of SVM,discussing the feature extraction methods based on color feature,spatial features and texture features,aiming at the typical feature extraction algorithms,which includes HOG feature extraction,LBP feature extraction,and Haar-like feature extraction,comparing the advantages and disadvantages of different feature *** on color feature and HOG feature respectively,classify the image with the SVM *** test results show that the SVM classifier combined with image features has good performance,high classification accuracy,fast training speed and excellent results in the image classification of small samples.

关键词： Support vector machine HOG Image classification

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Performance–guaranteed consensus control inspired by the mammalian limbic system for a class of nonlinear multi-agents ⁎

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IFAC-PapersOnLine 2020年第2期53卷 9496-9501页

作者： Ignacio Rubio Scola Luis Rodolfo Garcia Carrillo João P. Hespanha Rogelio Lozano CIFASIS (CONICET-UNR) and Department of Mathematics National University of Rosario Rosario 2000 Argentina. Unmanned Systems Laboratory. School of Engineering and Computer Sciences Texas A&M University - Corpus Christi TexasUSA. 78412-5797. Center for Control Dynamical Systems and ComputationUniversity of California Santa Barbara CA 93106 USA. Heuristique et Diagnostic des Systemes Complexes Universit é de Technologie de Compiègne UMR CNRS 7253 60200 CompiegneFrance

Computational models of emotional learning observed in the mammalian brain have inspired diverse self-learning control approaches. These architectures are promising in terms of their fast learning ability and low computational cost. In this paper, the objective is to establish performance–guaranteed emotional learning–inspired control (ELIC) strategies for autonomous multi–agent systems (MAS), where each agent incorporates an ELIC structure to support the consensus controller. The objective of each ELIC structure is to identify and compensate model differences between the theoretical assumptions taken into account when tuning the consensus protocol, and the real conditions encountered in the real system to be stabilized. Stability of the closed-loop MAS is demonstrated using a Lyapunov analysis. Simulation results based on the consensus task of a group of inverted pendulums demonstrate the effectiveness of the proposed ELIC for stabilization of nonlinear MAS.

关键词： Multi-agents systems Biologically-inspired control Robust control Distributed control Nonlinear control

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A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning

arXiv

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arXiv 2021年

作者： Li, Zekun Zhao, Wei Shi, Feng Qi, Lei Xie, Xingzhi Wei, Ying Ding, Zhongxiang Gao, Yang Wu, Shangjie Liu, Jun Shi, Yinghuan Shen, Dinggang State Key Laboratory for Novel Software Technology Nanjing University China National Institute of Healthcare Data Science Nanjing University Nanjing210046 China School of Computer Science and Artificial Intelligence Southeast University Nanjing210018 China Department of Research and Development Shanghai United Imaging Intelligence Co. Ltd. Shanghai201807 China School of Biomedical Engineering ShanghaiTech University Shanghai China Department of Artificial Intelligence Korea University Seoul02841 Korea Republic of Department of Radiology Second Xiangya Hospital Central South University Hunan410011 China Department of Radiology Quality Control Center Changsha410011 China Department of Radiology Hangzhou First People's Hospital Zhejiang University School of Medicine Hangzhou Zhejiang China Department of Pulmonary and Critical Care Medicine Second Xiangya Hospital Central South University Changsha410011 China

How to fast and accurately assess the severity level of COVID-19 is an essential problem, when millions of people are suffering from the pandemic around the world. Currently, the chest CT is regarded as a popular and informative imaging tool for COVID-19 diagnosis. However, we observe that there are two issues - weak annotation and insufficient data that may obstruct automatic COVID-19 severity assessment with CT images. To address these challenges, we propose a novel three-component method, i.e., 1) a deep multiple instance learning component with instance-level attention to jointly classify the bag and also weigh the instances, 2) a bag-level data augmentation component to generate virtual bags by reorganizing high confidential instances, and 3) a self-supervised pretext component to aid the learning process. We have systematically evaluated our method on the CT images of 229 COVID-19 cases, including 50 severe and 179 non-severe cases. Our method could obtain an average accuracy of 95.8%, with 93.6% sensitivity and 96.4% specificity, which outperformed previous works. Copyright © 2021, The Authors. All rights reserved.

关键词： computerized tomography

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Metamorphosis of discontinuity lines and rectification of magnetic flux avalanches in the presence of noncentrosymmetric pinning forces

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Physical Review B 2021年第22期103卷 224514-224514页

作者： M. Motta L. Burger Lu Jiang J. D. González Acosta Ž. L. Jelić F. Colauto W. A. Ortiz T. H. Johansen M. V. Milošević C. Cirillo C. Attanasio Cun Xue A. V. Silhanek B. Vanderheyden Departamento de Física Universidade Federal de São Carlos 13565-905 São Carlos São Paulo Brazil Montefiore Research Unit Department of Electrical Engineering and Computer Science Université de Liège 4000 Sart Tilman Belgium School of Aeronautics Northwestern Polytechnical University Xi'an 710072 China Facultad de Ingeniería Universidad del Magdalena Santa Marta Colombia Departement Fysica Universiteit Antwerpen Groenenborgerlaan 171 B-2020 Antwerpen Belgium Nokia Bell Labs Antwerp Belgium Department of Physics University of Oslo POB 1048 Blindern 0316 Oslo Norway CNR-SPIN c/o Università degli Studi di Salerno I-84084 Fisciano (Sa) Italy Dipartimento di Fisica “E.R. Caianiello” Università degli Studi di Salerno I-84084 Fisciano (Sa) Italy School of Mechanics Civil Engineering and Architecture and MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an 710072 China Experimental Physics of Nanostructured Materials Q-MAT CESAM Université de Liège B-4000 Sart Tilman Belgium

Considering a noncentrosymmetric pinning texture composed of a square array of triangular holes, the magnetic flux penetration and expulsion are investigated experimentally and theoretically. A direct visualization of the magnetic landscape obtained using a magneto-optical technique on a Nb film is complemented by a multiscale numerical modeling. This combined approach allows the magnetic flux dynamics to be identified from the single flux quantum limit up to the macroscopic electromagnetic response. Within the theoretical framework provided by time-dependent Ginzburg-Landau simulations, an estimation of the in-plane current anisotropy is obtained and its dependence with the radius of the curvature of hole vertices is addressed. These simulations show that current crowding plays an important role in channeling the flux motion, favoring hole-to-hole flux hopping rather than promoting interstitial flux displacement in between the holes. The resulting anisotropy of the critical current density gives rise to a distinct pattern of discontinuity lines for increasing and decreasing applied magnetic fields, in sharp contrast to the invariable patterns reported for centrosymmetric pinning potentials. This observation is partially accounted for by the rectification effect, as demonstrated by finite-element modeling. At low temperatures, where magnetic field penetration is dominated by thermomagnetic instabilities, highly directional magnetic flux avalanches with a fingerlike shape are observed to propagate along the easy axis of the pinning potential. This morphology is reproduced by numerical simulations. Our findings demonstrate that anisotropic pinning landscapes and, in particular, ratchet potentials produce subtle modifications to the critical state field profile that are reflected in the distribution of discontinuity lines.

关键词： Flux pinning Magneto-optical effect Monolayer films Superconductors Finite-element method Landau-Ginzburg theory

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Blockchain Technology Based Decentralized Energy Trading for Multiple-Microgrid Systems

Blockchain Technology Based Decentralized Energy Trading for...

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

作者： Ting Li Wei Zhang Ning Chen Minhui Qian Ying Xu School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China EPRI Nanjing China Department of Electrical Engineering & Computer Science University of Central Florida Orlando USA

ISBN: (数字)9781728131375

ISBN: (纸本)9781728131382

With the emerging technology for distributed generation and urge of improving quality of service of power supply for energy users, more and more Microgrids (MGs) are integrated into the distributed networks to serve the energy users. These Microgrids are gradually formulating a Multi-Microgrid System (MMGS, Multi-Microgrid System), which will play an important role for the future energy supply. Building a centralized control center not only increases the expense of investment, but also brings the issues of maintaining fairness among energy users. To address these problems, this paper proposes a peer-to-peer method for energy trading of MMGS, based on the idea of decentralized trading. An auction-based trading mechanism suitable for peer-to-peer energy trading is proposed first. For this mechanism, the MGs firstly declare their energy buying bids or selling quotations. Then, the market-clearing price is determined by using a unified weight clearing algorithm in a decentralized manner. By applying the edge technology of Blockchain, the implementation of the proposed peer-to-peer energy trading method, including the architecture, procedures, security check, etc., is also discussed. The proposed Blockchain-based energy trading platform can realize the decentralized and autonomous energy trading of MGs within an MMGS. A case study with an MMGS with 10 MG units is provided to demonstrate the effectiveness of the proposed approach.

关键词： Peer-to-peer computing Microgrids Blockchain Distributed power generation Electronic commerce Power distribution economics Pricing

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Hierarchic neighbors embedding

arXiv

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arXiv 2019年

作者： Liu, Shenglan Yu, Yang Liu, Yang Qiao, Hong Feng, Lin Feng, Jiashi School of Computer Science and Technology Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian Liaoning116024 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

Manifold learning now plays a very important role in machine learning and many relevant applications. Although its superior performance in dealing with nonlinear data distribution, data sparsity is always a thorny knot. There are few researches to well handle it in manifold learning. In this paper, we propose Hierarchic Neighbors Embedding (HNE), which enhance local connection by the hierarchic combination of neighbors. After further analyzing topological connection and reconstruction performance, three different versions of HNE are given. The experimental results show that our methods work well on both synthetic data and high-dimensional real-world tasks. HNE develops the outstanding advantages in dealing with general data. Furthermore, comparing with other popular manifold learning methods, the performance on sparse samples and weak-connected manifolds is better for HNE. Copyright © 2019, The Authors. All rights reserved.

关键词： Topology

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