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IEEE Conference on Decision and control

作者： Junyao Hou Xiang Yin Shaoyuan Li Majid Zamani Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Computer Science Department University of Colorado Boulder CO USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

Opacity is an important information-flow security property that captures the plausible deniability for some "secret" of a system. In this paper, we investigate the problem of synthesizing controllers that enforce opacity for labeled transition systems (LTS). Most of the existing works on synthesis of opacity-enforcing controllers are based on the original system model, which may contain a large number of states. To mitigate the complexity of the controller synthesis procedure, we propose an abstraction-based approach for controller synthesis. Specifically, we propose notion of opacity-preserving alternating (bi)simulation relation for the purpose of abstraction. We show that, if the abstract system is opacity-preserving alternatingly simulated by the original system which may be significantly smaller, then we can synthesize an opacity-enforcing controller based on the abstract system and then refine it back to a controller enforcing opacity of the original system. We investigate both initial-state opacity and infinite-step opacity. We also show the effectiveness of the proposed approach by a set of examples.

关键词： Computational modeling control system synthesis control system security Closed loop systems

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Robust Semi-Global Leaderless Consensus and Containment control of Identical Linear systems with Imperfect Actuators

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Journal of systems Science & Complexity 2018年第1期31卷 69-86页

作者： SHI Liangren ZHAO Zhiyun LIN Zongli Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240 China Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 USA

This paper investigates both the robust semi-global leaderless consensus problem and the robust semi-global containment control problem for a group of identical linear systems with imperfect actuators. The imperfect actuators are characterized by nonlinearities such as saturation and dead zone and there input output relationships are not precisely known. The dynamics of follower agents are also affected by the input additive disturbances. Low-and-high gain feedback consensus protocols are constructed to solve these problems. More specifically, it is shown that robust semi-global leaderless consensus can be achieved over a connected undirected graph and robust semi-global containment control can be achieved when each follower agent has access to the information of at least one leader agent. Numerical simulation illustrates the theoretical results.

关键词： Consensus containment control dead zone leaderless consensus multi-agent systems saturation

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A novel method to increase energy density of permanent magnet machine based on multi-physical field analysis

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UPB Scientific Bulletin, Series D: Mechanical Engineering 2020年第4期82卷 79-92页

作者： Zheng, Qingchun Zhao, Yangyang Zhu, Peihao Wang, Sen Liu, Jingna Ma, Wenpeng Li, Xiang Xiao, Yinhong Wang, Naixin Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China School of Computer Science Tianjin University of Technology Tianjin300384 China School of Automation Shenyang Institute of Engineering Shenyang110136 China Baoding Power Supply Company Hebei Electric Power Company State Grid Corporation of China Baoding071000 China

As an important component of all-electric aircraft, the main propulsion machine is developing towards high energy density, high efficiency and high fault tolerance. In order to improve the energy density of main propulsion machine for all-electric aircraft, a novel approach, which can be used for excellent performance improvement of electric machine of all-electric aircraft, is reported in this paper. The analytical formula of energy density is put forward and the design method of high energy density permanent magnet machine is presented. A high energy density machine with rated power of 30kW is designed, and the electromagnetic field simulation analysis, strength and stress structure verification, temperature field simulation analysis and multi-physical field coupling analysis are obtained. A prototype is developed, the experiment platform is established, and experiments are performed. The energy density of main propulsion machine designed is up to 21kW·N·m/kg2, and the index is increased by 3.2 times. The optimal method based on the multi-physical field analysis can be also applied to other high energy density machines. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Electromagnetic fields

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Fabry-perot lasers as enablers for parallel reservoir computing

arXiv

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arXiv 2020年

作者： Bogris, Adonis Mesaritakis, Charis Deligiannidis, Stavros Li, Pu Department of Informatics and Computer Engineering University of West Attica Aghiou Spiridonos Egaleo Athens12243 Greece Department of Information & Communication Systems Engineering University of the Aegean 2 Palama & Gorgyras St. Karlovassi Samos83200 Greece Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan030024 China

We introduce the use of Fabry-Perot (FP) lasers as potential neuromorphic computing machines with parallel processing capabilities. With the use of optical injection between a master FP laser and a slave FP laser under feedback we demonstrate the potential for scaling up the processing power at longitudinal mode granularity and perform real-time processing for signal equalization in 25 Gbaud intensity modulation direct detection optical communication systems. We demonstrate the improvement of classification performance as the number of nodes increases and the capability of simultaneous processing of arbitrary data streams. Extensive numerical simulations show that up to 8 longitudinal modes in typical Fabry-Perot lasers can be leveraged so as to enhance classification performance. Copyright © 2020, The Authors. All rights reserved.

关键词： Recurrent neural networks

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H∞ State Estimation for Stochastic Jumping Neural Networks with Fading Channels Over a Finite-Time Interval

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Neural Processing Letters 2019年第1期50卷 1-18页

作者： Shen, Liang Shen, Hao Gao, Mingming Liu, Yajuan Huang, Xia School of Electrical and Information Engineering Anhui University of Technology Ma’anshan243002 China School of Metallurgical Engineering Anhui University of Technology Ma’anshan243002 China The State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

In the work, a class of Markov jump neural networks in the discrete-time domain with fading channels are taken into account. The main aim is to investigate the H∞ state estimation issue when the Rice fading occurs in measured networks. In the first place, the analyses of the finite-time boundedness and the H∞ performance for the estimation error system with the aid of finite-time stability theory are presented. Some conditions which guarantee the solvability of the addressed problem are established. Furthermore, by applying an unique decoupling method, the gains of the presented estimator are obtained under the feasible solutions of the conditions derived before. Finally, the validity of the presented approach is verified by a numerical example. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

关键词： State estimation

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Coordinated Dispatching and Frequency control Strategy of Power systems with Large Scale Wind Power Penetration

Coordinated Dispatching and Frequency Control Strategy of Po...

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Chinese Automation Congress (CAC)

作者： Jianhua Zhang Rui Shan Fei Xu Bo Hu Guiping Zhou Guolian Hou Congzhi Huang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China Tsinghua University Beijing China State Grid Liaoning Electric Power Supply Co. Ltd. Shenyang China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In this paper, a coordinated dispatching and frequency control strategy is presented for wind turbines (WTs) participating in frequency regulation from three levels. Firstly, the coordinated dispatching and frequency control strategy among multi-source power generation systems is given with the aid of the wind power installed capacity penetration rate; Secondly, the coordinated distribution strategy among the wind farms is presented by combing the incremental active power reference with parameters tuning method; Thirdly, the coordinated control is investigated by integrating droop control, inertia control and de-load control for each WT. Simulation results demonstrate that the proposed coordinated dispatching and frequency control strategy can obtain better frequency regulation performance for power systems with large scale wind power penetration.

关键词： Frequency control Wind turbines Wind power generation Dispatching Wind speed Wind farms Rotors

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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Cerebrovascular Segmentation in MRA via Reverse Edge Attention Network 23rd

Cerebrovascular Segmentation in MRA via Reverse Edge Attenti...

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23rd International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2020

作者： Zhang, Hao Xia, Likun Song, Ran Yang, Jianlong Hao, Huaying Liu, Jiang Zhao, Yitian College of Information Engineering Capital Normal University Beijing China Cixi Institute of Biomedical Engineering Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo China School of Control Science and Engineering Shandong University Jinan China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China International Science and Technology Cooperation Base of Electronic System Reliability and Mathematical Interdisciplinary Capital Normal University Beijing China Laboratory of Neural Computing and Intelligent Perception Capital Normal University Beijing China Beijing Advanced Innovation Center for Imaging Theory and Technology Capital Normal University Beijing China

ISBN: (纸本)9783030597245

Automated extraction of cerebrovascular is of great importance in understanding the mechanism, diagnosis, and treatment of many cerebrovascular pathologies. However, segmentation of cerebrovascular networks from magnetic resonance angiography (MRA) imagery continues to be challenging because of relatively poor contrast and inhomogeneous backgrounds, and the anatomical variations, complex geometry and topology of the networks themselves. In this paper, we present a novel cerebrovascular segmentation framework that consists of image enhancement and segmentation phases. We aim to remove redundant features, while retaining edge information in shallow features when combining these with deep features. We first employ a Retinex model, which is able to model noise explicitly to aid removal of imaging noise, as well as reducing redundancy within an image and emphasizing the vessel regions, thereby simplifying the subsequent segmentation problem. Subsequently, a reverse edge attention module is employed to discover edge information by paying particular attention to the regions that are not salient in high-level semantic features. The experimental results show that the proposed framework enables the reverse edge attention network to deliver a reliable cerebrovascular segmentation. © 2020, Springer Nature Switzerland AG.

关键词： Image enhancement

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Transactive energy system deployment over insecure communication links

arXiv

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arXiv 2020年

作者： Lu, Yang Lian, Jianming Zhu, Minghui Ma, Ke The System Security Group Lancaster University LancasterLA1 4YW United Kingdom The Grid-Interactive Controls Group Oak Ridge National Laboratory Oak RidgeTN37831 United States The School of Electrical Engineering and Computer Science Pennsylvania State University University ParkPA16802 United States The Optimization and Control Group Pacific Northwest National Laboratory RichlandWA99354 United States

In this paper, the privacy and security issues associated with the transactive energy system (TES) deployment over insecure communication links are addressed. In particular, it is ensured that (1) individual agents' bidding information is kept private throughout hierarchical market-based interactions;and (2) any extraneous data injection attack can be quickly and easily detected. An implementation framework is proposed to enable the cryptography-based enhancement of privacy and security for the deployment of any general hierarchical systems including TESs. Under the proposed framework, a unified cryptography-based approach is developed to achieve both privacy and security simultaneously. Specifically, privacy preservation is realized by an enhanced Paillier encryption scheme, where a block design is proposed to significantly improve computational efficiency. Attack detection is further achieved by an enhanced Paillier digital signature scheme, where a stamp-concatenation mechanism is proposed to enable detection of data replace and reorder attacks. Simulation results verify the effectiveness of the proposed cyber-resilient design for transactive energy systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Cryptography

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Multi-objective optimal control of micro-grid based on economic model predictive control

Multi-objective optimal control of micro-grid based on econo...

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第三十八届中国控制会议

作者： Shijia Ren Jiajun Wang Miaomiao Ma School of Control & Computer Engineering North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University

This paper presents an economic model predictive control(EMPC) scheme to manage the grid-connected micro-grid in an economic way. The grid-connected micro-grid system is composed of wind generation unit, photovoltaic generation unit,energy storage battery, micro-turbines and load. The generation units are scheduled optimally to achieve the three objectives of power balance, economic performance and environmental protection. Moreover, the analytic hierarchy process(AHP) is used to determine the weight coefficients of the objective function. Simulation and analysis results for the economic optimization of micro-grid system are given to illustrate the effectiveness of the proposed economic model predictive control framework.

关键词： Micro-grid multi-objective optimization EMPC AHP power balance

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