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arXiv 2021年

作者： Du, Xin Uddin, Mohammad Monir Fony, A. Mostakim Hossain, Md. Tanzim Shuzan, Md. Nazmul Islam School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Department of Mathematics and Physics North south University Dhaka1229 Bangladesh Department of Mathematics Chittagong University Chittagong Bangladesh Department of Electrical and Computer Engineering North South University Dhaka1229 Bangladesh

This paper discusses model order reduction of large sparse second-order index-3 differential algebraic equations (DAEs) by applying Iterative Rational Krylov Algorithm (IRKA). In general, such DAEs arise in constraint mechanics, multibody dynamics, mechatronics and many other branches of sciences and technologies. By deflecting the algebraic equations the second-order index-3 system can be altered into an equivalent standard second-order system. This can be done by projecting the system onto the null space of the constraint matrix. However, creating the projector is computationally expensive and it yields huge bottleneck during the implementation. This paper shows how to find a reduce order model without projecting the system onto the null space of the constraint matrix explicitly. To show the efficiency of the theoretical works we apply them to several data of second-order index-3 models and experimental resultants are discussed in the paper. © 2021, CC BY.

关键词： Differential equations

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Method of Electronic Component Location, Grasping and Inserting Based on Machine Vision

Method of Electronic Component Location, Grasping and Insert...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Bin Xue Chang Sun Huihui Chu Qingsen Meng Shuanben Jiao Engineering and Technology R&D center of Mechanical and Electrical in Colleges of Shandong Qingdao Binhai University Shandong PR China Qingdao Zhongzhuang Vision Automation System Control Co. Ltd Shandong PR China

ISBN: (数字)9781728131290

ISBN: (纸本)9781728131306

Aiming at the problems of low efficiency, high cost, missing or wrong insertion of labor in PCB production, a method of electronic component location, grabbing and inserting based on machine vision is proposed. By building the machine vision system, three industrial cameras cooperate with dome light sources to take images of the whole components, the pin features of components and the jack features of PCB board respectively. After image acquisition, image processing is carried out on VisionPro 9.0 software platform, which mainly completes feature extraction of component pins and PCB board jacks, and coordinates positioning. Then, coordinate transformation is carried out by nine-point calibration method to guide the manipulator to complete the work of location, grabbing and inserting. Through the running test, the system has a fast grabbing speed and inserting speed. The error inserting rate, missing inserting rate, bad product rate and inserting precision all reach the standard, and the working efficiency is three times that of the manual.

关键词： Pins Feature extraction Machine vision Lifting equipment Manipulators Cameras Image color analysis

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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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Dual Grid Voltage Modulated Direct Power control of Grid-Connected Voltage Source Converter under Unbalanced Network Condition

Dual Grid Voltage Modulated Direct Power Control of Grid-Con...

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2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

作者： Gao, Shuning Zhao, Haoran Gui, Yonghao School of Electrical Engineering Shandong University Ji'nan250061 China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Ji'nan250061 China Automation and Control Section Department of Electronic Systems Aalborg University Aalborg Denmark

ISBN: (纸本)9781728135205

The Grid voltage Modulated Direct Power control (GVM-DPC) for Voltage Source Converter (VSC) is a recently proposed superior control strategies which features several advantages such as fast power reference tracking, simple structure, no need to use synchronizing techniques, strong robustness and so on. In this paper, an improved Dual Grid Voltage Modulated Direct Power control (D-GVM-DPC) strategies for unbalanced grid voltage condition is proposed and compared with regular voltage oriented dual PI control techniques. The idea of this improvement is to separately control the positive and negative sequence power components based on the original GVM-DPC controller. The simulation results shows that the proposed strategy is superior to the dual current control schemes been used with voltage oriented control strategy. © 2019 IEEE.

关键词： Electric power transmission networks

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Low-latency federated learning over wireless channels with differential privacy

arXiv

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arXiv 2021年

作者： Wei, Kang Li, Jun Ma, Chuan Ding, Ming Chen, Cailian Jin, Shi Han, Zhu Poor, H. Vincent School of Electrical and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China Data61 CSIRO SydneyNSW2015 Australia The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul Korea Republic of The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

In federated learning (FL), model training is distributed over clients and local models are aggregated by a central server. The performance of uploaded models in such situations can vary widely due to imbalanced data distributions, potential demands on privacy protections, and quality of transmissions. In this paper, we aim to minimize FL training delay over wireless channels, constrained by overall training performance as well as each client's differential privacy (DP) requirement. We solve this problem in the framework of multi-agent multiarmed bandit (MAMAB) to deal with the situation where there are multiple clients confornting different unknown transmission environments, e.g., channel fading and interferences. Specifically, we first transform the long-term constraints on both training performance and each client's DP into a virtual queue based on the Lyapunov drift technique. Then, we convert the MAMAB to a max-min bipartite matching problem at each communication round, by estimating rewards with the upper confidence bound (UCB) approach. More importantly, we propose two efficient solutions to this matching problem, i.e., modified Hungarian algorithm and greedy matching with a better alternative (GMBA), in which the first one can achieve the optimal solution with a high complexity while the second one approaches a better tradeoff by enabling a verified low-complexity with little performance loss. In addition, we develop an upper bound on the expected regret of this MAMAB based FL framework, which shows a linear growth over the logarithm of communication rounds, justifying its theoretical feasibility. Extensive experimental results are conducted to validate the effectiveness of our proposed algorithms, and the impacts of various parameters on the FL performance over wireless edge networks are also discussed. Copyright © 2021, The Authors. All rights reserved.

关键词： Multi agent systems

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Energy trading in microgrids for synergies among electricity, hydrogen and heat networksi

arXiv

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arXiv 2020年

作者： Zhu, Dafeng Yang, Bo Liu, Qi Ma, Kai Zhu, Shanying Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China School of Electrical Engineering Yanshan University Qinhuangdao066004 China

In this paper, an energy trading mechanism among microgrids is introduced to incentive them to share extra electricity, in order to balance renewable energy generation and energy demand at a low cost. However, energy trading might not completely absorb the excess renewable energy, a multi-energy management framework including fuel cell vehicles, energy storage, combined heat and power (CHP) and renewable energy is proposed, and the characteristics and scheduling arrangements of fuel cell vehicles are considered to further realize the local absorption of renewable energy and enhance the economic benefits of microgrids. This work designs a joint energy scheduling and trading algorithm based on Lyapunov optimization and double auction to solve the optimization problem of microgrids, which guarantees the truthfulness of information, customers satisfaction and optimal benefits. The simulations based on real data evaluate the performance of the multi-energy management framework and demonstrate the effectiveness of the proposed algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： Scheduling

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Missile Attitude control Based on Deep Reinforcement Learning

Missile Attitude Control Based on Deep Reinforcement Learnin...

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International Conference on control and automation (ICCA)

作者： Bohao Li Fei Ma Yunjie Wu State Key Laboratory of Virtual Reality Technology and System Beihang University Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China Science and Technology on Aircraft Control Laboratory Beihang University Beijing China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

Deep reinforcement learning (DRL) has been one of the research hotspots in the areas of control. In this paper, we focus on the study of missile attitude control system using DRL. An novel PID controller based on deep deterministic policy gradient(DDPG) algorithm is presented, which could applied to the self-tuning of parameters. The framework of the adaptive DDPG-PID controller is given. The controller takes flight information as input and takes rudder angle as output. A reward function related to the system error is designed, which can be used to train the DDPG algorithm effectively. Simulation results show that the adaptive DDPG-PID controller has a faster convergence velocity, reduces the overshoot and oscillation, achieves higher accuracy tracking control to target.

关键词： Software algorithms Missiles Heuristic algorithms Earth Adaptation models Task analysis Solid modeling

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A framework of hierarchical attacks to network controllability

arXiv

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arXiv 2020年

作者： Lou, Yang Wang, Lin Chen, Guanrong The Department of Electrical Engineering City University of Hong Kong Hong Kong The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

Network controllability robustness reflects how well a networked dynamical system can maintain its controllability against destructive attacks. This paper investigates the network controllability robustness from the perspective of a malicious attack. A framework of hierarchical attack is proposed, by means of edge- or node-removal attacks. Edges (or nodes) in a target network are classified hierarchically into categories, with different priorities to attack. The category of critical edges (or nodes) has the highest priority to be selected for attack. Extensive experiments on nine synthetic networks and nine real-world networks show the effectiveness of the proposed hierarchical attack strategies for destructing the network controllability. From the protection point of view, this study suggests that the critical edges and nodes should be hidden from the attackers. This finding helps better understand the network controllability and better design robust networks. © 2020, CC BY.

关键词： Complex networks

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Simulation and analysis of high-reliability braking system of aircraft based on self-feed energy nonsimilar margin

Simulation and analysis of high-reliability braking system o...

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CSAA/IET International Conference on Aircraft Utility systems 2020, AUS 2020

作者： Wang, Xiyu Shang, Yaoxing Hu, Haiying Qiu, Binghui Teng, Fengjian Zhang, Hao Jiao, Zongxia Liu, Xiaochao School of Automation Science and Electrical Engineering Beihang University Beijing100191 China AVIC Jiangxi Hongdu Aviation Industry Group Company Ltd Nanchang330000 China Beijing Aeronautical Technology Research Center Beijing100076 China Aerospace System Engineering Shanghai Shanghai201109 China Research Institute for Frontier Science Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China

ISBN: (纸本)9781839535635

As one of the key and important airborne systems, aircraft braking systems mostly use traditional centralized hydraulic sources. With the new concept of "multi-electric aircraft", the aircraft energy supply system has further branched. This article introduces an integrated hydraulic brake device. It does not require an on-board hydraulic source, and can directly convert the energy of the wheel rotation when the aircraft lands, to complete the braking function. Using Simulink/SimHydraulics module, a corresponding model of aircraft brake integrated hydraulic device was established. The function of this self-feeding hydraulic brake device was verified through simulation and analysis. This method provides a new way to further study the braking system. © 2020 Institution of engineering and Technology. All rights reserved.

关键词： Electric aircraft

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A Scale Adaptive Kernel Correlation Filter-Based Tracker with Optimized Update Strategy

A Scale Adaptive Kernel Correlation Filter-Based Tracker wit...

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第三十九届中国控制会议

作者： Minghui Shi Yong Heng Liang Han Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing Institute of Electronic System Engineering School of Sino-French Engineer Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Correlation filter-based trackers have achieved competitive results in the field of visual tracking, but the abilities to deal with the multi-scale and keep the tracking stability still need to be improved. In this article, the complex background tracking problems are studied based on the kernel correlation filter. In order to address the fixed size limitation, we present an improved scheme, which can not only realize scale adaption, but also retain the advantages of the original algorithm. In addition, the adaptive update learning rate of the model is achieved by using the peak sidelobe ratio as an indicator to measure the filter performance. Using the index, we can selectively reduce the model interference to low precision information. Moreover, we design a redetection mechanism that runs automatically when the tracking evaluation indicator is low. Compared with the radical model update methods, those conservative update strategies can effectively decrease the model pollution and ensure the tracking effect. Extensive verifications based on OTB-100 benchmark show that the optimized algorithm improves the accuracy, robustness, and generalization ability of target tracking.

关键词： Target tracking Kernel correlation filter Scale adaption Peak sidelobe ratio Learning rate adaption

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