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arXiv 2018年

作者： Zheng, Bolun Sun, Rui Tian, Xiang Chen, Yaowu Zhejiang University Institute of Advanced Digital Technology and Instrument No. 38 Zheda Road Hangzhou310027 China Sichuan University College of Physical Science and Technology No.24 South Section 1 Yihuan Road Chengdu China Zhejiang Provincial Key Laboratory for Network Multimedia Technologies Zhejiang University China State Key Laboratory of Industrial Control Technology Zhejiang University China Zhejiang University Embedded System Engineering Research Center Ministry of Education of China

Recent studies have used deep residual convolutional neural networks (CNNs) for JPEG compression artifact reduction. This study proposes a scalable CNN called S-Net. Our approach effectively adjusts the network scale dynamically in a multitask system for real-time operation with little performance loss. It offers a simple and direct technique to evaluate the performance gains obtained with increasing network depth, and it is helpful for removing redundant network layers to maximize the network efficiency. We implement our architecture using the Keras framework with the TensorFlow backend on an NVIDIA K80 GPU server. We train our models on the DIV2K dataset and evaluate their performance on public benchmark datasets. To validate the generality and universality of the proposed method, we created and utilized a new dataset, called WIN143, for over-processed images evaluation. Experimental results indicate that our proposed approach outperforms other CNN-based methods and achieves state-of-the-art performance. Copyright © 2018, The Authors. All rights reserved.

关键词： Network layers

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A distributed learning method for due date assignment in flexible job shops 9th

A distributed learning method for due date assignment in fle...

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9th International Conference on Discrete Optimization and Operations Research, DOOR 2016

作者： Weng, Wei Rong, Gang Fujimura, Shigeru Graduate School of Information Production and Systems Waseda University Fukuoka8080135 Japan State Key Laboratory of Industrial Control Technology Institute of Cyber-systems and Control Zhejiang University Hangzhou China

This study intends to help manufacturers that use flexible job shops improve performance of due date assignment, that is, setting delivery times to jobs that arrive dynamically. High performing due date assignment enables achieving on-time delivery and quick response of delivery time to customer orders. Traditional methods for due date assignment are predefined equations that estimate the duration of making a product in the production system. Such equations are sufficient for relatively simple systems such as single machine shops, but are not very high in accuracy for complex systems such as flexible job shops. To improve due date assignment for such systems, we propose a more flexible method that uses distributed learning to learn the remaining time of a job inside the system. We let each workstation in the production shop be a distributed unit that updates its local queuing time and interacts with other units to provide the total remaining time of a job. We carry out extensive computational experiments to evaluate performance of the proposed method, and the results show that it outperforms two advanced equational methods in terms of both accuracy of estimation and stability in performance. Copyright © by the paper's authors.

关键词： Learning systems

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Kalman and Smooth Variable Structure Filters for Pose Estimation in Robotic Visual Servoing

Kalman and Smooth Variable Structure Filters for Pose Estima...

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2017 3rd International Conference on Artificial Intelligence and industrial Engineering (AIIE2017)

作者： Xi-yuan LU Liang DU Xiao-lin REN Bo DONG Yuan-chun LI Department of Control Science and Engineering Changchun University of Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

Pose estimation problem of an object in real time is an important issue for robotic visual servoing(RVS). Many pose estimation schemes in RVS rely on an extended Kalman filter(EKF) that provides good accurate estimation. However, it may cause the estimation to become unstable because of nonlinear modeling uncertainties. While, smooth variable structure filter(SVSF) is a new method that is more robust to disturbances and uncertainties. In this paper, a novel pose estimate method is developed based on the EKF and SVSF. It is combined the accuracy of the EKF and the robustness provided by the SVSF that will lead to more accurate state estimates and improve robustness to modeling errors and uncertainties. The resulting algorithms are called the EKF-SVSF. The simulation results are provided to demonstrate the robustness and accuracy.

关键词： Pose estimation Robotic visual servoing(RVS) Kalman filter(KF) Smooth variable structure filter

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Unit commitment considering demand response behavior based on utility maximization

Unit commitment considering demand response behavior based o...

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

作者： Zhang, Yumin Han, Xueshan Xu, Bo Zhang, Li Sun, Donglei Miao, Xiaofeng Jiang, Jiayin Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Haidian District Beijing100084 China Economic and Technology Research Institute of State Grid Shandong Electric Power Company Jinan China State Grid Shandong Electric Power Company Yantai Electric Power Company Yantai264001 China

ISBN: (纸本)9781538614273

The active participation of demand side resources in power grid operation not only benefits the individual participant but also benefits the whole system. The optimal goal can promote by excavating the active behaviors of demand side. The welfare maximization of market participant is the driving force of such active behaviors. Considering the independence of each user's behavior, the consumer's utility function is selected to depict consumer's preference and demand response behavior. In order to coordinate the consumers' maximum welfare with social welfare maximization, consumers' utility function and units' operation cost are integrated into Unit Commitment (UC) model. The objective function is to maximize social welfare, by subtracting units' operation cost from consumers' total utility, and this objective can be acquired. Considering the proposed model should be solved in a distributed manner, the idea of the centralized coordination and the decentralized decision-making is proposed. Based on the Lagrangian relaxation (LR) principle and distributed real-time pricing scheme, a closed-loop feedback mechanism is constructed to reflect the relationship among generator output, price level, and load demand. The ten generating units example can illustrate the effectiveness of the proposed method. © 2017 IEEE.

关键词： Power markets

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A new framework of science and technology innovation education for k-12 in Qingdao, China

A new framework of science and technology innovation educati...

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2017 ASEE International Forum

作者： Liu, Xiwei Gong, Xiaoyan Wang, Fei-Yue Sun, Rui Gao, Yanqing Zhang, Yu Zhou, Jiehan Deng, Xiaofei State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China Intelligent Education Institution Qingdao Academy of Intelligent Industries China Qingdao Experimental High School China Oregon Institute of Technology United States University of Oulu Finland

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Social Energy:Mining Energy From the Society

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 466-482页

作者： Jun Jason Zhang David Wenzhong Gao Yingchen Zhang Xiao Wang Xiangyang Zhao Dongliang Duan Xiaoxiao Dai Jun Hao Fei-Yue Wang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of Denver IEEE National Renewable Energy Laboratory Qingdao Academy of Intelligent Industries(QAII) QingdaoShandongChinaand SKL-MCCSCASIA School of Automation Science and Electrical Engineering Beihang University Department of Electrical and Computer Engineering College of Engineering and Applied ScienceUniversity of Wyoming State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social *** this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system *** recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and *** this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy *** the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

关键词： ACP distribution locational marginal pricing intelligent operation in power systems parallel control parallel intelligence parallel management social energy socio-technical energy systems

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An SNR-Adaptive Relaying Algorithm for Multi-Antenna Cooperative Networks

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China Communications 2017年第10期14卷 228-236页

作者： Shuangshuang Han Peng Zhang Feijin Shi Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing China Qingdao Academy of Intelligent Industries Qingdao Shandong Province China The School of Computer Engineering Weifang University Shandong P. R. China Communications Headquarters Ministry of Foreign Affairs of the People's Republic of China Beijing China Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology Changsha China

Multiple-input multiple-output(MIMO) and cooperative communications have been attracted great attention for the improvements of communication capacity, power consumption, and transmission coverage. The conventional fixed relaying protocols, amplify-and-forward(AF) and decode-and-forward(DF), have their own advantages and disadvantages, i.e. AF performs better than DF for low signal-to-noise ratio(SNR) region, while the reverse is true for high SNR region. Therefore, this paper proposes an SNR-adaptive forward(SAF) relaying scheme obtaining the advantages of both AF and DF. Furthermore, the proposed SAF does not need to switch between AF and DF when SNR changes. The main idea is to adaptively derive the soft information at the cooperative relay nodes based on the information of the received signal and the SNR. Besides, based on the theoretical analysis and the simulation results, it is affirmed that the proposed SAF achieves superior performance than both AF and DF for all SNRs. Moreover, the performance gain would be improved with the increasing number of parallel cooperative relay nodes.

关键词： MIMO SNR SNR-adaptive forward multi-antenna

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Switching control System Based on Robust Model Reference Adaptive control

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Journal of systems Science & Complexity 2016年第4期29卷 897-932页

作者： HU Qiong FEI Qing MA Hongbin WU Qinghe GENG Qingbo School of Automation Beijing Institute of Technology Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology

For conventional adaptive control, time-varying parametric uncertainty and unmodeled dynamics are ticklish problems, which will lead to undesirable performance or even instability and nonrobust behavior, respectively. In this study, a class of discrete-time switched systems with unmodeled dynamics is taken into consideration. Moreover, nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper, and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance. For robustness against unmodeled dynamics and uncertainty, robust model reference adaptive control(RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems. Meanwhile, two different switching laws are presented for switched systems and nonlinear systems, respectively. Thereby, the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems. Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes. Furthermore, as to the proposed scheme for nonlinear systems, its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.

关键词： Longitudinal control of F-16 aircraft switching control switching law. nonlinear systems RMRAC switched systems

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Optimal jamming power allocation against remote state estimation

Optimal jamming power allocation against remote state estima...

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American control Conference

作者： Heng Zhang Yifei Qi Junfeng Wu Huaihai Institute of Technology Lianyun-gang China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China ACCESS Linnaeus Center Automatic Control The Royal Institute of Technology (KTH) Sweden

ISBN: (纸本)9781509045839

This paper investigates a remote state estimation problem, where a smart sensor observes the state of a physical plant, locally estimates the state with Kalman filter, and then sends its local estimation data to a remote estimator through a communication network. There is a jamming attacker in the communication network who intentionally blocks the network with the purpose of deteriorating estimation quality subject to the jamming energy constraint. From the viewpoint of jamming attacker, in order to maximize attack effect, we focus on the questions "when to jam the communication network", and "how much power the attacker should adopt to jam the network". After theoretic analysis, we point out that any grouped together attack schedule is optimal for the given jamming power. We provide a close form of jamming power when a sufficient condition holds, and the corresponding jamming effect on remote state estimation is explicitly presented. For a general case, we design a jamming power allocation algorithm and show the computational complexity of the proposed algorithm is not worse than O(T), where T is the length of the time horizon considered.

关键词： paper investigates remote jamming state estimation Remote networks(communications) power splitting intelligent sensors control time horizon

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Algebraic Connectivity Estimation Based on Decentralized Inverse Power Iteration

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Asian Journal of control 2017年第2期19卷 805-812页

作者： Wei, Yue Fang, Hao Chen, Jie Xin, Bin School of Automation Beijing Institute of Technology Beijing 100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

In this work, we propose a new scheme to estimate the algebraic connectivity of the graph describing the network topology of a multi-agent system. We consider network topologies modeled by undirected graphs. The main idea is to propose a new decentralized conjugate gradient algorithm and a decentralized compound inverse power iteration scheme. The matrix inversion computation in this scheme is replaced by solving the non-homogeneous linear equations relying on the proposed decentralized conjugate gradient algorithm. With this scheme, we can achieve a fast convergence rate in estimating the algebraic connectivity by setting the parameter μ properly. Simulation results demonstrate the effectiveness of the proposed scheme. © 2016 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd

关键词： Network topology

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