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A Novel Forwarding Method for Full-Duplex Two-Way Relay Networks

China Communications 2017年第4期14卷 65-72页

作者： Shuangshuang Han Xiang Cheng Liuqing Yang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing China and Qingdao Academy of Intelligent Industries The State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Department of Electrical and Computer Engineering Colorado State University

An estimate-and-forward(EF) scheme for single-input single-output(SISO) and multiple-input multiple-output(MIMO) full-duplex two-way relay networks is proposed and analyzed. The relay estimates the received signal from two terminal nodes by a minimum mean squared error(MMSE) estimation and forwards a scaled version of the MMSE estimate to the destination. The proposed EF outperforms conventional amplify-and-forward(AF) and decode-and-forward(DF) across all signal-to-noise ratio(SNR) region. Because its computational complexity is high for relays with a large number of antennas(large MIMO) and/or high order constellations, an approximate EF scheme, called list EF, are thus proposed to reduce the computational complexity. The proposed list EF computes a candidate list for the MMSE estimate by using a sphere decoder, and it approaches the performance of the exact EF relay at a negligible performance loss. The proposed forwarding approach also could be used to other relay networks, such as half-duplex, one-way or massive MIMO relay networks.

关键词： estimate-and-forward full-duplex two-way relay wireless communications

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A Novel Deep Learning Approach: Stacked Evolutionary Auto-encoder

A Novel Deep Learning Approach: Stacked Evolutionary Auto-en...

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International Joint Conference on Neural Networks

作者： Yaoming Cai Zhihua Cai Meng Zeng Xiaobo Liu Jia Wu Guangjun Wang School of Computer Science China University of Geosciences Wuhan China Qinzhou University Guangxi China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Computing Macquarie University Sydney NSW Australia

Deep neural networks have been successfully applied to many data mining problems in recent works. The training of deep neural networks relies heavily upon gradient descent methods, however, which may lead to the failure of training due to the vanishing gradient (or exploding gradient) and local optima problems. In this paper, we present SEvoAE method based on using Evolutionary Multiobjective Optimization (EMO) algorithm to train single layer auto-encoder, and sequentially learning deeper representation in a stacking way. SEvoAE is able to achieve accurate feature representation with good sparseness by globally simultaneously optimizing two conflicting objective functions and allows users to flexibly design objective functions and evolutionary optimizers. We compare results of the proposed method with existing architectures for seven classification problems, showing that the proposed method is able to outperform existing methods with a reduced risk of overfitting the training data.

关键词： Training Optimization Decoding Neural networks Linear programming Feature extraction Stacking

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Stochastic stabilization of linear systems under delayed and noisy feedback control 36

Stochastic stabilization of linear systems under delayed and...

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第36届中国控制会议

作者： ZONG Xiaofeng LI Tao ZHANG Ji-Feng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Shanghai Key Laboratory of Pure Mathematics and Mathematical Practice Department of MathematicsEast China Normal University Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

ISBN: (纸本)9781538629185

This paper is to study the stabilizability and stabilization issues of linear dynamical systems based on the delayed and noisy feedback control. For the general linear systems, the necessary conditions and sufficient conditions for mean square and almost sure stabilizability are deduced and the corresponding feedback controls are designed according to the generalized algebraic Riccati equation. It is revealed that the stabilizability is up to the system parameters（delays, noises, and unstable eigenvalues of the original system） and unstable systems can be stabilized in mean square if the feedback control is disturbed by noises with small intensities. It is showed that second-order integrator systems must be stabilizable for any given noise intensity and delay.

关键词： Stabilization Feedback control Noise Delay

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Relation Model of Burden Operation and State Variables of Blast Furnace Based on Low Frequency Feature Extraction*

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IFAC-PapersOnLine 2017年第1期50卷 13796-13801页

作者： Zhang, Kexin Wu, Min An, Jianqi Cao, Weihua Liu, Zhentao Ning, Fulong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Faculty of Engineering China University of Geosciences wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

In the blast furnace ironmaking process, the running state of the blast furnace can be directly adjusted by the burden operation. Therefore, the explicit relation between the burden operation and the running state variables is vital for the blast furnace operators. However, the state variables of the blast furnace are affected by many factors and the burden matrix is complicated. In this paper, a support vector regression(SVR) predicting model based on low frequency feature extraction is proposed to solve these problems. First, the low frequency components of state variables time series which are mostly affected by the burden operation are extracted. Then, the dimensions of the burden matrix are reduced by a devised simple expression method. Finally, the relation model based on SVR is proposed to predict the values of the expected state variables according to the simplified burden matrix and the value of initial state variables. The simulation on real factory data indicates that the model reflects the accurate quantitative relation between the burden operation and the state variables. © 2017

关键词： Blast furnaces Blast furnace practice Extraction Feature extraction Support vector regression Blast furnace iron making Blast furnace operators burden operation Initial state variables Low frequency components Relation models State variables Support vector regression (SVR)

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Adaptive robust controller for electric cylinder with fast parameter estimation based on modified lugre model 36

Adaptive robust controller for electric cylinder with fast p...

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36th Chinese control Conference, CCC 2017

作者： Li, Duo Yang Zheng, Jun Hao, Wang Ren Jian Wang, Shou Kun Shen, Wei Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789881563934

In this paper, the adaptive robust control (ARC) algorithm is proposed for tracking control of the electric cylinder position. According to the analysis of the working principle of the electric cylinder servo system, the model of the system is established on the modified Lugre friction model, and single observer is designed for calculating friction as well. Then the ARC controller and adaptive law are designed for on-line parameters estimation, frictional compensation and the suppression external disturbance. Through the Lyapunov approach, the stability of this system can be obtained in this work. The simulation result shows that ARC can suppresses external disturbances effectively and realize real-time online parameter estimation. © 2017 Technical Committee on control Theory, CAA.

关键词： Friction Mathematical model Load modeling Adaptation models Adaptive systems Permanent magnet motors Synchronous motors

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Research on Information Structure of Programmatic Advertising Markets

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IFAC-PapersOnLine 2017年第1期50卷 13587-13592页

作者： Li, Juanjuan Yuan, Yong Zhao, Xueliang Wang, Fei-Yue The State Key Laboratory of Management Control for Complex Systems Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology Beijing Qingdao China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China

With the abundance of online big data and computing resources, as well as the rapid develop-ment and diversification of business models, programmatic advertising (PA) has emerged and become the mainstream and one of the most promising advertising channels in recent years. As an effective way to precision marketing, PA relies heavily on the information elicited from analyzing Web users and pages, which can help advertisers precisely identify their best-matched audiences and evaluate the ad impressions in a real-time fashion In PA markets, publishers serve as the supplier of ad impressions, and have control on whether, what and how to reveal such key information to advertisers. These decisions play a central role in the information structure of data-driven PA markets, and attract intensive research interests. In this paper, we strive to investigate publishers’ rational preference over the symmetric and asymmetric information structures, with the aim of maximizing their revenues. Our model views publishers’ revenue as a function of the information structure among advertisers, and we hereby proved its convexity under an incentive compatible mechanism. This conclusion indicates that publishers prefer an asymmetric information structure rather than a symmetric one. Our research findings can help improve publishers’ revenue, and also can explain the underlying rationale for the hybrid PA markets mixed by public real-time bidding and private marketplaces. © 2017

关键词： Commerce Big data Marketing Advertising markets Asymmetric information Computing resource Incentive compatible mechanisms Information structures Precision marketings private marketplace Real time biddings

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Stability and Neimark-Sacker bifurcation analysis for single gene discrete system with delay

Stability and Neimark-Sacker bifurcation analysis for single...

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Chinese control Conference

作者： Feng Liu Qicheng Mei Fenglan Sun Xinmei Wang Hua O. Wang Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Automation China University of Geosciences Wuhan China Research Center of System Theory and Application Chongqing University of Posts and Telecommunications Chongqing China Department of Mechanical Engineering Boston University Boston MA USA

The network structure and functional properties of gene regulatory system and their relationships arc an important research field in systems biology. In this paper, a new improved model is proposed based on the study of gene expression process. The model takes into account the effect of protein concentration on the gene expression, so as to obtain a new bifurcation point and improve the performance of the system. The validity of the model is verified by theoretical analysis and data simulation.

关键词： Mathematical model Proteins Stability analysis Bifurcation Biological system modeling Delays RNA

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Event-based Cubature Kalman Filter for Smart Grid Subject to Communication Constraint

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IFAC-PapersOnLine 2017年第1期50卷 49-54页

作者： Li S. Li Z. Li J. Wang Q. Song Z. Chen Z. Sheng Y. Liu X. Liu Y. School of Automation and Key Laboratory for Intelligent Control Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China Department of control science and engineering Harbin Institute of Technology Harbin 150001 China

Accurate real-time estimation plays an important role in smart grids. Although various filtering algorithms, such as unscented Kalman filter (UKF), have been proposed for phasor measurement unit (PMU), they occupy huge communication bandwidth without specific concern, which puts heavy burden on the communication network especially when wireless communications are applied. In order to relief this burden, the event-based cubature Kalman filter (EBCKF) is proposed based on event-based schemes in this paper. The event-based strategy guarantees that only the observations containing innovational information are transmitted, and cubature Kalman filter (CKF), which is based on the spherical cubature integration, provides more accurate estimation than UKF. Besides, the design-oriented communication rate is provided corresponding to the event-based strategy design. The proposed filter can effectively reduce the communication rate while ensuring the accuracy of filtering. Finally, the standard IEEE 39-bus system is utilized to verify the feasibility and performance of the proposed method. © 2017

关键词： communication rate dynamic state estimation Event-based cubature Kalman filter (EBCKF) IEEE 39-bus phasor measurement unit (PMU)

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A NSGA-II based Peak Load Shifting Optimization Method for Customers with Distributed Generators Considering Time-of-use Price

A NSGA-II based Peak Load Shifting Optimization Method for C...

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Chinese control Conference

作者： Hao Zhou Min Ding Bo Hu Qingyi Wang Zhili Tan Danyun Li Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan P. R. China Global Energy Interconnection Development and Cooperation Organization Beijing P. R. China

With the extensive use of distributed generation, the traditional demand response analysis cannot meet the current requirements. This paper proposes a NSGA-II based peak load shifting optimization method for customers with distributed generators considering time-of-use price. Firstly, a fuzzy classification method divides the daily power into three time segments, peak hours, flat hours and valley hours. Secondly, on the basis of the time-of-use price, a peak load shifting optimization model is built with constraints and the objectives of minimizing the peak load, maximizing the valley load, and minimizing the peak-valley difference. Then, a NSGA-II based optimization method solves the optimal model and obtains the optimal electricity prices of different time segments to shift the peak load and the valley load. Finally, the simulation results shows the effectiveness of the proposed method.

关键词： Load management Load modeling Real-time systems Mathematical model Distributed power generation Optimization Heuristic algorithms

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Impedance control with New Inner Torque loop for Compliant Joints and Its Performance Analysis 36

Impedance Control with New Inner Torque loop for Compliant J...

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第36届中国控制会议

作者： Yin Ke Jian Li Zonglin Huang Shuai Li Guodong Li The Bionic Robot and System Key Laboratory School of Mechatronic EngineeringBeijing Institute of Technology Key Laboratory for Intelligent Control and Decision on Complex Systems School of AutomationBeijing Institute of Technology Beijing Jingwei Hirain Technologies

ISBN: (纸本)9781538629185

For the purpose of enhancing compliance of robot joint,an impedance control strategy with new inner torque controller is *** inertia of the motor can be scaled down thanks to this new type of torque *** of different position（motor-side position 9 and link-side position q） feedback strategies are explored through theoretical deviation,simulation and static stiffness *** expressions of static stiffness under both position feedback strategies are obtained with validity verified by Simulink *** with 9 feedback strategy,static stiffness can exceed spring stiffness under q feedback strategy with high desired stiffness,which means wider variation range of static stiffness and this benefits robot applications that require wider variation range of impedance,such as rehabilitation robots and collaborative ***,several experiments with the compliant joint prototype verify the developed controllers and show the efficiency of the proposed control approach in terms of compliant behavior.

关键词： Compliant joint Impedance control Static stiffness

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