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2017 2nd International Conference on Renewable Energy and Smart Grid (ICRESG2017)

作者： Zhe Jiang Zhimin Li Wenbo Li Mingqiang Wang Mengxia Wang Department of Electrical Engineering Harbin Institute of Technology Electric Power Research Institute State Grid Shandong Electric Power Company Key Laboratory of Power System Intelligent Dispatch and Control Shandong University

In this paper, a cooperation method between wind farm and Electric vehicle battery switch station（EVBSS） was proposed. In the pursuit of maximizing their own benefits, the cooperation between wind farm and EVBSS was formulated as a Stackelberg game model by treating them as decision makers in different status. As the leader, wind farm will determine the charging/discharging price to induce the charging and discharging behavior of EVBSS reasonably. Through peak load shifting, wind farm could increase its profits by selling more wind power to the power grid during time interval with a higher purchase price. As the follower, EVBSS will charge or discharge according to the price determined by wind *** optimizing the charging/discharging strategy, EVBSS will try to charge with a lower price and discharge with a higher price in order to increase its profits. Since the possible charging/discharging strategy of EVBSS is known, the wind farm will take the strategy into consideration while deciding the charging/discharging price, and will adjust the price accordingly to increase its profits. The case study proved that the proposed cooperation method and model were feasible and effective.

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Blind restoration of post-stack 3D seismic data 86th

Blind restoration of post-stack 3D seismic data

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SEG International Exposition and 86th Annual Meeting, SEG 2016

作者： Wang, Yi Lu, Wenkai Easysignal group State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing100084 China

Post-stack 3D seismic data is spatially blurred by the effect of migration operators with limited aperture widths, which is not conducive to discontinuity (such as fault, channel, etc.) detection. By approximating the migration blur with a time-invariant point spread function (PSF), seismic image deblurring method has been used to obtain a deblurred seismic data with enhanced discontinuity. We denote this method as TIPSF. By applying a discontinuity detection method (say, the coherence algorithm) on the deblurred seismic data, a better result is achieved, in comparison with the result obtained by applying the same method on the original seismic data directly. Since the migration blurs are always time-dependent in real seismic data, we propose a time-variant PSF estimation algorithm for seismic image deblurring in this paper, which is named as TVPSF. In which, we first obtain a series of initial PSFs' estimates from a 3D seismic data by estimating one PSF from each horizontal time slice (HTS), respectively. Secondly, we construct a sequence of time windows with adaptive variable length, according to the similarities with these initial PSFs' estimates. Thirdly, we use the average of these initial PSFs' estimates, which are fallen in one time window, to be the final PSF estimate corresponding to the center sample point of this time window. For these non-center sample points, a linear interpolation method is used to obtain their final PSFs' estimates using the PSFs' estimates of those center sample points. At last, a 2D Wiener filter is used to perform seismic image deblurring, HTS by HTS. Furthermore, in order to adapt to different signal-to-noise ratios (SNR) level in time slices of the 3D seismic data, our proposed method adjusts the whitening factor of the Wiener filter for each HTS according to its energy. Applications of both TVPSF and TIPSF methods on a real data set show that the TVPSF method outperforms the TIPSF method clearly, which demonstrate the validity o

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Training and testing object detectors with virtual images

arXiv

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arXiv 2017年

作者： Tian, Yonglin Li, Xuan Wang, Kunfeng Wang, Fei-Yue Department of Automation University of Science and Technology of China Hefei230027 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

In the area of computer vision, deep learning has produced a variety of state-of-the-art models that rely on massive labeled data. However, collecting and annotating images from the real world has a great demand for labor and money investments and is usually too passive to build datasets with specific characteristics, such as small area of objects and high occlusion level. Under the framework of Parallel Vision, this paper presents a purposeful way to design artificial scenes and automatically generate virtual images with precise annotations. A virtual dataset named ParallelEye is built, which can be used for several computer vision tasks. Then, by training the DPM (Deformable Parts Model) and Faster R-CNN detectors, we prove that the performance of models can be significantly improved by combining ParallelEye with publicly available real-world datasets during the training phase. In addition, we investigate the potential of testing the trained models from a specific aspect using intentionally designed virtual datasets, in order to discover the flaws of trained models. From the experimental results, we conclude that our virtual dataset is viable to train and test the object detectors. Copyright © 2017, The Authors. All rights reserved.

关键词： Object detection

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Frequency synchronization for uplink massive MIMO systems

arXiv

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arXiv 2017年

作者： Zhang, Weile Gao, Feifei Jin, Shi Lin, Hai MOE Key Lab for Intelligent Networks and Network Security Xi'An Jiaotong University Xi'an Shaanxi710049 China State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing100084 China National Communications Research Laboratory Southeast University Nanjing210096 China Department of Electrical and Information Systems Osaka Prefecture University Osaka Japan

In this paper, we propose a frequency synchronization scheme for multiuser orthogonal frequency division multiplexing (OFDM) uplink with a large-scale uniform linear array (ULA) at base station (BS) by exploiting the angle information of users. Considering that the incident signal at BS from each user can be restricted within a certain angular spread, the proposed scheme could perform carrier frequency offset (CFO) estimation for each user individually through a joint spatial-frequency alignment procedure and can be completed efficiently with the aided of fast Fourier transform (FFT). A multi-branch receive beamforming is further designed to yield an equivalent single user transmission model for which the conventional singleuser channel estimation and data detection can be carried out. To make the study complete, the theoretical performance analysis of the CFO estimation is also conducted. We further develop a user grouping scheme to deal with the unexpected scenarios that some users may not be separated well from the spatial domain. Finally, various numerical results are provided to verify the proposed studies. Copyright © 2017, The Authors. All rights reserved.

关键词： Orthogonal frequency division multiplexing

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Robust group lasso over decentralized networks

arXiv

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arXiv 2017年

作者： Wang, Manxi Li, Yongcheng Wei, Xiaohan Ling, Qing State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System Luoyang China Department of Electrical Engineering University of Southern California Los Angeles United States Department of Automation University of Science and Technology of China Hefei China

This paper considers the recovery of group sparse signals over a multi-agent network, where the measurements are subject to sparse errors. We first investigate the robust group LASSO model and its centralized algorithm based on the alternating direction method of multipliers (ADMM), which requires a central fusion center to compute a global row-support detector. To implement it in a decentralized network environment, we then adopt dynamic average consensus strategies that enable dynamic tracking of the global row-support detector. Numerical experiments demonstrate the effectiveness of the proposed algorithms. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning

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Analysis of underwater locomotion and improvement of FroBot

Analysis of underwater locomotion and improvement of FroBot

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2016 IEEE International Conference on Advanced intelligent Mechatronics, AIM 2016

作者： Yi, Yang Jianqing, Zhang Han, Xu Maokuan, Chen Lu, Zhang Zhongjing, Zhu School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Electronic Engineering School of Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781509020652

The main characteristic of FroBot is the dual-swing-legs propulsion mechanism, and it is necessary for us to conduct a series of experiments to study its propulsion model, both on land and underwater. As the propulsion of FroBot comes from the interaction force between caudal fins and water when it locomotes underwater, this paper presents an analysis about the propulsion and control of angle Θ. Then a number of underwater hydrodynamic simulations and analysis are also conducted to get a better control in reality. Finally, on the basis of propulsion model and experiments, we present the latest mechanical structure designs and further improvements to eliminate the limitations exposed in the previous generations of FroBot. © 2016 IEEE.

关键词： Propulsion

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Power flow calculation considering power exchange control for multi-area interconnection power networks 52

Power flow calculation considering power exchange control fo...

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52nd Annual Meeting on IEEE Industry Application Society, IAS 2016

作者： Dong, Xiaoming Ding, Yuanyuan Zhao, Penghui Wang, Chengfu Wang, Yong Sun, Hua Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China Department of Electrical Automation Shandong Labour Vocational and Technology College Jinan China

ISBN: (纸本)9781467386715

Base on the power flow formulations, a new power flow model that allows for power exchanges among subareas of network and automation generation control in each subarea, is established. The proposed power flow model is rendering by unified newton iteration formulation. Parameters representing the level or allocation of the unbalancing power are introduced to indicate the performance of the generators that participate in the automation generation control. The power exchange formulations for subareas are derived from the power flow equations of the interconnected branches. The Newton iteration method is used to solve the equations that consist of node power injection equations and interconnected power equations. Because of the consideration of the power balance in each subarea and the order of power exchange, the presented method is applicable for power flow problems of interconnected power networks, and is in particular applicable for the system analysis and calculation that based on the uniform iteration formulation. Case studies of IEEE 5 bus test system and IEEE RTS96 system illustrate the efficiency and the convergence of the proposed method. © 2016 IEEE.

关键词： systems analysis

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Dejun Guo Hesheng Wang Weidong Chen Ming Liu Zeyang Xia Kam K. Leang DARC (Design Automation Robotics & Control) Lab University of Utah Robotics Center Salt Lake City Utah USA State Key Laboratory of Robotics and System (HIT) Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Institute of Biomedical and Health Engineering Chinese Academy of Sciences Shenzhen China

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Cameras Robot vision systems Kinematics Mobile robots Calibration automation

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Energy management strategy research for residential microgrid considering virtual energy storage system at demand side

Energy management strategy research for residential microgri...

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International Conference on Electronic Measurement and Instruments, ICEMI

作者： Liu Changliang Wu Yanqun Bai Kang Liu Weiliang Chen Chen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China Automation Department North China Electric Power University Baoding China Department of mineral resources and architectural engineering Hebei Energy College of Vocation and Technology Tangshan China

An energy management strategy for residential microgrid is proposed, which takes the virtual energy storage system into consideration. Firstly, a heat transfer model is established based on the heat balance equation for the residential buildings with low temperature floor radiant heating / cold and the potential of the energy storage is analyzed. After that, the residential building is used as a virtual energy storage system, and a micro grid energy management model based on economy and comfort is constructed. Finally, taking the winter heating scenario as an example, the scheduling results under different energy management strategies are analyzed for two typical residential microgrids. The results show that the proposed energy management strategy can tap the energy storage potential of residential buildings, so as to effectively reduce the operating costs of microgrid under the premise of ensuring user comfort.

关键词： Resistance heating Floors Microgrids Energy storage Silicon

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Learning with only multiple instance positive bags

Learning with only multiple instance positive bags

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2016 International Joint Conference on Neural Networks, IJCNN 2016

作者： Wang, Zhigang Zhao, Zengshun Zhang, Changshui Computer and Communication Engineering School Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education China College of Electronics Communication and Physics Shandong University of Science and Technology China Automation Department Tsinghua University State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology China

ISBN: (纸本)9781509006199

In traditional multiple instance learning (MIL), both positive and negative bags are required to learn a prediction function. However, a high human cost is needed to know the label of each bag - positive or negative. Only positive bags contain our focus (positive instances) while negative bags consist of noise or background (negative instances). So we do not expect to spend too much to label the negative bags. Contrary to our expectation, nearly all existing MIL methods require enough negative bags besides positive ones. In this paper we propose an algorithm called 'Positive Multiple Instance' (PMI), which learns a classifier given only a set of positive bags. So the annotation of negative bags becomes unnecessary in our method. PMI is constructed based on the assumption that the unknown positive instances in positive bags be similar each other and constitute one compact cluster in feature space and the negative instances locate outside this cluster. The experimental results demonstrate that PMI achieves the performances close to or a little worse than those of the traditional MIL algorithms on benchmark and real data sets. However, the number of training bags in PMI is reduced significantly compared with traditional MIL algorithms. © 2016 IEEE.

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