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2nd International Conference on Cloud Computing and Internet of Things, CCIOT 2016

作者： Chen, Zhenjie Yan, Jingqi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of Ministry of Education for System Control and Information Processing China Shanghai China

ISBN: (纸本)9781467398213

This paper proposes k nearest neighbors (kNN) search based on set compression tree (SCT) and best bin first (BBF) to deal with the problem for big data. The large compression rate by set compression tree is achieved by compressing the set of descriptors jointly instead of compressing on a per-descript or basis. So set compression tree has a good performance in kNN search at a low bit rate. At the same time, the best bin first (BBF) is a very efficient algorithm to find the approximately kNN from a large number of high dimensional feature descriptors. SCT-BBF is a novel exploration and it improves search performance in three aspects: First, SCT-BBF requires less memory footprint, which is important in big data age. Second, it increases accuracy compared traditional method like KD-Tree and original SCT. SCT-BBF can be used with other data processing methods like PCA and SIFT to perform better. Third, this paper adopts finer search to increase accuracy at a slight loss of speed. And it can extend to big data easily. © 2016 IEEE.

关键词： Big data

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Association rule analysis for tour route recommendation and application to WCTSNOP

Association rule analysis for tour route recommendation and ...

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ISPRS Geospatial Week 2017

作者： Fang, Hui Chen, Chongcheng Lin, Jiaxiang Liu, Xianfeng Fang, Dong Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education Spatial Information Research Centre of Fujian Fuzhou University District Xueyuan Road China Dept. of Computer Science Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou University District Xiyuangong Road China College of Computer and Information Sciences Fujian Agriculture and Forestry University Fuzhou China Fuzhou Silviscene Information Technology Co. Ltd. China

The increasing E-tourism systems provide intelligent tour recommendation for tourists. In this sense, recommender system can make personalized suggestions and provide satisfied information associated with their tour cycle. Data mining is a proper tool that extracting potential information from large database for making strategic decisions. In the study, association rule analysis based on FP-growth algorithm is applied to find the association relationship among scenic spots in different cities as tour route recommendation. In order to figure out valuable rules, Kulczynski interestingness measure is adopted and imbalance ratio is computed. The proposed scheme was evaluated on Wangluzhe cultural tourism service network operation platform (WCTSNOP), where it could verify that it is able to quick recommend tour route and to rapidly enhance the recommendation quality. © Authors 2017. CC BY 4.0 License.

关键词： Data mining

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Indoor 3D scene reconstruction for mobile robots using Microsoft kinect sensor 35

Indoor 3D scene reconstruction for mobile robots using Micro...

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第35届中国控制会议

作者： LI Jiang-Wei ZHENG Ding-Fu GUAN Zhi-Hong CHEN Chao-Yang JIANG Xiao-Wei ZHANG Xian-He College of Automation Huazhong University of Science and Technology The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control (Huazhong University of Science and Technology) School of Information and Electrical Engineering Hunan University of Science and Technology College of Mechatronics and Control Engineering Hubei Normal University

ISBN: (纸本)9781509009107

3D mapping for unknown environments is a crucial issue for mobile service robots,which has many important applications in navigation and path *** this paper,we use Microsoft kinect sensor mounted on a mobile robot to obtain3 D *** the process,consistent frames of RGB-D data are captured and *** Closest Point(ICP)algorithm and incremental registration method are employed to perform the fine ***,we use OctoMap to store 3D map of octree representation,an efficient data ***,our results demonstrate the practical applicability and effectiveness of the proposed approach.

关键词： 3D mapping Kinect OctoMap Mobile Robots

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Distributed optimization problem for second-order multi-agent networks with only position interaction 35

Distributed optimization problem for second-order multi-agen...

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第35届中国控制会议

作者： TRAN Ngoc-Tu LIU Xiao-Kang WANG Yan-Wu School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control(Huazhong University of Science and Technology) Ministry of Education Hubei Provincial Collaborative Innovation Center for New Energy Microgrid China Three Gorges University

ISBN: (纸本)9781509009107

In this paper, distributed optimization problem is investigated under a second-order multi-agent network, in which each agent is described as the double integrator. The multi-agent network is introduced for solving a large scale optimization problem by the cooperation of coupled agents. Based on the interaction over the network, the optimal solution of the problem can be obtained. Since the existing distributed algorithms for second-order multi-agent network enforce each agent to transmit complete information(both state information and derivation information of the independent variable, i.e., corresponded position and velocity information of the agent), this paper is motivated to design the distributed algorithm with only using the position information of neighbors, which reduces the requirement on communication bandwidth. With the help of Lyapunov analysis and La Sallel's Invariance Principle, the optimal solution is derived and the optimization problem is solved via the second-order multi-agent network. Finally, a numerical example is presented to illustrate the theoretical result.

关键词： Second-order multi-agent networks Distributed optimization Consensus

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controllability of giant connected components in a directed network

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Physical Review E 2017年第4期95卷 042318-042318页

作者： Xueming Liu Linqiang Pan H. Eugene Stanley Jianxi Gao Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou 450002 Henan China Center for Complex Network Research and Department of Physics Northeastern University Boston Massachusetts 02115 USA

When controlling a complex networked system it is not feasible to control the full network because many networks, including biological, technological, and social systems, are massive in size and complexity. But neither is it necessary to control the full network. In complex networks, the giant connected components provide the essential information about the entire system. How to control these giant connected components of a network remains an open question. We derive the mathematical expression of the degree distributions for four types of giant connected components and develop an analytic tool for studying the controllability of these giant connected components. We find that for both Erdős-Rényi (ER) networks and scale-free (SF) networks with p fraction of remaining nodes, the minimum driver node density to control the giant component first increases and then decreases as p increases from zero to one, showing a peak at a critical point p=pm. We find that, for ER networks, the peak value of the driver node density remains the same regardless of its average degree 〈k〉 and that it is determined by pm〈k〉. In addition, we find that for SF networks the minimum driver node densities needed to control the giant components of networks decrease as the degree distribution exponents increase. Comparing the controllability of the giant components of ER networks and SF networks, we find that when the fraction of remaining nodes p is low, the giant in-connected, out-connected, and strong-connected components in ER networks have lower controllability than those in SF networks.

关键词： Network structure

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Fuzzy control for Uncertain Vehicle Active Suspension Systems via Dynamic Sliding-Mode Approach

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2017年第1期47卷 24-32页

作者： Wen, Shiping Chen, Michael Z. Q. Zeng, Zhigang Yu, Xinghuo Huang, Tingwen School of Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Department of Mechanical Engineering University of Hong Kong Hong Kong Hong Kong Platform Technologies Research Institute RMIT University MelbourneVIC3001 Australia Texas A and M University at Qatar Doha23874 Qatar

This paper investigates the fuzzy control issue for uncertain active suspension systems via dynamic sliding-mode method. The Takagi-Sugeno fuzzy approach is adopted on the background of the varying masses to describe the prescribed nonlinear system in order to achieve the design targets via the method of sector nonlinearity. This paper employs the dynamic sliding-mode scheme to control nonlinear active suspension systems. In the proposed sliding-mode control scheme, the sliding surface function is formed linearly with the system states and control inputs. Then, a fuzzy dynamic term is utilized to construct the sliding-mode feedback controller. In existing results, the sliding mode is achieved and maintained with no consideration of the system perturbations. Thus, sufficient conditions are proposed to make the sliding surface reachable with the existence of the system perturbations to make the augmented system stable. Finally, simulation results are presented to verify the effectiveness of the proposed schemes. © 2013 IEEE.

关键词： Robust control

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Online Calibration of Intracortical Neural Interface Based on Transfer Learning

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Journal of Physics: Conference Series 2018年第1期1069卷

作者： Bo Peng Wei Li Jiping He School of Automation Huazhong University of Science and Technology Wuhan 430074 P. R. China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan 430074 P. R. China Department of Mechanical Engineering Beijing Institute of Technology Beijing 100081 P. R. China

In the application of neural interface, the neural activity of neurons and neuronal groups is not fixed even under the same task conditions. Meanwhile, the recording conditions of neural signals are also very unstable, with a high degree of within-and across-day variability. This results in a very unstable firing pattern for the recorded neural spike signals. In order to get better performance, the decoder often requires a lot of online calibration samples. This brings a heavy training burden to neural interface users. To solve this problem, this paper proposes to apply transfer learning (TL) to online calibration of intracortical neural interface to reduce the dependence of decoder on a large number of online calibration samples. Experimental results show that through transferring from a large amount of historical data, decoder can achieve satisfactory classification accuracy with only a small amount of online data.

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Research on walking-aid robot motion control with both compliance and safety

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Zidonghua Xuebao/Acta Automatica Sinica 2016年第12期42卷 1859-1873页

作者： Xu, Wen-Xia Huang, Jian Yan, Qing-Yang Wang, Yong-Ji Tao, Chun-Jing Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan430074 China National Rehabilitation Center Beijing100176 China

Aimed at compliance and safety problems in motion control of walking-aid robot, a multi-sensor fusion based walking-aid robot motion control method with both compliance and safety is proposed. Firstly, the mechanism, control theory and multi-sensor system of the walking-aid robot are introduced. Then according to multi-sensor system, user motion intention estimation methods for each sensor are designed and a multi-sensor based compliance motion control for walking-aid robot is proposed. After analyzing user's possible falling modes, a Kalman filter (KF) based sequential probability ratio test (SPRT) method and decision function are used to detect the fall and falling mode. Finally, several compliance motion control experiments and fall detection experiments are described to show validity of the proposed algorithm. Copyright © 2016 Acta Automatica Sinica. All rights reserved.

关键词： Robots

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Design and analysis of minimizing torque ripple for direct torque controlled permanent magnet synchronous motor based on fuzzy control method

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3706-3713页

作者： Ning, Bowen Cheng, Shanmei Qin, Yi Key Laboratory of Education Ministry for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

This paper is presented to examine and improve the performance of the torque ripple suppression for direct torque controlled permanent magnet synchronous motor by using fuzzy control method. On the basis of analyzing the torque ripple of the direct torque control in details, the fuzzy controllers are designed for two parts. Since the errors of the torque and flux could not assess accurately in hysteresis structure, the hysteresis controllers of the conventional DTC method are replaced by the fuzzy controller which could select the optimal voltage vector by judging the deviation degree of the torque and flux errors according to the fuzzy logic inference. Then the action time of the selected optimal voltage vector is determined by using the fuzzy duty ratio control method, the ripples of torque and flux can be attenuated effectively. The comprehensive simulation experiment is exhibited to reveal the excellent response performance of the system and verify the feasibility of the proposed fuzzy control scheme. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Fuzzy control

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The study on Dynamics of Functional Brain network:Based on Symbolic Dynamics

The study on Dynamics of Functional Brain network:Based on S...

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第28届中国控制与决策会议

作者： Miao Wang Yapeng Li Xi Chen Wei Li College of Automation Huazhong University of Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China

ISBN: (纸本)9781467397155

It is an important means to reveal mysteries of the brain with information theory,but scientists rarely use this method for the study of the nervous system in recent *** this study,it's the first time,by using the concepts of information theory,to exploratory investigate the dynamic properties of time course data of fMRI and functional brain *** show that the symbolic dynamics method can reduce the noise of the MRI datasets,and highlight the differences between the *** elderly group,the regions with larger entropy are mainly located in prefrontal regions,basal ganglia ***,there are significant differences in the search information entropy between the young and elderly *** results have significance for the interpretation of the brain mechanisms,which may be the basis for follow-up studies of the brain mechanisms.

关键词： fMRI Symbolic dynamics Probabilistic entropy Search information entropy

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