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International Conference on Intelligent Transportation

作者： Qiankun Zhao Qing-Jie Kong Yingjie Xia Yuncai Liu Department of Automation and Key Laboratory of China MOE for System Control and Information Processing Shanghai Jiao Tong University Shanghai China Hangzhou Institute of Service Engineering Hangzhou Normal University Hangzhou China

Nowadays, probe vehicles equipped with Global Position system (GPS) are an effective way of collecting real-time traffic information. This paper first briefly introduces the Curve-Fitting Estimation Model (CFEM), which is one of the typical methods using GPS data to estimate the traffic flow state. After that, it is detailedly analyzed how many probe vehicles the CFEM requires in order to ensure enough estimated accuracy. Furthermore, a sample size algorithm is developed to calculate the minimum sample size of the CFEM. In the algorithm, the road type, the length of road section, and sample frequency are taken into account. Finally, the proposed algorithm of sample size analysis are tested by the experiments using the data collected from the road network of the whole center region of Shanghai.

关键词： Vehicles Probes Global Positioning system Roads State estimation Computational modeling

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Subspace identification using the saturation measurement in data-driven control systems

Subspace identification using the saturation measurement in ...

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Asian control Conference

作者： Yongling Wu Shaoyuan Li Hua Yang Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiaotong University Shanghai China College of Information Science and Engineering Ocean University of China Qingdao Shandong China

ISBN: (纸本)9781612844879

Saturation characteristic exists widely in the real system, and a large number of articles have taken constraint conditions into account during the controller design process. However, relative to the research on the input (actuator) saturation, study on the output (sensor) saturation has not been taken seriously and research results are very little, especially in the aspect of effect on the identification due to the saturation output. In this paper, under the data-driven control system based on online subspace identification and model predictive control (MPC) method, the relationship among the output saturation step, prediction horizon and subspace matrix is obtained, while the change of the system information is unknown because the output signals are locked. Finally, a simulation example is given to demonstrate the correction of the conclusion.

关键词： Predictive models Matrix decomposition Mathematical model Predictive control Actuators

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Coal-fired boiler ash deposition monitoring technology of economizer

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Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) 2011年第SUPPL. 1期41卷 285-287页

作者： Wang, Bin Wang, Jing-Cheng Shi, Yuan-Hao Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiaotong University Shanghai 200240 China

For the purpose of realization of ash deposition monitoring and optimal operation of sootblowing, taking the economizer as the research object and the cleanliness factor as the measurement of the degree of pollution of heating surface, based on the principle of heat balance, a model of heating surface ash deposition was being established. The model considered the impact of changing conditions, and added radiation heat transfer as sub-module. Finally, with offline data to calculate the model, it is verified that the model is reasonable.

关键词： Deposition

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Dynamic average consensus estimation over stochastically switching network via quantization communication

Dynamic average consensus estimation over stochastically swi...

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Chinese control Conference (CCC)

作者： Dequan Li Qipeng Liu Xiaofan Wang Department of Automation and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiaotong University Shanghai China Department of Automation Ministry of Education of China Shanghai P. R. China

In this paper, we consider the problem that a group of agents aims to compute the average of individually estimated noisy parameters by sharing information among a random network of digital links. In this scenario, the average consensus seeking is involved in a two-step procedure. First, each agent estimates the local time-varying parameters individually, and then agents average their estimations by interaction with neighbors through quantized communication. Impact of quantization on the performance of the proposed distributed algorithm is investigated. We prove that the agents' states converge to a random variable that deviates from the average of the estimated parameters. We derive an upper bound for the asymptotic residual mean square error of the states, which captures effects of the quantization precision and the structure of the random communication networks.

关键词： Quantization Heuristic algorithms Estimation Probabilistic logic Mean square error methods Noise Symmetric matrices

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Video vehicle detection through multiple background-based features and statistical learning

Video vehicle detection through multiple background-based fe...

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International Conference on Intelligent Transportation

作者： Mingxia Sun Kunfeng Wang Ming Tang Fei-Yue Wang Jinfeng Yang Tianjin Key Laboratory of Advanced Signal Processing Civil Aviation University of China Tianjin China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences (CAS) Beijing China

This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image, assuming moving vehicles may cause pixel intensities and local texture to change, and then by identifying such pixel changes to detect vehicles. In this research, multiple pattern classifiers including LDA + Adaboost, SVM, and Random Forests are used to detect vehicles that are passing through virtual loops. We extract fourteen pattern features (related to foreground area, texture change, and luminance and contrast in the local virtual loop zone and the global image) to train pattern classifiers and then detect vehicles. As experimental results illustrate, the proposed approach is quite robust to detect vehicles under complex dynamic environments, and thus is able to improve the accuracy of traffic data collection in all weather for long term.

关键词： Vehicles Feature extraction Training Image edge detection Vehicle detection Meteorology Radio frequency

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Data-driven process monitoring method based on dynamic component analysis

Data-driven process monitoring method based on dynamic compo...

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Chinese control Conference (CCC)

作者： Guangming Zhang Ning Li Shaoyuan Li Department of Automation and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiaotong University Shanghai China Department of Automation Ministry of Education of China Shanghai P. R. China

A novel data-driven process monitoring method based on dynamic independent component analysis-principle component analysis (DICA-DPCA) is proposed to compensate for shortcomings in the conventional component analysis based monitoring methods. The primary idea is to first augment the measured data matrix to take the process dynamic into account. Then perform independent component analysis (ICA) and principle component analysis (PCA) on the augmented data to capture both the non-Gaussian and Gaussian process information. Finally, a combined monitoring statistic is proposed by support vector data description (SVDD) with its control limit being determined by bootstrap quantile estimation method to lessen monitoring work-load. The Tennessee Eastman process is used to demonstrate the improved monitoring performance of the proposed mechanism in comparison with existing component analysis based monitoring methods, including PCA, ICA, ICA-PCA, dynamic PCA, and dynamic ICA.

关键词： Monitoring Principal component analysis Process control Estimation Data mining Support vector machines Training

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Reliability assessments of Chinese high speed railway network

Reliability assessments of Chinese high speed railway networ...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Jianhua Zhang Liu Hong Shuliang Wang Xiaoming Xu Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Department of Control Science and Engineering Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Shanghai Academy of System Science University of Shanghai for Science and Technology Shanghai China

With the economic developments, high speed railway has been paid many attentions in China and medium- short term planning of Chinese high speed railway network has been formed and most of the railways have been started into operations. In this paper, graph theory and complex network theory are adopted to assess the reliability of Chinese high speed railway network. The topological characteristics and real distances between pairs of stations are discussed to investigate the reliability of Chinese high-speed rail network. Several parameters are presented to investigate the topological characteristics and the reliability and robustness of the network subject to failures. The parameter called unit degree betweenness is proposed to assess the transport capacity of lines connecting with the nodes. The largest degree node-based attacks and the highest betweenness node-based attacks are involved into Chinese high speed railway network to assess the topological reliability and robustness. The results show that the highest betweenness node-based attacks are more effective to destroy the network than the largest degree node-based attacks. Moreover, the cumulative degree distribution and the real mileages of railways between pairs of stations can be fitted by Gauss functions, and the distribution of real shortest distances over all pairs of stations of the network is fitted by a normal distribution function. By the simulations, the critical stations, Guangzhou Station, Zhengzhou Station and Jinan Station for the largest degree node-based attacks, and Wuhan Station, Xuzhou Station and Shijiazhuang Station for the highest betweenness node-based attacks, can be obtained in this paper.

关键词： Artificial neural networks Robustness Rail transportation

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Angle restriction enhances synchronization of self-propelled objects

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Physical Review E 2011年第4期84卷 046115-046115页

作者： Jianxi Gao Shlomo Havlin Xiaoming Xu H. Eugene Stanley Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 PR China Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA Department of Physics Bar-Ilan University IL-52900 Ramat-Gan Israel

Understanding the synchronization process of self-propelled objects is of great interest in science and technology. We propose a synchronization model for a self-propelled objects system in which we restrict the maximal angle change of each object to θR. At each time step, each object moves and changes its direction according to the average direction of all of its neighbors (including itself). If the angle change is greater than a cutoff angle θR, the change is replaced by θR. We find that (i) counterintuitively, the synchronization improves significantly when θR decreases, (ii) there exists a critical restricted angle θRc at which the synchronization order parameter changes from a large value to a small value, and (iii) for each noise amplitude η, the synchronization as a function of θR shows a maximum value, indicating the existence of an optimal θR that yields the best synchronization for every η.

关键词： NOISE SYNCHRONIZATION ROBOTS STOCHASTIC convergence MATHEMATICS

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Visual tracking of robots in uncalibrated environments

Visual tracking of robots in uncalibrated environments

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2011 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Hesheng Wang Weidong Chen Zhongli Wang Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

This paper presents a new adaptive controller for visual tracking control of a robot manipulator in 3D general motion with a fixed camera whose intrinsic and extrinsic parameters are uncalibrated. In addition to camera parameters, the feature positions in 3D space are also assumed unknown. Based on the fact that the unknown parameters appears linearly in the closed-loop dynamics of the system if the depth-independent interaction matrix is adopted to map the image errors onto the joint space of the manipulator, we developed a new adaptive algorithm to estimated the unknown parameters on-line. With a full consideration of dynamic responses of the robot manipulator, we employ the Lyapunov method to prove asymptotic convergence of the image errors. Experimental results are used to demonstrate the performance of the proposed approach.

关键词： Cameras Robot vision systems Trajectory Manipulator dynamics Joints

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Harmonic signals extraction by multi-resolution BSS

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Journal of Computational Information systems 2011年第2期7卷 585-592页

作者： Liu, keying Wang, Cunsheng Wang, Fasong Department of Mathematics North China University of Water Resources and Electric Power Zhengzhou 450011 China North Automatic Control Technology Institute Taiyuan 030006 China China Electronics Technology Group Corporation The 27th Research Institute Zhengzhou 450047 China National Key Laboratory for Radar Signal Processing Xidian University Xi'an 710071 China

Using the sparsity property in the frequency domain of harmonic signals, this paper gives a harmonic signal extraction algorithm based on multi-resolution blind source separation(BSS) method. After the general and detailed definition of the multi-resolution BSS model is given, the wavelet packet decomposition based multi-resolution BSS algorithm for harmonic signal extraction is constructed in detail. Some simulations of the proposed algorithm are exhibited in the simulation part to demonstrate the validity of the method. At last, we discuss the impact of multiresolution BSS research and outline potential future research directions and applications. Copyright © 2011 Binary Information Press.

关键词： Blind source separation

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