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作者： Zhang, Tao Fei, Shu-Min College of Automation Electronic Engineering Qingdao University of Sciences and Technology Qingdao China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9781424487363

Robust real-time tracking of non-rigid objects is a challenging task. Color is a powerful feature for tracking deformable objects in image sequences with complex backgrounds. Color distribution is applied, as it is robust to partial occlusion, is rotation and scale invariant and computationally efficient. Particle filter has been proven very successful for non-linear and non-Gaussian estimation tracking problems. The article presents the integration of color distributions into particle filtering. A target is tracked with a particle filter by comparing its histogram with the histograms of the sample positions using the Bhattacharyya distance. Additionally, to solve the sample impoverishment (all particles collapse to a single point within a few iterations) in the particle-filter algorithm, a new resampling algorithm is proposed to tackle sample impoverishment. The performance of the proposed filter is evaluated qualitatively on various real-world video sequences. The experimental results show that the improved color-based particle filter algorithm can reduce sample impoverishment effectively and track the moving object very well. © 2011 IEEE.

关键词： Color

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Path Selection in Disaster Response Management Based on Q-learning

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International Journal of Automation and computing 2011年第1期8卷 100-106页

作者： Zhao-Pin Su Jian-Guo Jiang Chang-Yong Liang2＇ 3 Guo-Fu Zhang Guo-Fu Zhang Key Laboratory of Special Display Technology （Hefei University of Technology） Ministry of Education Hefei 230009 PRC School of Computer and Information Hefei University of Technology Hefei 230009 PRC Postdoctoral Research Station for Management Science and Engineering Hefei University of Technology Hefei 230009 PRC Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei 230009 PRC

Suitable rescue path selection is very important to rescue lives and reduce the loss of disasters, and has been a key issue in the field of disaster response management. In this paper, we present a path selection algorithm based on Q-learning for disaster response applications. We assume that a rescue team is an agent, which is operating in a dynamic and dangerous environment and needs to find a safe and short path in the least time. We first propose a path selection model for disaster response management, and deduce that path selection based on our model is a Markov decision process. Then, we introduce Q-learning and design strategies for action selection and to avoid cyclic path. Finally, experimental results show that our algorithm can find a safe and short path in the dynamic and dangerous environment, which can provide a specific and significant reference for practical management in disaster response applications.

关键词： Disaster response management path selection agent self-organizing Markov decision process Q-learning.

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Path planning of robotic fish based on genetic algorithm and modified dynamic programming

Path planning of robotic fish based on genetic algorithm and...

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2011 International Conference on Advanced Mechatronic Systems, ICAMechS 2011

作者： Yang, Qian Yu, Mei Liu, Shu Chai, Zhong-Ming School of Control and Computer Engineering North China Electric Power University Beijing 102206 China Key Laboratory of Measurement and Control New Technology and System for Industrial Process North China Electric Power University Beijing 102206 China

ISBN: (纸本)9780955529375

In this paper, genetic algorithm and modified dynamic programming are applied to path planning of robotic fish for the first time. Using grid method to the environment modeling and applying genetic algorithm to the path planning, an optimal or sub-optimal robot path can be obtained. Since the robotic fish can't track linear motion, the robot path can be seen as several circular arc. Based on the optimal path obtained via genetic algorithm, modified dynamic programming algorithm is proposed to calculate the shortest circular arc path, fish velocity and direction in every step. Finally the experiment on the robotic fish control software shows the effectiveness of the proposed method. © 2011 Intl Journal of Adv Mechatr.

关键词： Motion planning

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Matching decision model for self- adaptability of knowledge manufacturing system

Matching decision model for self- adaptability of knowledge ...

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2011 International Conference on Information Science and technology, ICIST 2011

作者： Wang, Yufang Yan, Hongsen Meng, Xiangang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing Jiangsu Province 210096 China School of Information and Control Engineering Nanjing University of Information Science and Technology Nanjing Jiangsu Province 210044 China

ISBN: (纸本)9781424494408

Knowledge manufacturing system has the ability of modifying dynamically manufacturing mode rapidly when production environment factors change. It is essential to evaluate the matching degree of established manufacturing mode and changed production environment factors. In this paper, a matching decision model for self-adaptability of knowledge manufacturing system based on the fuzzy neural network is proposed. The changed production environment factors are regarded as linguistic variable inputs. A modified momentum factor B-P algorithm consisting of information feed-forward process and the error back-propagation process is used. The proposed FNN model is employed to evaluate the matching degree of a car-lamp production manufacturing mode to variable environment units. Matching result indicates adaptive degree of manufacturing system. Experiment result demonstrates the method is effective. © 2011 IEEE.

关键词： Manufacture

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Design and implementation of substation communication software for IED

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Dianli Xitong Baohu yu Kongzhi/Power System Protection and control 2011年第24期39卷 132-137页

作者： Hu, Feng-Kai Huang, Qi Jing, Shi Li, Jing The Power System Wide-area Measurement and Control Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu 611731 China

With the development of smart grid, Intelligent Electronic Device (IED) will be increasingly used in substation protection, control and measurement. A kind of substation communication software for variety of IEDs is designed and implemented. This paper focuses on the overall flow of the system, function library, multithreading architecture, and the design of database. This software utilizes the Modbus TCP/IP which is an openly published, efficient, and widely used communication protocol in the industrial automation field. In order to make the system have a strong scalability, this paper also describes the implementation guide of Modbus based on IPv6. Finally, the performance of the library and the real time capability of the overall system are tested respectively, indicating that this software meets the requirements of being efficient and stable, reliable in the communication of substation.

关键词： Software testing

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Stochastic distribution control theory applied in superheated steam temperature systems

Stochastic distribution control theory applied in superheate...

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Chinese control Conference (CCC)

作者： Jianhua Zhang Fenfang Zhang Guolian Hou Jinfang Zhang Beijing Key Laboratory of Industrial Process Measurement and Control New Technology and System 102206 China

A novel control algorithm is applied to control superheated steam temperature in power plants. Since the disturbances existed in practical processes are probably non-Gaussian, the performance index is constructed by minimizing the entropy and mean value of tracking error besides the constraints on control energy. The optimal control solution is given and applied to control superheated steam temperature in a power plant. The simulation results verify its effectiveness.

关键词： Entropy Temperature control Process control Stochastic processes Temperature distribution Temperature measurement Performance analysis

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A New Robust Least Squares Support Vector Machine for Regression with Outliers

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Procedia Engineering 2011年 15卷 1355-1360页

作者： Lü You Liu Jizhen Qu Yaxin Key Laboratory of Measurement & Control New Technology and System for Industrial Process North China Electric Power University Beijing 102206 China

The least squares support vector machine (LS-SVM) is sensitive to noises or outliers. To address the drawback, a new robust least squares support vector machine (RLS-SVM) is introduced to solve the regression problem with outliers. A fuzzy membership function, which is determined by heuristic method, is assigned to each training sample as a weight. For each data point, firstly a deleted input neighborhood is found when the high-dimension feature space of input is focused on. Then the new field is reformulated after the output is brought in the neighborhood which we have found. The fuzzy membership function (weight) is set according to the distance from the data point to the center of its neighborhood and the radius of the neighborhood, which implies the probability to be an outlier. Two benchmark simulation experiments and analysis are presented to verify that the performance is improved.

关键词： Outlier Robust Weight Least squares support vector machine Regression

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A reconstruction method for disparity image based on region segmentation and RBF neural network

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Information technology Journal 2011年第5期10卷 1050-1055页

作者： Shuchun, Yu Xiaoyang, Yu Li'na, Shan Yuping, Zhang Yongbin, Shen Miaomiao, Tian Shenshen, Fan Haixia, Huang School of Measurement-Control Technology College of Measurement-Control Technology and Communications Engineering Harbin University of Science and Technology Harbin 150080 China Key Laboratory for Measuring and Control Technology and Instrumentations of Heilongjiang Province Harbin University of Science and Technology XueFu Road Nan Gang District Harbin 150080 China

The Reconstruction for disparity image is the key technology for 3D image restoration in stereovision field. However, the data volume of disparity images is so large and the topological structures of disparity images is so complicated that reconstruction for disparity image is very difficult. We had done a lot of works for the sake of constructing a new method to reconstruct disparity image. In this study, a reconstruction method for disparity image based on region segmentation and isomorphic RBF(Radical Basis Function) neural network is presented. First, the disparity image is divided into some regions with adjustable threshold and edge detection. Next, reconstruction based on RBF neural network is carried out in every region, in which process the disparity point clouds are optimized. Then, all the regions are connected and the reconstruction result is obtained. When reconstruction based on RBF is executed in different regions, trainings are carried on with different resolution data according to the complexity of the structures of different regions. Experimental results show that the method proposed in this study can attain reconstruction results of high quality effectively. © 2011 Asian Network for Scientific Information.

关键词： Edge detection

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Forecasting product design time based on Gaussian margin regression

Forecasting product design time based on Gaussian margin reg...

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IEEE 2011 10th International Conference on Electronic measurement and Instruments, ICEMI 2011

作者： Shang, Zhigen Yan, Hongsen School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China Department of Automation Yancheng Institute of Technology Yancheng 224003 China

ISBN: (纸本)9781424481590

In order to obtain a forecast model for product design time from a small data set, Gaussian Margin Regression (GMR) is presented on the basis of combining Gaussian Margin Machines and kernel based regression. Gaussian Margin Regression maintains a Gaussian distribution over weight vectors for kernel based regression. The algorithm is applied to seeking the least information distribution that will make actual value be included in the confidential interval with high probability, and embedded genetic algorithm is presented for choosing its relevant parameters. The results of application in injection mold designs reveal that the time forecast model based on GMR is of feasibility and validity. © 2011 IEEE.

关键词： Product design

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Study of measurement of Protein Content Based on Laser Light Scattering technology

Study of Measurement of Protein Content Based on Laser Light...

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2011 2nd Asia-Pacific Conference on Wearable Computing Systems

作者： Qin Yong Zhou Zhen College of Measurement and Control Technology and Communication Engineering The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province Harbin University of Science and Technology

The objectives of this study were to investigate the measurement methodology of the protein content in skimmed milk by laser light scattering(LLS). There was a definition that the ratio of the scattering light( at 90° scattering angles, relative to the incident beam direction) intensity to the transmitted light intensity, which was called scattered transmitted ratio(STR). Using the STR theory, we constructed a sensing system to measure the protein content. The sensing system contains a laser beam of 658 nm wavelength, sample reservoir and two photodiodes which measure the scattered light and transmitted light respectively. Through data analysis, the relationship model was established between the protein content and the STR. Comparing with Kjeldahl determination of nitrogen, the STR method described in this study can also accurately measure the protein content.

关键词： skim milk protein laser light scattering measurement

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