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IEEE International Conference on Networking, Sensing and control

作者： Shuangshuang Li Zhen Shen Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center for Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

The k-nearest neighbor (k-NN) nonparametric regression is a classic model for single point short-term traffic flow forecasting. The traffic flows of the same clock time of the days are viewed as neighbors to each other, and the neighbors with the most similar values are regarded as nearest neighbors and are used for the prediction. In this method, only the information of the neighbors is considered. However, it is observed that the “trends” in the traffic flows are useful for the prediction. Taking a sequence of consecutive time periods and viewing the a sequence of “increasing”, “equal” or “decreasing” of the traffic flows of two consecutive periods as a pattern, it is observed that the patterns can be used for prediction, despite the patterns are not from the same clock time period of the days. Based on this observation, a pattern recognition algorithm is proposed. Moreover, empirically, we find that the patterns from different clock time of the days can have different contributions to the prediction. For example, if both to predict the traffic flow in the morning, the pattern from the morning can lead to better prediction than same patterns from afternoon or evening. In one sentence, we argue that both the pattern and the clock time of the pattern contain useful information for the prediction and we propose the weighted pattern recognition algorithm (WPRA). We give different weights to the same patterns of different clock time for the prediction. In this way, we take both virtues of the k-NN method and the PRA method. We use the root mean square error (RMSE) between the actual traffic flows and the predicted traffic flows as the measurement. By applying the results to actual data and the simulated data, about 20% improvement compare with the PRA is obtained.

关键词： Clocks Data models Pattern recognition Prediction algorithms Mathematical model Meteorology Vectors

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A novel parking control algorithm for a car-like mobile robot

A novel parking control algorithm for a car-like mobile robo...

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IEEE International Conference on Networking, Sensing and control

作者： Yaru Zhang Shuming Tang Zhilin Zhang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

This paper proposes a novel algorithm for parking motion of a Car-like mobile robot. The algorithm presented here addresses calculating equations for planning a parking path in real time. Moreover, by incorporating the constraints of the mechanical and kinematical characteristics of the car and the geometry of the parking lot in the path planning, we can turn a parking problem into solving algebraic equations. By tracking a planned path, the Car-like mobile robot can drive into the parking area without hitting any boundaries. The efficiency of the proposed algorithm is demonstrated by simulation.

关键词： Vehicles Mobile robots Algorithm design and analysis Mathematical model Turning Equations Signal processing algorithms

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A review on vision-based pedestrian detection in intelligent transportation systems

A review on vision-based pedestrian detection in intelligent...

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IEEE International Conference on Networking, Sensing and control

作者： Bo Li Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Pedestrians are key participants in transportation systems, so pedestrian detection in video surveillance systems is of great significance to the research and application of intelligent Transportation systems (ITS). We review some methods and models for vision-based pedestrian detection in recent years. In this paper, the pedestrian detection techniques are divided into macroscopic and microscopic according to different application in transportation systems. Macroscopic pedestrian detection aims to estimate crowd density without distinguishing each pedestrian, and microscopic pedestrian detection focuses on detection and recognition of individual pedestrians. The latter detection style is deeply studied, so it is presented in detail in this paper, especially for the feature-classifier-based detection method. Finally, the pedestrian detection algorithms are discussed and concluded from the viewpoint of video surveillance and ITS. Existing problems and future trends are presented in that section.

关键词： Feature extraction Shape Training Transportation Traffic control Video surveillance

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A vehicle license plate recognition system based on analysis of maximally stable extremal regions

A vehicle license plate recognition system based on analysis...

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IEEE International Conference on Networking, Sensing and control

作者： Bo Li Bin Tian Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Vehicle License Plate Recognition (VLPR) system is a core module in intelligent Transportation systems (ITS). In this paper, a VLPR system is proposed. Considering that license plate localization is the most important and difficult part in VLPR system, we present an effective license plate localization method based on analysis of Maximally Stable Extremal Region (MSER) features. Firstly, MSER detector is utilized to extract candidate character regions. Secondly, the exact locations of license plates are inferred according to the arrangement of characters in standard license plates. The advantage of this license plate localization method is that less assumption of environmental illumination, weather and other conditions is made. After license plate localization, we continue to recognize the license plate characters and color to complete the whole VLPR system. Finally, the proposed VLPR system is tested on our own collected dataset. The experimental results show the availability and effectiveness of our VLPR system in locating and recognizing all the explicit license plates in an image.

关键词： Licenses Image color analysis Character recognition Lighting Histograms Feature extraction Image segmentation

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Rear lamp based vehicle detection and tracking for complex traffic conditions

Rear lamp based vehicle detection and tracking for complex t...

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IEEE International Conference on Networking, Sensing and control

作者： Ye Li Qingming Yao State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

In video surveillance system, detection and tracking of vehicles are two foundational and significant tasks. In this paper, a vehicle detection and tracking method based on rear lamp pairs is proposed. The proposed method combines color with motion information to perform vehicle detection. In order to adapt to different weather conditions like night, the rear lamps are divided into two categories: unlit lamps and lighted lamps. First, threshold segmentation are used to extract both the unlit and lighted lamp candidates in hue-saturation-value (HSV) color space and the thresholds are selected automatically by maximally stable extremal region (MSER) method. Then, all lamp candidates are tracked by using Kalman filter and lamp candidates with short-lived trajectories are removed to avoid disturbances. Next, two adjacent lamp candidates with similar speed are bound together as a region of interest (ROI), which represents a potential pair of lamps. Image cross-correlation symmetry analysis based on Gabor filter is utilized to find the ROIs with symmetrical texture and these symmetric ROIs can be regarded as pairs of lamps. The experimental results show that the proposed method can effectively deal with various illumination conditions and improve the accuracy and robustness of vehicle detection. In addition, this method can perform vehicle detection and tracking under complex traffic conditions and the Gabor filter based symmetry analysis can successfully suppress subtle difference between the left and right parts of a vehicle as well as environment noises.

关键词： Vehicles Image color analysis Vehicle detection Gabor filters Correlation Tracking Kalman filters

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Low frequency positive real control for delta operator systems

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Automatica 2012年第8期48卷 1791-1795页

作者： Hongjiu Yang Yuanqing Xia School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 China Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 China

A strictly positive real control problem for delta operator systems in a low frequency range is presented by using the generalized Kalman–Yakubovic˘–Popov lemma. The objective of the strictly positive real control problem is to design a controller such that the transfer function is strictly positive real and the resulting closed-loop system is stable. Sufficient conditions for the low frequency strictly positive real controller of the closed-loop delta operator systems are presented in terms of solutions to a set of linear matrix inequalities. A numerical example is given to illustrate the effectiveness and potential for the developed techniques.

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A Quantitative Performance Evaluation Index for Image Fusion: Normalized Perception Mutual Information

A Quantitative Performance Evaluation Index for Image Fusion...

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Chinese control Conference

作者： Liping Yan Yulei Liu Bo Xiao Yuanqing Xia Mengyin Fu School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781467325813

Information entropy based criteria are analyzed and the Normalized Mutual Information(NMI) that is presented in the field of image registration is revised to Normalized Mutual Information Entropy (NMIE) to meet the need of the evaluation of image fusion algorithms, Then, through analysis to NMIE and some human perception based criteria, and by analyzing the essence of image fusion techniques systematically, a new index, Normalized Perception Mutual Information (NPMI), is defined in view of information transmission as well as edge preservation, and is used to evaluate the performance of image fusion algorithms, The experiments are done to three groups of images, namely, the remote sensing images corrupted by noises, the multifocus images and the medical images obtained by CT and MRI, respectively. Compared with other indices including the root mean square error (RMSE), space frequncy (SF), space visibility (SV), entropy, the collective cross entropy (CCE), information deviation (ID), and the edge information preservation value (EIPV), etc., NPMI is shown to be the only one that is effective in all the eases in the evaluation of the performances of the fused images or the image fusion algorithms, which illustrates the feasibility and effectiveness of the presented algorithm.

关键词： Image fusion Performance evaluation Mutual information Human perception Normalized perception mutual intonation

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Optimized model reference adaptive motion control of robot arms with finite time tracking

Optimized model reference adaptive motion control of robot a...

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Chinese control Conference (CCC)

作者： Chenguang Yang Hongbin Ma Mengyin Fu Alex M. Smith School of Computing and Mathematics University of Plymouth Plymouth UK Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology BIT Beijing China

ISBN: (纸本)9781467325813

In this paper, we study motion control of general n degrees of freedom (DOFs) rigid robot arms. Aiming at shaping the controlled closed-loop dynamics to be of minimized motion tracking errors and as well as angular accelerations, we employ the linear quadratic regulation (LQR) optimization technique to obtain an optimal reference model. Adaptive control is then developed to ensure that the reference model can be matched in finite time, in the presence of various uncertainties. The stability and optimal tracking performance have been rigorously established by theoretic analysis.

关键词： Adaptation models Tracking Impedance Manipulators Adaptive control Force

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Application of fuzzy PID controlling technique in downhole power supply

Application of fuzzy PID controlling technique in downhole p...

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31st Chinese control Conference, CCC 2012

作者： Xinchao, Zhang Pengfeng, Li Hongxin, Chen Zengguang, Hou State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China CNOOC Research Institute Beijing 100025 China

ISBN: (纸本)9789881563811

This paper presents a novel downhole power supply control system using fuzzy PID control strategy. The control system is powered by a downhole turbine generator which generates AC voltage. The output of the turbine generator is processed through a full wave bridge rectifier and filter, and then input to the phase-shifted full-bridge PWM controller. A digital signal processor TMS320F2809 is used as the main control unit of the regulator control module. In order to verify the effectiveness of this system, a fuzzy proportion integration differentiation (F-PID) controller is used to control the phase-shifted full-bridge switching power supply, and the results presented that the controller can ensure the stability for power supply. © 2012 Chinese Assoc of Automati.

关键词： Fuzzy control

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design and implementation of a wireless video sensor network

Design and implementation of a wireless video sensor network

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IEEE International Conference on Networking, Sensing and control

作者： Bin Tian Xue-Liang Zhao Qing-Ming Yao Lei Zha State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Jiangsu China Sciences Intelligent Engineering Company Limited Suzhou China

As a new research field in wireless sensor network (WSN), wireless video sensor network (WVSN) makes surveillance multifunctional and intelligent, with rich and intuitive sensing information. It attracts more and more researchers' attention. We design and implement a wireless video sensor network prototype system, using WIFI as the wireless communication solution and CMOS video camera as the front-end sensor. The wireless video node adopts ARM11 based embedded platform. As back-end processing algorithm, the node realizes moving object detection. Finally, we verify the sensor network system. WIFI network can transmit video sequences smoothly. The moving object detection algorithm performs well.

关键词： Wireless communication Wireless sensor networks IEEE 802.11 Standards Object detection Program processors CMOS integrated circuits Cameras

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