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Chinese automation Congress (CAC)

作者： Mingfang Du Junzheng Wang Jing Li Haiqing Cao Guangtao Cui Jianjun Fang Ji Lv Xusheng Chen Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Automation School Beijing Union University Beijing China

The local invariant features SURF (Speeded Up Robust Features) is introduced into the robot visual recognition field to solve scale changes, rotation, perspective changes, changes in illumination and other problems. A Speeded up SURF (SSURF) algorithm is proposed to meet the needs of robot visual identification. In SSURF algorithms, the main direction determination step of SURF algorithm is modified which make the search scope of the main direction becomes {-α, +α} (0 ≤ α ≤ 30°) from the original scope 360 According to compressed sensing ideas and interest points distribution histogram, the main scale search space is selected to improve the interest points searching step of SURF algorithm, so the interest points searching time-consuming is reduced. Matching the sample object and the scene using SSURF descriptor, and positioning the target position in the scene and giving ROI(region of interest). Experimental results in the autonomous mobile robot platform show that the proposed method significantly improves the speed of the robot to identify the target object, and proved robust to the scale changes, rotation, perspective changes, changes in illumination.

关键词： Feature extraction Robots Object recognition Robustness Vectors Image recognition Visualization

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Distributed Flocking of Second-order Multi-agent systems with Global Connectivity Maintenance

Distributed Flocking of Second-order Multi-agent Systems wit...

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American control Conference

作者： Yutian Mao Lihua Dou Hao Fang Jie Chen Tao Cai School of Automation and Key Laboratory of Complex System Intelligent Control and Decision (Ministry of Education) Beijing Institute of Technology Beijing 100081 P.R.China

ISBN: (纸本)9781479901777

This paper investigates the problem of connectivity-preserving flocking of multiple autonomous agents with second-order dynamics. First, the inverse power iteration algorithm is formulated in a completely distributed manner to estimate the algebraic connectivity, i.e., the second smallest eigenvalue of the group Laplacian, as well as the corresponding eigenvector. Furthermore, distributed gradient-based flocking algorithms that exploit decentralized eigenvalue/eigenvector estimation are developed both to steer the agent group to the desired flocking motion and to maintain the global connectivity of the underlying network during maneuvers. Different from the common potential/tension function method which keeps certain fixed edges all the time, the algorithm proposed in this paper guarantees the global connectivity which allows any existing edge to be broken, thus gives more freedom of motions for the agents. Finally, nontrivial simulations are performed to demonstrate the correctness and effectiveness of the theoretical results.

关键词： underlying desired agents

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Differential Evolution Based Receding Horizon control for UAV Motion Planning in Dynamic Environments

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机器人 2013年第1期35卷 107-114页

作者： ZHANG Xing School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China Decision and Cognitive Sciences Research Centre Manchester Business School University of Manchester Manchester M15 6PB UK

This paper presents online motion planning for UAV(unmanned aerial vehicle) in complex threat field,including both static threats and moving threats,which can be formulated as a dynamic constrained optimal control *** horizon control(RHC) based on differential evolution(DE) algorithm is adopted.A location-predicting model of moving threats is established to assess the value of threat that UAV faces in *** flyable paths can be generated by the control inputs which are optimized by DE under the guidance of the objective *** results demonstrate that the proposed method not only generates smooth and flyable paths,but also enables UAV to avoid threats efficiently and arrive at destination safely.

关键词：无人机在线运动规划动态约束目标函数

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A unified optimization method for real-time trajectory generation of mobile robots with kinodynamic constraints in dynamic environment

A unified optimization method for real-time trajectory gener...

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IEEE Conference on Robotics, automation and Mechatronics

作者： Wenhao Luo Jun Peng Weirong Liu Jing Wang Wentao Yu Department of Automation Key Laboratory of System Control And Information Processing Shanghai China School of Information Science and Engineering Hunan Engineering Laboratory for Advanced Controland Intelligent Automation Changsha China Computer Engineering Program Bethune-Cookman University Daytona Beach FL USA

This paper presents an efficient analytic method for a mobile robot to determine a collision-free trajectory with unified optimization. The robot kinodynamic constraints and the geometric constraints due to obstacles are addressed by considering a set of constrained inequalities from parameterized trajectories model. Two optimal performance matrices are employed to assess optimization problems. Particularly, both the constraints and performance functions are incorporated by similar forms in terms of trajectory parameters, which thereby can be considered in a uniform way. A parameter space of adjustable trajectory parameters is constructed to solve the unified optimization problem with constraints and results in more flexible and better optimal performance. The proposed approach is complete and enhances methods of deterministic real-time planning by overcoming typical drawbacks as intermediate configuration, curvature discontinuities, vertical singularities and incomplete optimization. Simulation results verify the validity and superiority of the proposed method.

关键词： Trajectory Robot kinematics Collision avoidance Mobile robots Acceleration Optimization

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Dynamic image stabilization precision test system based on the Hessian matrix

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Science China(Information Sciences) 2012年第9期55卷 2056-2074页

作者： LI Jing ,WANG JunZheng,WANG ShouKun,MA LiLing & SHEN Wei key laboratory of complex system intelligent control and Decision,School of automation,Beijing Institute of Technology,Beijing 100081,China 1. Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing 100081 China

Dynamic image stabilization precision of an optical image-stable device is a key technical ***,a fast dynamic image stabilization precision test system for an optical image-stable device is developed.A large-aperture collimator with a designed cross divisional board is used to simulate the infinity *** image-stable device is installed on the motion simulator with six degrees of freedom which is used to simulate the moving state of the *** CCD camera installed behind the eyepiece lens of the image-stable device acquires images rapidly and in real *** local energy maxima center of the cross light spot can be acquired accurately through the proposed algorithm using the Hessian *** addition,to deal with the CCD non-uniformity,an adaptive non-uniformity correction algorithm based on bi-dimensional empirical mode decomposition is *** actual test results for the proposed method show that the test error of dynamic image stabilization is less than 0.7,and the time for the frame image acquisition and processing is less than 10 ms,which demonstrates the effectiveness of the test system.

关键词： image stabilization precision adaptive non-uniformity correction empirical mode decomposition local energy maxima Hessian matrix

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Hybrid dynamic model of polymer electrolyte membrane fuel cell stack using variable neural network

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Journal of Beijing Institute of Technology 2012年第3期21卷 354-361页

作者：李鹏陈杰蔡涛王光辉 School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of EducationBeijing Institute of Technology

The polymer electrolyte membrane（PEM） fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,which combines the advantages of mechanism model and black-box model,is proposed in this *** improve the performance,the static neural network and variable neural network are used to build the black-box *** static neural network can significantly improve the static performance of the hybrid model,and the variable neural network makes the hybrid dynamic model predict the real PEM fuel cell behavior with required ***,the hybrid dynamic model is validated with a 500 W PEM fuel *** static and transient experiment results show that the hybrid dynamic model can predict the behavior of the fuel cell stack accurately and therefore can be effectively utilized in practical application.

关键词： PEM fuel cell variable neural network hybrid dynamic model

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Unsupervised robust adaptive filtering against impulsive noise

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Journal of systems Engineering and Electronics 2012年第1期23卷 32-39页

作者： Tao Ma Jie Chen Wenjie Chen Zhihong Peng School of Automation Beijing Institute of Technology Beijing 100081 R R. China Key Laboratory of Complex System Intelligent Control and Decision （Ministry of Education） Beijing Institute of Technology Beijing 100081 P. R. China

An implementation of adaptive filtering, composed of an unsupervised adaptive filter （UAF）, a multi-step forward linear predictor （FLP）, and an unsupervised multi-step adaptive predictor （UMAP）, is built for suppressing impulsive noise in unknown circumstances. This filtering scheme, called unsupervised robust adaptive filter （URAF）, possesses a switching structure, which ensures the robustness against impulsive noise. The FLP is used to detect the possible impulsive noise added to the signal, if the signal is ＂impulse-free＂, the filter UAF can estimate the clean sig- nal. If there exists impulsive noise, the impulse corrupted samples are replaced by predicted ones from the FLP, and then the UMAP estimates the clean signal. Both the simulation and experimental results show that the URAF has a better rate of convergence than the most recent universal filter, and is effective to restrict large disturbance like impulsive noise when the universal filter fails.

关键词： adaptive filtering unsupervised form impulse insen- sitive switching structure.

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Probabilistic model based image retrieval using hypothesis testing

Probabilistic model based image retrieval using hypothesis t...

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International Conference on Information Engineering and Applications, IEA 2011

作者： Li, Bo Liu, Guoping School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education Beijing China Advanced Control and Network Technology Research Unit University of Glamorgan Glamorgan United Kingdom

ISBN: (纸本)9781447123859

The content based image retrieval (CBIR) is aimed to find the most similar images from a collection of images or a database to the query image according to the visual or semantic similarity. Current image retrieval algorithms mainly focus on feature selection and learning distance metric. Other methods are also proposed to promote the performance such as relevance feedback. But as a whole their performance still can not reach the expectation for application. This paper presents a new framework for image retrieval by introducing the hypothesis testing heory. The rest of this paper is organized as follows: Section II introduces the motivation of the proposed approach and the hypothesis testing problem in image retrieval. Section III is the main part of the paper and in this section the concepts of background model, image model, test ratio and feature extraction that compose the framework are introduced and discussed. Section IV shows the relevant experimental results of the algorithm. © 2012 Springer-Verlag London Limited.

关键词： Semantics

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Preliminary studies on word-cell and its properties

Preliminary studies on word-cell and its properties

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2012 International Conference on Technology and Management, ICTAM 2012

作者： Xiao, Zhi-Quan Mo, Hong School of Mechanical and Electrical Engineering Wuhan Textile University Wuhan Hubei China Key Laboratory of Complex System and Intelligent Science Institute of Automation Chinese Academic of Science Beijing China College of Electric and Information Changsha University of Science and Technology Changsha Hunan China

ISBN: (纸本)9783642296369

A new concept of word-cell is introduced. It evolves from the concepts of footprint of uncertainty (FOU) of interval type-2 fuzzy set and sets-as-points geometric view of fuzzy sets. The word-cell can be graphically illustrated in the fuzzy hypercube as certain type of an information granule. Based on the construction approach of word-cell, some properties are discussed. The further understanding of word-cell may help us to use fuzzy sets as linguistic terms (word) for the numerically studying of linguistic dynamic systems(LDS). © 2012 Springer-Verlag GmbH Berlin Heidelberg.

关键词： Cells

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Decentralized Valley-fill Charging control of Large-population Plug-in Electric Vehicles

Decentralized Valley-fill Charging Control of Large-populati...

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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Zhongjing Ma School of Automation Beijing Institute of Technology (BIT) and the Key Laboratory of Complex System Intelligent Control and Decision (BIT) Ministry of Education

Optimal charging control of large-population autonomous plug-in electric vehicles (PEVs) in power grid can be formulated as a class of constrained non-linear timevariant optimization problems. To overcome the computational complexity of this class of optimization problems, the author and his collaborators proposed a game-based decentralized control method such that individual agents update their best charging strategies simultaneously with respect to a common electricity price signal which is determined by the total demand in the grid. Due to the heterogeneity of individual PEVs, the game systems converge to a nearly valley-fill NE strategy with nontrivial deviation costs due to the heterogeneity property of individual PEV charging characteristics. In this paper the author proposed a novel algorithm to implement the optimal decentralized valley fill strategies for the charging problems of the PEV population which is composed of disjoint homogeneous subpopulations. The author introduces a cost which penalizes against the deviation of strategy of individual agent in a subpopulation from the average value of the subpopulation. It can be shown that in case that the update algorithm converges, the system reaches the optimal valley-fill equilibrium strategy where the introduced agent deviation cost vanishes. Simulation examples are used to illustrate the results developed in this paper.

关键词： Decentralized charging control Plug-in electric vehicles (PEVs) Valley-fill (VF) Nash equilibrium (NE)

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