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作者： Li, Zhiping Chen, Jie Gan, Minggang Fang, Hao Zhang, Guozhu Beijing Institute of Technology and Education Ministry Key Laboratory of Complex Systems Intelligent Control and Decision School of Automation Beijing China

ISBN: (纸本)9781424474264

This paper presents an adaptive robust dynamic surface control (ARDSC) algorithm for the position control of DC torque motors which are modeled as third-order nonlinear systems with parametric and nonlinear uncertainties. Based on the dynamic surface control (DSC) approach, the "explosion of terms" problem in the normal adaptive robust control (ARC) is avoided, which enhances the practicability of the controller. Furthermore, besides theoretically proving that the tracking error is uniformly ultimate bounded or asymptotically converge to zero in presence of parametric uncertainties only, the true estimates of the unknown parameters are achieved by designing a novel adaptation law, which improves the system performance and can be used in system monitor and diagnosis on-line as byproducts. Finally, the comparative simulation results illustrate that the proposed algorithm is very effective. © 2010 AACC.

关键词： Position control

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Automatic construction of domain theory for attack planning

Automatic construction of domain theory for attack planning

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2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security, ISI 2010

作者： Li, Xiaochen Mao, Wenji Zeng, Daniel Wang, Fei-Yue Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona Tucson AZ United States

ISBN: (纸本)9781424464609

Terrorism organizations are devising increasingly sophisticated plans to conduct attacks. The ability of emulating or constructing attack plans by potential terrorists can help us understand the intents and motivation behind terrorism activities. A feasible computational method to construct plans is planning technique in AI. Traditionally, AI planning methods rely on a predefined domain theory which is compiled by domain experts manually. To facilitate domain theory construction and plan generation, we propose a method to construct domain theory automatically from free text data. The effectiveness of our proposed approach is evaluated empirically through experimental studies using real world terrorist plans . © 2010 IEEE.

关键词： Terrorism

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带马尔科夫跳的模态相关时变时滞随机系统的状态反馈控制器设计(英文)

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自动化学报 2010年第11期36卷 1601-1610页

作者：马莉达飞鹏吴凌尧 Key Laboratory of Measurement and Control for Complex Systems of Engineering Ministry of EducationResearch Institute of AutomationSoutheast University College of Electronic and Information Engineering Jiangsu University

In this paper,an improved mean-square exponential stability condition and delayed-state-feedback controller for stochastic Markovian jump systems with mode-dependent time-varying state delays are obtained. First,by constructing a modified Lyapunov-Krasovskii functional,a mean-square exponential stability condition for the above systems is presented in terms of linear matrix inequalities (LMIs). Here,the decay rate can be a finite positive constant in a range and the derivative of time-varying delays is only required to have an upper bound which is not required to be less than 1. Then,based on the proposed stability condition,a delayed-state-feedback controller is designed. Finally,numerical examples are presented to illustrate the effectiveness of the theoretical results.

关键词：马尔科夫跳模态相关时变时滞随机系统状态反馈控制器

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Story extraction from the Web: A case study in security informatics

Story extraction from the Web: A case study in security info...

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2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010

作者： Ge, Ansheng Mao, Wenji Zeng, Daniel Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Management Information Systems University of Arizona Tucson AZ 85721 United States

ISBN: (纸本)9781424471188

Open source intelligence is becoming more and more important in security-related applications. Effective extraction of valuable information from these intelligence sources so as to understand the content of intelligence is one of the central issues in security domain. To address this key problem, this paper studies how to extract domain events and generate story representation of the events. We implement a story extraction platform (SEP) which applies pattern matching to extract events from Web news and organizes events based on theme using narrative structure. We also design extraction rules, use domain- specific features and employ ontology to facilitate story extraction in SEP. The experimental results show the effectiveness of our system in security informatics. © 2010 IEEE.

关键词： Extraction

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Employing cost-sensitive learning in cultural modeling

Employing cost-sensitive learning in cultural modeling

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2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010

作者： Su, Peng Mao, Wenji Zeng, Daniel Wang, Fei-Yue Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Management Engineering Shandong Lianzhu University Shandong 250101 China Department of Management Information Systems University of Arizona Tucson AZ 85721 United States

ISBN: (纸本)9781424471188

Cultural modeling aims at developing behavioral models of groups and analyzing the impact of culture factors on group behavior using computational methods. Machine learning methods in particular classification, play a central role in such applications. In modeling cultural data, it is expected that standard classifiers yield good performance under the assumptions that class distribution is balanced and different classification errors have uniform costs. However, these assumptions are often violated in practice and thus the performance of standard classifiers is severely hindered. To handle this problem, this paper studies cost-sensitive learning in cultural modeling domain by considering cost factor when building the classifiers, with the aim of minimizing total misclassification costs. We empirically investigate four typical cost-sensitive learning methods, combine them with six standard classifiers and evaluate their performances under various conditions. Our empirical study verifies the effectiveness of cost-sensitive learning in cultural modeling. Based on the results of our experimental study, we gain a thorough insight into the problem of class imbalance and non-uniform misclassification costs, as well as the selection of cost-sensitive methods, base classifiers and method-classifier pairs for this domain. © 2010 IEEE.

关键词： Costs

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A target tracking algorithm based on mean shift and normalized moment of inertia feature

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Zidonghua Xuebao/Acta Automatica Sinica 2010年第9期36卷 1332-1336页

作者： Gan, Ming-Gang Chen, Jie Wang, Ya-Nan Jin, Dai-Zhong School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex Systems Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China

The paper presents a target tracking algorithm which is based on the mean shift algorithm and the normalized moment of inertia (NMI) feature, because the result of the moving target tracking in the air is not satisfactory by the traditional mean shift tracking algorithm. The NMI feature of the target is introduced, and the studied tracking strategy based on the minimum principle of the false alarm probability and the two-stage decision threshold of the similarity is constructed in the algorithm. The Kalman filter is used for the estimation and prediction when the target is occluded. The experimental results show that with the algorithm even the moving target in the air is in large deformation and occlusion, the system can effectively guarantee that the tracking is real-time and stable. Copyright © 2010 Acta Automatica Sinica. All rights reserved.

关键词： Kalman filters

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Related topic network

Related topic network

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2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010

作者： Chang, Chao Zeng, Daniel Zhao, Huimin Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona United States Sheldon B. Lubar School of Business University of Wisconsin Milwaukee United States

ISBN: (纸本)9781424471188

Topic Detection and Tracking provides a flat and unorganized view of a document collection and cannot adequately reflect the content of the complete collection as some of the information is lost in the process. Topic models account for more information and lead to a more organized view of the document collection. In this paper, we propose a more efficient model named Related Topic Network with a new term weighting method. Empirical evaluation using two real-world datasets consisting of 953 and 5,550 news documents demonstrates the utility of the proposed model and shows that the new term weighting method leads to performance improvement. copy;2010 IEEE.

关键词： Related topic network Topic detection and tracking Topic model

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Variable structure neural network adaptive robust control

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Zidonghua Xuebao/ Acta Automatica Sinica 2010年第1期36卷 174-178页

作者： Chen, Jie Li, Zhi-Ping Zhang, Guo-Zhu School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex Systems Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

A variable structure neural network adaptive robust control (VSNNARC) is proposed for a class of uncertain nonlinear SISO systems. A neural network which is adjusted by using nodes activation and passivation techniques to minish the size of the neural network and computation load is used as an opproximator for the system unknown nonlinear functions. And the adaptive robust control is used for the weight learning and compensation to the modeling error and extern disturbances. The adaptation law of neural networks weights and the design method of robust controller are given out based on the Lyapunov stability analysis. Furthermore, the proposed controller can guarantee not only global stability but also transient performance. Finally, the controller is applied to a position tracking system of a turntable. The experimental results show that the system can perform good tracking and has strong robustness. © 2010 Acta Automatica Sinica. All rights reserved.

关键词： controllers

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Adaptive robust dynamic surface control of DC torque motors with true parameter estimates

Adaptive robust dynamic surface control of DC torque motors ...

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American control Conference

作者： Zhiping Li Jie Chen Minggang Gan Hao Fang Guozhu Zhang School of Automation Beijing Institute of Technology and Education Ministry Key Laboratory of Complex Systems Intelligent Control and Decision Beijing China

ISBN: (纸本)9781424474264

关键词： torque motors Position control System performance Parametric Unknown parameter asymptotic Self tuning

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Limited-memory-BFGS-based iterative algorithm for multispectral bioluminescence tomography with Huber regularization

Limited-memory-BFGS-based iterative algorithm for multispect...

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Medical Imaging 2010 - Biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Feng, Jinchao Jia, Kebin Tian, Jie Qin, Chenghu Zhu, Shouping College of Electronic Information and Control Engineering Beijing University of Technology Beijing 100022 China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences P. O. Box 2728 Beijing 100190 China Life Science Research Center Xidian University Xi'an 710071 China

ISBN: (纸本)9780819480279

Multispectral bioluminescence tomography is becoming a promising tool because it can resolve the biodistibution of bioluminescent reporters associated with cellular and subcellular function through several millimeters with to centimeters of tissues in vivo. Generally, to recover the bioluminescent sources, the source reconstruction problem is formulated as a nonlinear least-squares-type bounds constrained optimization problem. However, bioluminescence tomography (BLT) is an ill-posed problem. For the sake of stability and uniqueness of BLT, many algorithms have been proposed to regularize the problem, such as L2 norm and L1 norm. Here, we proposed a new regularization method with Huber function to regularize BLT problem to obtain robustness like L1 and rapid convergence of L 2. Furthermore, the computational burden is largely increased with the use of spectral data. Therefore, there is a critical need to develop a fast reconstruction algorithm for solving multispectral bioluminescence tomography. In the paper, a limited memory quasi-Newton algorithm for solving the large-scale optimization problem is proposed to fast localize the bioluminescent source. In the numerical simulation, a heterogeneous phantom was used to evaluate the performance of the proposed algorithm with the Monte Carlo based synthetic data. Additionally, the real mouse experiments were conducted to further evaluate the proposed algorithm. The results demonstrate the potential and merits of the proposed algorithm. © 2010 Copyright SPIE - The International Society for Optical Engineering.

关键词： Constrained optimization

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