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2016 IEEE International Conference on Fuzzy systems, FUZZ-IEEE 2016

作者： Wang, Shenquan Jiang, Yulian Li, Yuanchun Liu, Derong College of Electrical and Electronic Engineering Changchun University of Technology Changchun130012 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9781509006250

This paper is concerned with the reliable H control problem for discrete-time Takagi-Sugeno (T-S) fuzzy systems with time-varying delays and stochastic actuator faults based on a novel summation inequality. A discrete-time homogeneous Markov chain is used to represent the stochastic behavior of actuator faults. By employing a fuzzy basis-dependent Lyapunov functional and the novel summation inequality, an improved sufficient condition is established to ensure that the resultant closedloop system is stochastically stable with an H performance index. Meanwhile, the solvability condition for the reliable H control is also established, by which the reliable H fuzzy controller can be solved from linear matrix inequalities. A numerical example is provided to demonstrate the effectiveness of the present approach. © 2016 IEEE.

关键词： Linear matrix inequalities

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Competitive perspective identification via topic based refinement for online documents

Competitive perspective identification via topic based refin...

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Junjie Lin Wenji Mao Daniel Zeng State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences

ISBN: (纸本)9781509038664

People write online documents from different personal perspectives. The competitive perspectives they hold reflect the conflicts in their fundamental stances and viewpoints. For many security-related applications, it is both beneficial and critical to identify the competitive perspectives implied in online documents. Previous work on competitive perspective identification is based on word features, which did not consider that the word usage for perspective expression varies with topics in documents. Thus topic information can be incorporated and contribute to a more fine-grained treatment of perspective identification. Motivated by this, this paper proposes an approach for competitive perspective identification in online documents via topic based refinement. Our approach refines the basic word feature-based perspective identification model with latent semantic information. In addition, we develop a self-adaptive process to fit the model parameters automatically. Experimental study shows the effectiveness of our approach compared to the related work and the baseline methods.

关键词： Mathematical model Training Support vector machines Semantics Fitting Optimization Testing

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Scene-specific pedestrian detection based on parallel vision

arXiv

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arXiv 2017年

作者： Zhang, Wenwen Wang, Kunfeng Qu, Hua Zhao, Jihong Wang, Fei-Yue School of Software Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Communication and Information Engineering Xi’an Jiaotong University Xi’an710049 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

As a special type of object detection, pedestrian detection in generic scenes has made a significant progress trained with large amounts of labeled training data manually. While the models trained with generic dataset work bad when they are directly used in specific scenes. With special viewpoints, flow light and backgrounds, datasets from specific scenes are much different from the datasets from generic scenes. In order to make the generic scene pedestrian detectors work well in specific scenes, the labeled data from specific scenes are needed to adapt the models to the specific scenes. While labeling the data manually spends much time and money, especially for specific scenes, each time with a new specific scene, large amounts of images must be labeled. What’s more, the labeling information is not so accurate in the pixels manually and different people make different labeling information. In this paper, we propose an ACP-based method, with augmented reality’s help, we build the virtual world of specific scenes, and make people walking in the virtual scenes where it is possible for them to appear to solve this problem of lacking labeled data and the results show that data from virtual world is helpful to adapt generic pedestrian detectors to specific scenes. Copyright © 2017, The Authors. All rights reserved.

关键词： Virtual reality

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Application of Hilbert-Huang decomposition to reduce noise and characterize for NMR FID signal of proton precession magnetometer

arXiv

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arXiv 2017年

作者： Huan, Liu Haobin, Dong Liu, Zheng Ge, Jian Bai, Bingjie Zhang, Cheng School of Automation China University of Geosciences Hubei Wuhan430074 China School of Engineering University of British Columbia Okanagan Campus KelownaBCV1X 1V7 Canada Institute of Geophysics and Geomatics China University of Geosciences Hubei Wuhan430074 China Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Hubei Wuhan430074

The parameters in a nuclear magnetic resonance (NMR) free induction decay (FID) signal contain information that is useful in magnetic field measurement, magnetic resonance sounding (MRS) and other related applications. A real time sampled FID signal is well modeled as a finite mixture of exponential sequences plus noise. We propose to use the Hilbert-Huang Transform (HHT) for noise reduction and characterization, where the generalized Hilbert-Huang represents a way to decompose a signal into so-called intrinsic mode function (IMF) along with a trend, and obtain instantaneous frequency data. Moreover, the HHT for an FID signal's feature analysis is applied for the first time. First, acquiring the actual untuned FID signal by a developed prototype of proton magnetometer, and then the empirical mode decomposition (EMD) is performed to decompose the noise and original FID. Finally, the HHT is applied to the obtained IMFs to extract the Hilbert energy spectrum, to indicate the energy distribution of the signal on the frequency axis. By theory analysis and the testing of an actual FID signal, the results show that, compared with general noise reduction methods such as auto correlation and singular value decomposition (SVD), combined with the proposed method can further suppress the interfered signals effectively, and can obtain different components of FID signal, which can use to identify the magnetic anomaly, the existence of groundwater etc. This is a very important property since it can be exploited to separate the FID signal from noise and to estimate exponential sequence parameters of FID signal. Copyright © 2017, The Authors. All rights reserved.

关键词： Singular value decomposition

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A Geometric Extension Design for Second-Order Nonlinear Agents Formation Surrounding a Sphere

A Geometric Extension Design for Second-Order Nonlinear Agen...

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第28届中国控制与决策会议

作者： Yang-Yang Chen Kai-Xuan Wang Ya Zhang Cheng-Lin Liu Qin Wang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University Chien-Shiung Wu College Southeast University Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan University College of information engineering Yangzhou University

ISBN: (纸本)9781467397155

This article deals with the problem of driving a family of second-order nonlinear agents to land on a sphere and formation tracking a set of given orbits on the sphere.A novel geometric extension called the concentric compression method is proposed to give a solution to spheral landing and then combines with the control of spherical meridian and parallel to achieve formation motion along given orbits on the *** asymptotic stability of system is proved by Lyapunov-based method when the communication topology is *** effectiveness of the analytical result is verified by a numerical simulation.

关键词： Formation tracking Sphere landing Geometric Extension Second-Order Nonlinear Agents

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A General Adaptive Dynamic Programming Approach with Experience Replay

A General Adaptive Dynamic Programming Approach with Experie...

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International Joint Conference on Neural Networks

作者： Bin Wang Dongbin Zhao Jin Cheng Yuan Xu Yueyang Li School of Electrical Engineering University of Jinan The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781509006212

Experience replay is a promising approach to improve the learning efficiency of adaptive dynamic programming. A general model-free adaptive dynamic programming (ADP) approach with the experience replay technology is investigated in this paper to solve the optimal control problems in continuous state and action spaces. Both the critic network and action network are modeled with a feedforward neural network with one hidden layer. During the learning process, a number of recently observed data samples are recorded in a database. When updating the parameters of the neural networks, the data in the sample database are repeatedly used to update the weights of the action network and the critic network. Implementation details of the algorithm are given, and simulation experiments are utilized to verify the learning efficiency of the proposed approach.

关键词： Erbium Dynamic programming Neural networks Databases Optimal control Heuristic algorithms Approximation algorithms

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Steps toward Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2016年第4期3卷 345-348页

作者： Fei-Yue Wang Xiao Wang Lingxi Li Li Li IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) Research Center of Computational Experiments and Parallel Systems the National University of Defense Technology Qingdao Academy of Intelligent Industries (QAII) QingdaoShandongChinaand SKL-MCCSCASIA Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis Department of Automation Tsinghua University Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies

The origin of artificial intelligence is investigated, based on which the concepts of hybrid intelligence and parallel intelligence are presented. The paradigm shift in Intelligence indicates the ''new normal'' of cyber-social-physical systems (CPSS), in which the system behaviors are guided by Merton's Laws. Thus, the ACP-based parallel intelligence consisting of Artificial societies, Computational experiments and Parallel execution are introduced to bridge the big modeling gap in CPSS. © 2014 Chinese Association of Automation.

关键词： control systems Electrical engineering

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A novel policy iteration based deterministic Q-learning for discrete-time nonlinear systems

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Science China(Information Sciences) 2015年第12期58卷 147-161页

作者： WEI QingLai LIU DeRong State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing

In this paper, a novel iterative Q-learning algorithm, called "policy iteration based deterministic Qlearning algorithm", is developed to solve the optimal control problems for discrete-time deterministic nonlinear systems. The idea is to use an iterative adaptive dynamic programming(ADP) technique to construct the iterative control law which optimizes the iterative Q function. When the optimal Q function is obtained, the optimal control law can be achieved by directly minimizing the optimal Q function, where the mathematical model of the system is not necessary. Convergence property is analyzed to show that the iterative Q function is monotonically non-increasing and converges to the solution of the optimality equation. It is also proven that any of the iterative control laws is a stable control law. Neural networks are employed to implement the policy iteration based deterministic Q-learning algorithm, by approximating the iterative Q function and the iterative control law, respectively. Finally, two simulation examples are presented to illustrate the performance of the developed algorithm.

关键词： adaptive critic designs adaptive dynamic programming approximate dynamic programming Q learning policy iteration neural networks nonlinear systems optimal control

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A double loop optimization method for gasoline online blending

A double loop optimization method for gasoline online blendi...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Weiheng Chen Jun Yang School of Information Science and Engineering Southeast University Nanjing P. R. China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing P. R. China

ISBN: (纸本)9781467380768

Direct-blending component oils bring great disturbance to the online gasoline blending control. A double loop optimization strategy with nested outer and inner loops is proposed, and the optimization strategy combined with a case study is illustrated in detail in this paper. The real industry application demonstrates that this new optimization strategy can not only take account of the bottom oil's properties deviation, but also timely detect the fluctuation of gasoline properties from the direct-blending oils. In this way, the final gasoline product properties can be controlled quite well at one time, and the re-blending times of final product have been much reduced compared with the conventional single loop optimization method.

关键词： Petroleum Oils Optimization methods Fluctuations Standards Production

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Boosting-Based One-Class SVM for Recognizing True-Fake Chinese Liquors Using Electronic Noses

Boosting-Based One-Class SVM for Recognizing True-Fake Chine...

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World Congress on Intelligent control and Automation

作者： Zhi-Hua Li Qing-Hao Meng Pei-Feng Qi Yu Zhou Shu-Gen Ma Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems Tianjin University Department of Robotics College of Science and Engineering Ritsumeikan University

ISBN: (纸本)9781467384155

The true-fake detection of Chinese liquors can be considered as a one-class classification problem. Using only positive sample in training process brings about difficulties in determining the optimal parameters of one-class SVM and its kernel. And one-class SVM optimized with conventional grid search method has a low recognition rate of positive test samples. Hence, we proposed a new idea for recognition, namely boosting-based one-class SVM. Six different kinds of liquors were sampled by a self-designed electronic nose system. After the preprocessing and feature extraction of sample data, 18 groups of optimum parameters of one-class SVM were chosen from specified parameter range, each group was used to train a classifier with training algorithm. Then the true-fake decisions were made for test samples with boosting integration rules. Finally the recognition rates of Hongjinjiu and Lanjinjiu positive sample reached 95.24% and 100%, and the recognition rates of both positive and negative sample reached 97.04% and 94.83%, respectively.

关键词： Support Vector Network optimal parameter Electronic Nose Recognition (Psychology) Search methods Chinese Chinese Chinese philosophy Chinese art Feature extraction test sample

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