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IEEE International Conference on Networking, Sensing and control

作者： Yegan Qian Gang Xiong Yanjie Yao Anhui Radio TV Station Hefei Hanteng Information Tech Company Hefei Anhui China 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

The paper discusses two important classification techniques, Fisher's linear discriminated analysis (FLDA) and Support Vector Machine (SVM). First, we propose a theoretical discussion, and then implement FLDA and SVM on several datasets of two classes and multiclass, a comparative experimental analysis among these two techniques aims at exploring and assessing the performance of FLDA and SVM classifiers. To sustain such analysis, the two classification techniques are compared with different training data sets and testing data sets. Different performance indicators have been used to support our experimental studies in a detailed and accurate way such as the classification accuracy. The results obtained on different datasets conclude that FLDA and SVM are valid and effective approaches for pattern classification and conclude their different performance and problems with different size datasets. Meanwhile, the paper employs a non-traditional method to get the training and testing data set, and concludes detailed pros and cons from the experiment results.

关键词： Support vector machines Training Testing Accuracy Vectors Head Magnetic heads

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Stability Analysis for High Frequency Networked control systems

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IEEE Transactions on Automatic control 2012年第10期57卷 2694-2700页

作者： Hongjiu Yang Yuanqing Xia Peng Shi Mengyin Fu Institute of Electrical Engineering Yanshan University Qinhuangdao China School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China School of Engineering and Science Victoria University Melbourne VIC Australia Department of Computing and Mathematical Sciences University of Glamorgan Pontypridd UK

This note generalizes the stability analysis for a high frequency networked control system. The high-frequency networked control system is described by a delta operator system with a high frequency constraint. Stability conditions are given for the high frequency delta operator system. Furthermore, by developing the generalized Kalman-Yakubovic-Popov lemma, improved stability conditions are also presented in terms of linear matrix inequalities. Some experiment results are presented to illustrate the effectiveness of the developed techniques.

关键词： Stability analysis Delay Linear matrix inequalities Frequency control Educational institutions Power system stability Numerical stability

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ACP based 3D Emergency Drills System for Petrochemical Plants

ACP based 3D Emergency Drills System for Petrochemical Plant...

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World Congress on intelligent control and automation

作者： Sifeng Jing Changjian Cheng Gang Xiong Xiwei Liu Xiuqin Shang Weixing 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 Dongguan Research Institute of CASIA Cloud Computing Industrial Technology Innovation and Incubation Center Chinese Academy of Sciences

ISBN: (纸本)9781467313971

To further enhance emergency management skills of an organisation's emergency response personnel, emergency response training, especially 3D emergency drill, is currently becoming more and more important in the petrochemical sector. So, a novel 3D emergency drills system is designed and developed based on ACP approach, which can be used for mocking emergency response plan drills and evaluating the plan. A case study reveals that the performance of the system is good and the system can meet the needs of emergency response training and optimizing emergency response plan in petrochemical plants.

关键词： ACP Approach Artificial systems Computational Experiments Parallel Execution Mock-Drill Emergency Response Training

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An Embedded Co-AdaBoost and Its Application in Classification of Software Document Relation

An Embedded Co-AdaBoost and Its Application in Classificatio...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Jin Liu Juan Li Yuan Xie Jeff Lei Qiping Hu State Key Laboratory of Software Engineering Computer School Wuhan University China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation CAS China Department of Computer Science and Engineering University of Texas Arlington USA International School of Software Wuhan University China

To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learning into the Adaboost learning framework and at the same time leverages the advantages of Co-training algorithm for performance enhancement. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of the convergence rate, the accuracy, and the steady performance as compared to the original AdaBoost algorithm, without relying on redundant and sufficient feature sets. As a algorithm application in software engineering, the Embedded Co-AdaBoost has been applied to the classification of software document relations to improve the quality of the architecture design documents and the reusability of design knowledge.

关键词： Classification algorithms Training Software Accuracy Partitioning algorithms Software algorithms Convergence

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Adaptive control with Nearest-neighbor Previous Instant Compensation for Discrete-time Nonlinear Strict-feedback systems

Adaptive Control with Nearest-neighbor Previous Instant Comp...

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American control Conference

作者： Chenguang Yang Hongbin Ma Bin Xu Mengyin Fu School of Computing and Mathematics the University of Plymouth UK PL4 8AA Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China 100081 School of Automation Northwestern Polytechnical University Xi'an China 710072

ISBN: (纸本)9781457710957

Many nonlinear systems can be modeled by or converted to strict-feedback forms, whose stabilization problem without modeling uncertainties has been extensively discussed in the literature. However, in practice, inevitable modeling uncertainties, especially co-existence of parametric uncertainties and nonparametric uncertainties, will make it very difficult and challenging to achieve desirable control performance. In this background, we consider a challenging adaptive control problem, aiming at asymptotic tracking to any bounded reference signal, in the presence of periodic uncertainties of both parametric and nonparametric types, i.e., periodic time-varying parameters and periodic unknown time-delays in the uncertain nonlinearities, for a class of strict-feedback discrete-time nonlinear systems due to the lack of related research and the increasing demand of digital control in current epoch. To deal with the co-existing various uncertainties, which bring highly-nonlinear coupled effects to the closed-loop system, a novel nearest-neighbor previous instant compensation technique, combined with the lifting approach and the future states prediction, is introduced in this paper to asymptotically fully compensate the effects of uncertainties. With such elaborately constructed adaptive estimation mechanism, the developed discrete-time backstepping adaptive controller can guarantee the closed-loop stability as well as asymptotic output tracking, which have been rigorously established and testified by extensive simulations.

关键词： adaptive control Uncertainty asymptotic tracking discrete-time Nearest neighbor Reference signals Parametric instant control performance Numerical controls compensated

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Fitting a Functional Structural Plant Model based on Global Sensitivity Analysis

Fitting a Functional Structural Plant Model based on Global ...

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IEEE International Conference on automation Science and Engineering

作者： Yubin LIN Mengzhen KANG Jing HUA National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences 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

ISBN: (纸本)9781467304290

Calibration of a functional structural plant model is a challenging task because of the complexity of model structure. Parameter estimation through gradient-based optimization technique was highly dependent on initial parameter values. This motivated the use of global sensitivity analysis technique to choose parameter subset in fitting the data sequence. Global sensitivity indices were computed using the source sink ratio as the output of interest, which regulates all organ growth. By fitting on chrysanthemum data from nine sampling dates, it is shown that sensitivity analysts method helps to identify the influential parameters for a given sampling date. As a result, fitting process is less dependent on the initial parameter values. Current work provides a new method of calibrating a plant growth model with multiple outputs.

关键词： Sensitivity analysis plant models organ growth MACHINE SHOP PRACTICE

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Mobile sensor network node deployment via Central Voronoi Tessellation

Mobile sensor network node deployment via Central Voronoi Te...

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International Conference on intelligent control and Information Processing

作者： Xiong, R. Bai, Y.Q. Sun, W. Liu, X. Key Laboratory of Complex Systems Intelligent Control and Decision School of Automation Ministry of Education Beijing 100081 China

ISBN: (纸本)9781457708145

The present work focuses on the node deployment algorithm of Wireless Sensor Networks. The Central Voronoi Tessellation algorithm is employed to optimize the node position. The energy consumption of the whole sensor network will be minimized by using this algorithm. Simulation of the proposed algorithm shows the effectiveness of minimizing the energy consumption. © 2011 IEEE.

关键词： Energy utilization

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A multi-target tracking approach combined with occlusion segmentation

A multi-target tracking approach combined with occlusion seg...

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4th International Workshop on advanced Computational Intelligence, IWACI 2011

作者： Ding, Huan Zhang, Wensheng State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781612843735

Multiple-target tracking in complex scenes is one of the most complicated problems in computer vision. Handling the occlusion between objects is the key issue in multiple target tracking. This paper presents an occlusion segmentation-based method to track multiple people in complex situations which are captured by static monocular cameras. In the proposed method, we calculate the probabilistic histogram of each object's optical flow vector, then use this motion statistic information along with the color and appearance information to construct a new expression of pixel distance. Finally, a stepwise classification and K-means clustering method are taken advantages of to accomplish occlusion segmentation. Object tracking is handled by a particle filter-based tracking framework, and a probabilistic appearance model is used to find the best particle. Experiments are conducted using public challenging data set PETS 2009. Results show that our approach can improve the performance of the existing tracking approach and handle dynamic occlusions better. © 2011 IEEE.

关键词： Clutter (information theory)

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Sensor fault diagnosis based on least squares support vector machine online prediction

Sensor fault diagnosis based on least squares support vector...

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2011 IEEE 5th International Conference on Robotics, automation and Mechatronics, RAM 2011

作者： Lishuang, Xu Tao, Cai Fang, Deng School of Automation Beijing Institute of Technology Key Laboratory of Complex Systems Intelligent Control and Decision Beijing 100081 China

ISBN: (纸本)9781612842509

In order to solve the challenging problem of diagnosis for sensor bias and drift faults, a method of sensor fault diagnosis based on the least squares support vector machine (LS-SVM) online prediction is proposed. In the paper, the real-time outputs of the sensor are made full use to establish LS-SVM prediction model. Through the residual which is obtained by comparing the outputs of LS-SVM prediction model and the actual output of the sensor, the real-time detection of the sensor faults can be achieved. Based on the residual sequence, the on-line identification of sensor bias fault and drift fault can be achieved as well. A model of sensor faults is established by the toolbox of matlab simulink in this paper, the simulation results show that the approach proposed can not only improve the accuracy and time efficiency of fault diagnosis, but also identify the type, size and the time of sensor faults occurred accurately. © 2011 IEEE.

关键词： Failure analysis

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The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine

The research of sensor fault diagnosis based on genetic algo...

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International Conference on intelligent control and Information Processing (ICICIP)

作者： Xu, Lishuang Cai, Tao Deng, Fang Liu, Xin School of Automation Beijing Institute of Technology Key Laboratory of Complex Systems Intelligent Control and Decision Beijing 100081 China

ISBN: (纸本)9781457708145

Fault diagnosis based on the wavelet packet decomposition, one-against-one support vector machine (SVM) and genetic algorithm (GA) is proposed in order to realize the real-time sensor fault diagnosis accurately. The input feature vectors of one-against-one SVM are produced by wavelet packet decomposition of the sensor output signal. GA is used to obtain optimal parameters of one-against-one SVM network model automatically, which can enhance the training speed and performance. The experiments of photoelectric encoder fault diagnosis show that the combination of these methods makes SVM own a better recognition rate and overall performance, which can improve the accuracy and time efficiency of fault diagnosis. © 2011 IEEE.

关键词： Failure analysis

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