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Fault detection and identification for a class of nonlinear systems with model uncertainty

Applied Mathematical Modelling 2016年第15-16期40卷 7368-7381页

作者： Bingyong Yan Housheng Su Wei Ma School of Automation Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology 130 Meilong Road Shanghai 200237 China School of Automation Key Laboratory of Image Processing and Intelligent Control of Ministry of Education of China Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory for Advanced Materials & Institute of Fine Chemicals East China University of Science and Technology 130 Meilong Road Shanghai 200237 China

In this paper, we present a novel fault detection and identification (FDI) scheme for a class of nonlinear systems with model uncertainty. At the heart of this approach is an on-line approximator, referred to as fault tracking approximator (FTA). Differently from the other approximators, the FTA uses iterative algorithms to detect and identify nonlinear system faults, even in the presence of model uncertainty, which is motivated by predictive control theory and iterative learning control theory. The FTA can simultaneously detect and identify the shape and magnitude of the faults. The rigorous stability analysis and fault tracking properties of the FTA are also proved. Finally, two examples are given to illustrate the feasibility and effectiveness of the proposed approach.

关键词： Fault detection and identification Predictive control Iterative learning control

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Mid-level parts mined by feature selection for action recognition 3

Mid-level parts mined by feature selection for action recogn...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Zhang, ShiWei Sang, Nong Gao, ChangXin Chen, FeiFei Hu, Jing Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology China

ISBN: (纸本)9781479961009

This paper develops a method to learn very few discriminative part detectors from training videos directly, for action recognition. We hold the opinion that being discriminative to action classification is of primary importance in selecting part detectors, not just intuitive. For this purpose, part selection based on feature selection is proposed, employing SVM method. Firstly, large number of candidate detectors are trained using k-means and Exemplar-LDA techniques in whitened feature space. Secondly, each candidate part detector is regarded as a visual feature, so that detector selection can be achieved by feature selection. Detectors with larger weight, indicating more discriminative, will be selected. Meanwhile, to keep space-volume structure information, we use the novel method saliency-driven pooling to form feature primitives which are concatenated into mid-level feature vector. Finally, we conduct experiments on three challenging action datasets (KTH, Olympic Sports, HMDB51) and the results outperform the state-of-the-art. © 2015 IEEE.

关键词： Feature Selection

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SAR image Despeckling Using Scale Mixtures of Gaussians in the Nonsubsampled Contourlet Domain

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Chinese Journal of Electronics 2015年第1期24卷 205-211页

作者： CHANG Xia JIAO Licheng LIU Fang SHA Yuheng Institute of Image Processing and Understanding School of Mathematics and Information Science Beifang University of Nationalities Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China International Research Center for Intelligent Perception and Computation Xidian University School of Computer Science and Technology Xidian University

The edge and contour details in SAR images are important for subsequent processing tasks. The multiscale geometric analysis method — Nonsubsampled contourlet transform(NSCT) is able to capture the geometric information of SAR images effectively. Describing the aggregation behavior of the neighborhoods coefficients, the scale mixtures of Gaussians model has exhibited favorable performances. A novel SAR image despeckling method is presented by constructing the scale mixtures of Gaussians model of NSCT. This method models the SAR images using the multiscale and multidirection information in NSCT domain. The dependency relationship of NSCT neighborhoods coefficients are also taken into consideration in our model. The speckle noise coefficients are shrinkaged by statistical prior estimation based on SAR image model constructed. Experimental results demonstrate that our method is advantageous at directional information preservation and the speckle restraint.

关键词： Synthetic aperture radar(SAR) image despeckling Stationary wavelet transform Nonsubsampled contourlet transform Scale mixtures of Gaussians model.

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Quantitative analysis of temperature distribution in cross-flow planar SOFC based on a validated model

Quantitative analysis of temperature distribution in cross-f...

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Chinese Automation Congress, CAC 2015

作者： Liu, Yali Cheng, Huan Jianhua, J. Li, Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781467371896

In this paper, quantitative analysis was implemented to reveal the mechanism of temperature distributions inside cross-flow stack. For this purpose, a differential model of planar cross-flow SOFC stack was built. The effectiveness of this model on describing temperature distributions were full validated by experiments on single cell and a 40-cell stack. Then, the quantitative analysis was given from two aspects, namely heat produced by reactions and heat transmission between gases and solid layer. Particularly, we rigorously revealed the non-intuitive phenomenon that the fuel temperatures were decreasing inside SOFC stack along the fuel flow direction. Moreover, the research idea and the analytical method proposed in this paper also apply to co-flow and counter-flow SOFC. © 2015 IEEE.

关键词： Temperature distribution

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Architectural distortion recognition based on a subclass technique and the sparse representation classifier

Architectural distortion recognition based on a subclass tec...

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International Congress on image and Signal processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Xiaoming Liu Leilei Zhai Ting Zhu Zhou Yang School of Automation Huazhong University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781509037117

Architectural distortion is the third most common sign of breast cancer in mammograms. The accurate recognition is important for computer aided diagnosis of breast cancer. However, due to the subtle symptom and complex structures in the mammogram images, it is difficult to recognize whether a region of interest (ROI) is truly an architectural distortion. In this paper, we proposed a new method for architectural distortion recognition. In the proposed method, several texture features are extracted for each region of interest, including features from GLCM matrix, spiculated related features, entropy features, etc. Feature selection is obtained by a sub-classes clustering based multi-task learning method (SMTL), which can utilize the discriminative label information and reflect the multi-clustering characteristic of the data samples. Finally, the powerful sparse representation based classifier is used for the classification of AD or non-AD. The proposed method has been tested on DDSM dataset and compared with several other methods, the experimental results showed the effectiveness of the proposed method.

关键词： Feature extraction Distortion Entropy Training Mammography Delta-sigma modulation Breast cancer

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Matrix flat splicing systems 11th

Matrix flat splicing systems

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Ceterchi, Rodica Pan, Linqiang Song, Bosheng Subramanian, K.G. Faculty of Mathematics and Computer Science University of Bucharest 14 Academiei Street Bucharest010014 Romania School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China Department of Mathematics Madras Christian College Chennai600059 India

ISBN: (纸本)9789811036101

In dealing with the problem of modelling DNA recombination, the operation of splicing on linear and circular strings of symbols was introduced. Inspired by splicing on circular strings, the operation of flat splicing on a pair of strings (u, v) was considered. This operation involves "cutting" u at a specified position and "inserting" v into it, with v having a pre-specified prefix as well as suffix defined by a flat splicing rule. In this work, we consider a well-known technique in formal language theory, known as "matrix of rules", and introduce matrix of flat splicing rules and thus define matrix flat splicing system (MFSS). Some results on the language generative power of MFSS are provided. An application of MFSS in the generation of chain code pictures is also pointed out. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Formal languages

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Displacement prediction model of landslide based on multi-gene genetic programming

Displacement prediction model of landslide based on multi-ge...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Jiejie Chen Zhigang Zeng Ping Jiang College of Computer Science and Technnology Hubei Normal university Huangshi China School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China Computer School Hubei PolyTechnic University Huangshi China

In this paper, a new approach is presented for predicting landslide displacement using multi-gene genetic programming (MGGP). For the characteristic of MGGP which does not need specific assumptions, two real cases is ... 详细信息

ISBN: (纸本)9781509044245

关键词： Terrain factors Mathematical model Predictive models Training Geology Computational modeling Forecasting

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Aero-thermal radiation correction via multi-scale bias field estimation 3

Aero-thermal radiation correction via multi-scale bias field...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Li, Lerenhan Yan, Luxin Sang, Nong Gao, Changxin Hu, Jing Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, a multi-scale bias field estimation is proposed to carry out the aero-thermal radiation correction. The bias field is estimated at scales from coarse to fine by an alternative minimization, after which, the degraded image is restored via subtraction. In the minimization, Tiknov regularization is employed to constrain the smoothness of bias field while Total Variation (TV) is adopted to preserve the details and structures of the latent image. Besides, Split Bregman iteration is introduced to conquer the difficulty in the non-smooth problem when resolving the minimization. Compared with conventional approaches, experiments verified that the proposed method contributes to the rapidness and precision of the algorithm. © 2015 IEEE.

关键词： Iterative methods

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DeNet: An explicit distance ensemble model for person re-identification 3

DeNet: An explicit distance ensemble model for person re-ide...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Wang, Jin Gao, Changxin Hu, Jing Sang, Nong Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, we address the problem of person reidentification (re-id), which remains to be challenging due to view point changes, pose variations, different camera settings, etc. Different from common methods that concatenate descriptors extracted from different support regions and feature channels directly as a long vector, we encode the importance of different feature channels and support regions explicitly and propose a two-layer distance ensemble model called DeNet to measure the similarity between two images. The first layer of DeNet combines distances of different support regions while the second layer weights different feature channels. Weight parameters of DeNet are learnt under the large margin framework with the goal of maximizing the difference between distances of positive and negative matching pairs. Our method achieves very competitive results on the widely used VIPeR and PRID 450S datasets. © 2015 IEEE.

关键词： Computers

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A multi-agent coordinated planning approach for deadline required emergency response tasks

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IET control Theory and Applications 2015年第3期9卷 447-455页

作者： Zhou, Chao Wang, Hongwei Zhuo, Hankz Hankui Key Laboratory of Image Processing and Intelligent Control of Education Ministry Institute of Systems Engineering Huazhong University of Science and Technology Wuhan430074 China School of Advanced Computing SunYat-sen University Guangzhou510006 China

This study investigates the emergency decision-making problem in a multi-agent system. Departments are modeled as agents to perform coordinated planning to obtain a global action plan with a short execution time constrained by a prescribed deadline. A novel multi-agent planning approach is proposed to coordinate for the solution among agents in the system. The approach consists of two stages. For the first stage, a coordinated planning and scheduling method is designed to generate a candidate global action plan. In this plan, durative actions are assigned to proper time intervals with the consideration of temporal relationships among agents. For the second stage, a coordination mechanism based on local heuristics is proposed to reduce the global time cost of the candidate plan to satisfy the deadline. An experimental study of emergency evacuation problem is conducted to demonstrate the effectiveness and efficiency of the proposed approach. © 2015 The Institution of Engineering and Technology.

关键词： Multi agent systems

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