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World Congress on Intelligent control and automation (WCICA)

作者： Renquan Lu Jun-Yi Li Yong Xu Hui Peng Key Lab for loT and Information Fusion Technology of Zhejiang The Institute of Information and Control Hanzzhou Dianzi University Hanzzhou China School of Automation Guangdong Key Laboratory of LoT Information Processing Guangzhou China

ISBN: (纸本)9781467384155

This paper is concerned with the distributed ℓ 2 - ℓ ∞ state estimation for discrete time periodic systems with multiplicative noises. To reflect a more general practical situation, multiplicative noises are considered both in state and measurement. The desired distributed state estimators are designed such that the estimation error system is globally asymptotically stable with a guaranteed ℓ 2 - ℓ ∞ performance index. A sufficient condition, based on a periodical Lyapunov procedure, is obtained to guarantee the stability and the performance of the system. At last, a numerical example is provided to illustrate the applicability and the effectiveness of the proposed results.

关键词： Estimation error Symmetric matrices State estimation Noise measurement automation Performance analysis Internet of things

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An overview of coordinated control for multi-agent systems subject to input saturation

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Perspectives in Science 2016年 7卷 133-139页

作者： Xiaoling Wang Housheng Su Xiaofan Wang Guanrong Chen Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China Department of Electronic Engineering City University of Hong Kong Hong Kong China

Coordinated control of multi-agent systems has widespread application in engineering such as unmanned aerial vehicles and unmanned ground vehicles. Due to the fact that input saturation can lead a control system to deterioration and instability, a lot of efforts have been devoted to investigating this subject of great importance. The present article offers a survey of recent developments on coordinated control of multi-agents systems subject to input saturation. Some preliminaries about graph theory, stability theory and input saturation are first provided, followed by some important results in the area, which are categorized into semi-global and global coordinated controls. Future research topics are finally discussed.

关键词： Multi-agent system Coordinated control Consensus tracking Input saturation Low-and-high-gain feedback

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Nonnegative Edge Consensus of Networked Linear Systems

Nonnegative Edge Consensus of Networked Linear Systems

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第35届中国控制会议

作者： Xiaoling Wang Housheng Su Xiaofan Wang Guanrong Chen Department of Automation Shanghai Jiaotong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of ChinaHuazhong University of Science and Technology Department of Electronic Engineering City University of Hong Kong

ISBN: (纸本)9781509009107

In this paper,nonnegative edge consensus of systems steered by general linear dynamics on directed network is *** the new approach,one first endows dynamics to each directed edge and then designs a distributed edge consensus protocol guiding all edges to reach a common *** the help of line graph theory,it is proved that strongly connected network can ensure reaching nonnegative edge consensus,if the initial conditions of all edges are *** simulations are provided to verify the theoretical results.

关键词： Networked system Nonnegative edge consensus Distributed algorithm Line graph

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Modelling and Optimization of Heating Dispatch in Thermal Power Plant

Modelling and Optimization of Heating Dispatch in Thermal Po...

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第28届中国控制与决策会议

作者： Lixia Xie Yali Wu Xianyong Peng Lei Li Fan Yi School of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Emerson Process Management Co.Ltd.

ISBN: (纸本)9781467397155

With the addition of heating in thermal power *** to lack of guidance for heating scheduling in traditional scheduling mode,it has been unable to satisfy the current costs for energy conservation and saving of thermal power *** load distribution(especially heat load dispatch) is an important subject in the operation optimization of a thermal power *** model of heat load dispatch on the condition of economic power dispatch is established and linear programming for optimized heat load distribution among units based on LINGO is *** average distribution and linear programming distribution are contrasted in a thermal power *** is obviously shown by simulation and calculation that linear programming distribution gets more optimal results than current average *** has important significance to reduce energy consumption and save costs.

关键词： Heating Dispatch Thermal Power Plant LINGO

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Unknown constrained mechanisms operation based on dynamic interactive control

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CAAI Transactions on Intelligence technology 2016年第3期1卷 259-271页

作者： Hesheng Wang Bohan Yang Weidong Chen Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China China State Key Laboratory of Robotics and System Harbin Institute of Technology (HIT) Harbin 150001 China

In order to operate various constrained mechanisms with assistive robot manipulators, an interactive control algorithm is proposed in this paper. This method decouples motion and force control in the constrained frame, and modifies the motion velocity online. Firstly, the constrained frame is determined online according to previous motion direction; then the selection matrix is adjusted dynamically, the constrained motion direction is chosen as the driving-axis. Consequently, the driving-axis and non-driving-axis are decoupled; finally, velocity control and impedance control are implied on above axes respectively. The selecting threshold for driving-axis is also varying dynamically to fit different constrained mechanism. Door-opening experiments are conducted to verify the performance of the proposed method.

关键词： Unknown constrained mechanism Selection matrix Constrained frame Robot manipulator Impedance control

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A multi-objective optimization algorithm based on tissue P system for VRPTW 11th

A multi-objective optimization algorithm based on tissue P s...

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

作者： Dong, Wenbo Zhou, Kang Qi, Huaqing He, Cheng Zhang, Jun Song, Bosheng School of Math and Computer Wuhan Polytechnic University WuhanHubei430023 China Department of Economics and Management Wuhan Polytechnic University WuhanHubei430023 China Key Laboratory of Image Information Processing and Intelligent Control Huazhong University of Science and Technology WuhanHubei430074 China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China

ISBN: (纸本)9789811036132

Vehicle routing problem with time windows has an important practical significance, but it is NP-Hard problem. In order to solve the problem, an optimization algorithm based on P system is proposed. The encoding of glowworm’s location is considered as evolutionary object and discrete glowworm evolution mechanism and variable neighborhood evolution mechanism are used as sub-algorithms. In this paper, the motion equations and related motion rules of glowworm algorithm are improved to optimize the performance of the algorithm. Meanwhile, in order to enlarge the search area of solution space and improve the precision, the variable neighborhood evolution mechanism is redesigned. Cell communication rules are used to exchange information between cells. Moreover, this paper introduced the concept of Pareto dominance to evaluate the advantages and disadvantages of the object, as a result, this method returns not a single non-dominated solution but a set of no-dominated solutions. At last, by solving the different Solomon numerical examples and simulation results show that the algorithm is easier to jump out of local optimal both achieves very good results in the number of vehicles and distance cost, besides, generates a lot of new solutions which are different from the database. This algorithm has the features of faster convergence rate and accurate precision, and it is competitive with other heuristic or metaheuristic algorithms in the literature. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Multiobjective optimization

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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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Improvement of Resting-state EEG Analysis Process with Spectrum Weight-Voting based on LES

arXiv

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arXiv 2017年

作者： Ye, Yumeng Liu, Haichun Zhang, TianHong Pan, Changchun Yang, Genke Wang, JiJun Qiu, Robert C. Key Laboratory of System Control and Information Processing Shanghai Jiaotong University Ministry of Education of China Shanghai200240 China Department of Automation and Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiaotong University School of Medicine Shanghai200030 China Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai200240 China Shanghai Jiaotong University Shanghai200240 China Department of Electrical Engineering Shanghai Jiaotong University Shanghai200240 China Department of Electrical and Computer Engineering Tennessee Technological University CookevilleTN38505 United States

Electroencephalography is a non-invasive technique for recording brain bioelectric activity, which has potential applications in various fields such as human-computer interaction and neuroscience. Among them, analysis of the risk of schizophrenia using EEG data is a relatively new research topic. However, there are many difficulties in analyzing EEG data, including its complex composition, low amplitude as well as low signal-to-noise ratio. Some of the existing methods of analysis are based on feature extraction and machine learning to differentiate the phase of schizophrenia (First-episode schizophrenia, Healthy controls or Clinical high-risk) that samples belong to. However, medical research requires the use of machine learning not only to give more accurate classification results, but also to give the results that can be applied to pathological studies. The main purpose of this study is to obtain the weight values as the representation of influence of each frequency band on the classification of schizophrenia phases on the basis of a more effective classification method using the LES feature extraction, and then the weight values are processed and applied to improve the accuracy of machine learning classification. We propose a method called weight-voting to obtain the weights of sub-bands features by using results of classification for voting to fit the actual categories of EEG data, and using weights for reclassification. Through this method, we can first obtain the influence of each band in distinguishing three schizophrenia phases, and analyze the effect of band features on the risk of schizophrenia contributing to the study of psychopathology. In addition, the weights applied to the original classifier can achieve the upgrade of the classification effect, which contributes to the BCI-assisted system of diagnosis and treatment. Our results show that there is a high correlation between the change of weight of low gamma band and the difference between HC, CHR an

关键词： Electroencephalography

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A Data Driven Approach for Resting-state EEG signal Classificition of Schizophrenia with control Participants Using Random Matrix Theory

arXiv

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arXiv 2017年

作者： Liu, Haichun Zhang, TianHong Ye, Yumeng Pan, Changchun Yang, Genke Wang, JiJun Qiu, Robert C. Key Laboratory of System Control and Information Processing Shanghai Jiaotong University Ministry of Education of China Shanghai200240 China Department of Automation Shanghai Jiaotong University Shanghai200240 China Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiaotong University School of Medicine Shanghai200030 China Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai200240 China Department of Electrical Engineering Shanghai Jiaotong University Shanghai200240 China Department of Electrical and Computer Engineering Tennessee Technological University CookevilleTN38505 United States

Resting state electroencephalogram (EEG) abnormalities in clinically high-risk individuals (CHR), clinically stable first-episode patients with schizophrenia (FES), healthy controls (HC) suggest alterations in neural oscillatory activity. However, few studies directly compare these anomalies among each types. Therefore, this study investigated whether these electrophysiological characteristics differentiate clinical populations from one another, and from non-psychiatric controls. To address this question, resting EEG power and coherence were assessed in 40 clinically high-risk individuals (CHR), 40 first-episode patients with schizophrenia (FES), and 40 healthy controls (HC). These findings suggest that resting EEG can be a sensitive measure for differentiating between clinical *** paper proposes a novel data-driven supervised learning method to obtain identification of the patients mental status in schizophrenia research. According to Marchenko-Pastur Law, the distribution of the eigenvalues of EEG data is divided into signal subspace and noise subspace. A test statistic named LES that embodies the characteristics of all eigenvalues is adopted. different classifier and different feature(LES test function) are selected for experiments, we have shown that using von Neumann Entropy as LES test function combine with SVM classifier could obtain the best average classification accuracy during three classification among HC, FES and CHR of Schizophrenia group with EEG signal. It is worth noting that the result of LES feature extraction with the highest classification accuracy is around 90% in two classification(HC compare with FES) and around 70% in three classification. Where the classification accuracy higher than 70% could be used to assist clinical diagnosis. Copyright © 2017, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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A GPS/INS Navigation Strategy of Dealing with Extreme Cases by Cooperating Radar(IEEE CGNCC)

A GPS/INS Navigation Strategy of Dealing with Extreme Cases ...

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2016 IEEE Chinese Guidance, Navigation and control Conference (IEEE CGNCC2016)

作者： Zhi Liu Huabao Long Jie He Yunze Cai Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China Shanghai Aerospace Control Technology Institute Eighth Design Department of Shanghai Spaceflight Bureau

ISBN: (纸本)9781467383196

This paper designs a strategy that monitors the system anomaly and uses radar's information to replace the GPS to complete the navigation when anomaly *** can solve system divergence problem that appears when the GPS data is distortional or the GPS is not functional in the GPS/INS navigation *** uses innovation adjustment method to monitor the anomaly of the Kalman filter then uses radar to replace the *** paper tests this navigation strategy on real-time data,then analyze the influence of precision of radar on the navigation system's precision in an extreme *** this strategy can keep the system in a good stability and a good navigation precision and has good feasibility.

关键词： Kalman filter INS A GPS/INS Navigation Strategy of Dealing with Extreme Cases by Cooperating Radar IEEE CGNCC GPS

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