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Robust reliable guaranteed cost control of positive interval systems with multiple time delays and actuator failure

International Journal of Systems Science 2016年第4期47卷 946-955页

作者： Zhang, Ji-Shi Wang, Yan-Wu Xiao, Jiang-Wen Chen, Yang School of Automation Huazhong University of Science and Technology Wuhan China School of Software Henan University Kaifeng China Key Laboratory of Image Processing and Intelligent Control Education Ministry of China Wuhan China

This paper addresses the robust reliable guaranteed cost control problem of positive interval systems with multiple time delays and actuator failure for a given quadratic cost function. Through constructing a Lyapunov-Krasovskii functional, a sufficient condition for the existence of robust reliable guaranteed cost controllers is established such that the closed-loop system is positive and asymptotically stable, and the cost function is guaranteed to be no more than a certain upper bound. Based on the linear matrix inequality method, a criterion for the design of robust reliable guaranteed cost controllers is derived which can tolerate all admissible uncertainties as well as actuator failure. Moreover, a convex optimisation problem with linear matrix inequality constraints is formulated to design the optimal robust reliable guaranteed cost controller which minimises the upper bound of the closed-loop system cost. A numerical example is given to show the effectiveness of the proposed methods. © 2014 Taylor & Francis.

关键词： Closed loop systems

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Brain MRI Segmentation with Patch-based CNN Approach

Brain MRI Segmentation with Patch-based CNN Approach

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第35届中国控制会议

作者： Zhipeng CUI Jie YANG Yu QIAO Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University The Key Laboratory of Ministry of Education for System Control and Information Processing

ISBN: (纸本)9781509009107

Brain Magnetic Resonance image(MRI) plays a non-substitutive role in clinical *** symptom of many diseases corresponds to the structural variants of *** structure segmentation in brain MRI is of great importance in modern medical *** methods were developed for automatic segmenting of brain MRI but failed to achieve desired *** this paper,we proposed a new patch-based approach for automatic segmentation of brain MRI using convolutional neural network(CNN).Each brain MRI acquired from a small portion of public dataset is firstly divided into *** of these patches are then used for training CNN,which is used for automatic segmentation of brain *** results showed that our approach achieved better segmentation accuracy compared with other deep learning methods.

关键词： CNN Deep Learning Brain MRI Segmentation Patch-based

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Objective resolution measurement in single particle reconstructions based on a new spectral signal-to-noise ratio estimation

Objective resolution measurement in single particle reconstr...

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第28届中国控制与决策会议

作者： Shuai Wang Biao Zhang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (纸本)9781467397155

The resolution measurement of 3D reconstructed density map in single particle reconstruction is an important and still an open *** this paper,we propose a new protocol to measure the resolution just from the reconstructed density *** approach estimates spectral signal-to-noise ratio(SSNR) of 3D reconstructed map by computing the ratio of signal power to noise power in frequency *** power distributions of signal and noise are estimated from structure particle region and surrounding region segmented by applying a mask *** proposed protocol of calculating SSNR,which we term mask-SSNR(mSSNR),is independent of the reconstruction algorithms and can be used for density maps reconstructed with any reconstruction ***,the mSSNR neither needs to split the dataset into halves like the Fourier shell correlation(FSC) approach,nor any original images or intermediate data like other SSNR calculation methods in this *** mSSNR provides a direct calculation of SSNR based on its original definition,and is proven to be a better approach.

关键词： Electron microscopy Resolution measurement Spectral signal-to-noise ratio Signal processing

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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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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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A robust cell tracking framework by fusing global and local optimization algorithms

A robust cell tracking framework by fusing global and local ...

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第28届中国控制与决策会议

作者： Shu Meng Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (纸本)9781467397155

Automated cell tracking is an important branch of multi-object tracking,which can be used for quantitatively analyzing cell migration,proliferation and *** this paper,we proposed a hierarchical tracking method,fusing the global optimal method in consecutive frames assignment and local optimal approach in spatial trajectory *** the process,the detection errors were recognized and cell moving trajectories were completed *** also introduced the concept of clustering to measure the correlation between established short trajectories and reduce the tracking errors caused by fast *** rare information of cells was used in the linkage,the system can work well with *** experimental results show the effectiveness of our approach with cells having different density and activity.

关键词： Multi-object tracking Bipartite graph Optimization Hierarchical tracking

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Consensus control for Second-Order Multi-Agent with Time-Delay on Antagonistic Networks

Consensus Control for Second-Order Multi-Agent with Time-Del...

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第35届中国控制会议

作者： Penglin LI Yue LIU Yadong ZHAO Jie YANG Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University State Key Laboratory of Industrial Control Technology Institute of Industrial Process ControlCollege of Control Science and EngineeringZhejiang University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781509009107

In this paper,we discuss consensus problems for antagonistic networks with double integrator *** cases are analyzed:(1) undirected graphs with fixed topology on antagonistic networks;(2) undirected graphs with fixed topology and time-delay on antagonistic *** both cases,distributed consensus protocols are proposed,with sufficient and necessary conditions *** is proved that the largest tolerable time-delay is only related to the largest eigenvalue of the graph ***,simulations are provided to demonstrate the obtained theoretical results.

关键词： Consensus Fixed Topology Multi-agent Antagonistic Networks Time-delay

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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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Learning robust and discriminative low-rank representations for face recognition with occlusion

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Pattern Recognition 2017年 66卷 129-143页

作者： Guangwei Gao Jian Yang Xiao-Yuan Jing Fumin Shen Wankou Yang Dong Yue Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China Jiangsu Engineering Laboratory of Big Data Analysis and Control for active distribution network Nanjing University of Posts and Telecommunications Nanjing China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University) Fuzhou China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Automation Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Automation Southeast University Nanjing China

For robust face recognition tasks, we particularly focus on the ubiquitous scenarios where both training and testing images are corrupted due to occlusions. Previous low-rank based methods stacked each error image into a vector and then used L 1 or L 2 norm to measure the error matrix. However, in the stacking step, the structure information of the error image can be lost. Depart from the previous methods, in this paper, we propose a novel method by exploiting the low-rankness of both the data representation and each occlusion-induced error image simultaneously, by which the global structure of data together with the error images can be well captured. In order to learn more discriminative low-rank representations, we formulate our objective such that the learned representations are optimal for classification with the available supervised information and close to an ideal-code regularization term. With strong structure information preserving and discrimination capabilities, the learned robust and discriminative low-rank representation (RDLRR) works very well on face recognition problems, especially with face images corrupted by continuous occlusions. Together with a simple linear classifier, the proposed approach is shown to outperform several other state-of-the-art face recognition methods on databases with a variety of face variations.

关键词： Face recognition Low-rank matrix recovery Nuclear norm

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Event-Triggering Load Frequency control for Multiarea Power Systems with Communication Delays

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IEEE Transactions on Industrial Electronics 2016年第2期63卷 1308-1317页

作者： Wen, Shiping Yu, Xinghuo Zeng, Zhigang Wang, Jinjian School of Automation Key Laboratory of Image Processing and Intelligent Control Ministry of Education of China Huazhong University of Science and Technology Wuhan430074 China Platform Technologies Research Institute RMIT University MelbourneVIC3001 Australia

This paper studies the load frequency control (LFC) for power systems with communication delays via an event-triggered control method to reduce the amount of communications required. The effect of the load disturbances on the augmented output is defined as a robust performance index of the augmented LFC scheme. By utilizing a time-delayed system design approach, a new model of the LFC scheme with delays is formulated, where the communication delays and event-triggered control are integrated for the LFC scheme. Based on the Lyapunov-Krasovskii functional method, the criteria for the event-triggered stability analysis and control synthesis of the LFC scheme are derived. Finally, the effectiveness of the proposed method is verified by simulation studies. © 1982-2012 IEEE.

关键词： Time delay

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