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第37届中国控制会议

作者： Yawen Xiao Jun Wu Zongli Lin Xiaodong Zhao Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information Processing of Ministry of Education The Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia School of Biomedical Engineering Shanghai Jiao Tong University

Breast cancer is the most often detected cancer in women. At the same time, it is one of the most curable types of cancer if diagnosed early. With the development of the detection technology, a growing amount of clinical data and highdimensional features can be used for breast cancer diagnosis. The high-dimensional data contributes to advances in the diagnostic technology, but also incurs a large amount of computational redundancy. Thus, extracting important information and reducing the feature dimension is critical to effective prediction and an accurate treatment ***, the previous works for breast cancer diagnosis are mainly based on labeled data that is difficult to obtain. To address this issue, in this paper, we demonstrate a new scheme, which integrates a deep learning based unsupervised feature extraction algorithm, the stacked auto-encoders, with a support vector machine model（SAE-SVM）, for breast cancer diagnosis. The stacked auto-encoders with the greedy layerwise pre-training and an improved momentum update algorithm is applied to capture essential information and extract necessary features of the original data. Then, a support vector machine model is employed to classify the samples with new features into malignant or benign tumors. The proposed method was tested on the Wisconsin Diagnostic Breast Cancer data set. The performance is evaluated using various measures and compared with the previously published results. The comparison results show that the proposed SAE-SVM method improves the accuracy to 98.25% and outperforms the other methods. The deep learning based unsupervised feature extraction significantly improves the performance of classification and provides a promising approach to breast cancer diagnosis.

关键词： Deep learning auto-encoder feature extraction breast cancer diagnosis unlabeled data

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Bifurcation analysis and control of quorum sensing network model 5

Bifurcation analysis and control of quorum sensing network m...

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5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2017

作者： Mei, Qicheng Liu, Feng Ren, Jie Sun, Fenglan Wang, Hua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Research Center of System Theory and Application Chongqing University of Posts and Telecommunications Chongqing400065 China Department of Mechanical Engineering Boston University BostonMA02215 United States

In this paper, a model is constructed to investigate the mechanism induced quorum sensing (QS) by coexisting of small RNA and signal molecule. The QS network model regulated by small RNAs is studied. The condition of the stability of the QS network is considered by using Routh-Hurwitz stability criterion. The conditions for the existence of Hopf bifurcation are obtained. Then, a linear feedback control is designed to make the system asymptotically stable. The numerical simulation is used to verify the results of theoretical analysis.

关键词： Hopf bifurcation

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Distributed state estimation and data fusion in wireless sensor networks using multi-level quantized innovation

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Science China(Information Sciences) 2016年第2期59卷 217-231页

作者： Zhi ZHANG Jianxun LI Liu LIU Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications

Low energy consumption and limited power supply are significant factors for wireless sensor networks(WSNs); thus, distributed state estimation and data fusion with quantized innovation are explored. The universal features of practical WSNs are investigated, and a dynamic transmission strategy is introduced. Furthermore,quantization state estimation based on Bayesian theory is derived. Unlike previous algorithms suitable for processing scalar measurement, the proposed distributed data fusion algorithm is applicable to general vector measurement. Furthermore, the efficiency of the proposed dynamic transmission strategy is analyzed. It is concluded that the proposed algorithm is more efficient than previous methods, and its estimation accuracy comparable to that of the standard Kalman filtering, which is based on analog-amplitude vector measurement.

关键词： data fusion distributed state estimation target tracking Kalman filtering quantization wireless sensor networks

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Synchronized Cell-Balancing Charging of Supercapacitors

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IFAC-PapersOnLine 2017年第1期50卷 3338-3343页

作者： Li H. Peng J. He J. Huang Z. Pan J. School of Information Science and Engineering Central South University Changsha 410087 China Department of Computer Science University of Victoria Victoria V8P5C2 Canada Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai 200240 China

As a classical cell balancing solution in low-power supercapacitor applications, the switched resistor circuit is vulnerable to resistance deviation effects with existing cell balancing methods. In this paper, we propose a synchronized cell balancing method for switched resistor circuits based on the consensus theory and a cyber-physical approach, with the aim of synchronizing cell voltages before they are fully charged. It is shown that the proposed cell-balancing algorithm is robust to resistance deviation effects. Extensive simulations are provided to show the effectiveness of the proposed method. © 2017

关键词： Cell balancing Charging Consensus Cyber-physical systems Supercapacitors

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Feedback control of a non-Markovian single qubit system

Feedback control of a non-Markovian single qubit system

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Asian control Conference

作者： Shibei Xue Thien Nguyen Ian R. Petersen Department of Automation Key Laboratory of System Control and Information Processing Shanghai China Research School of Engineering Australian National University Canberra Australia

ISBN: (纸本)9781509015740;9781509015733

In this paper, we utilize a feedback strategy to stabilize a single qubit in a non-Markovian environment with a Lorentzian spectrum. The non-Markovian single qubit is represented in an augmented system model, where an ancillary system is introduced as the internal mode of the environment to generate Lorentzian noise. The density matrix of the single qubit can be estimated by using an augmented-system-based quantum stochastic master equation. Then a feedback controller can be driven by the estimates to stabilize the qubit in a target state. Simulations show the feedback strategy can provide effective control of the non-Markovian single qubit.

关键词： Mathematical model Couplings Feedback control Quantum computing White noise Colored noise Quantum entanglement

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Track Irregularities Estimation Based on the Vibration of Car-body

Track Irregularities Estimation Based on the Vibration of Ca...

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： Yuanxing Zhang Xinya Sun Xiaobin Xu Wei Dong Yindong Ji Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Institute of System Science and Control Engineering Hangzhou Dianzi University

Track irregularities have a significant effect on ride quality and traffic safety. The inspection of track irregularity mainly relies on special track inspection car which has a high cost and long ins

ISBN: (纸本)9781467389808

关键词： Track irregularities On-line inspection Track quality index Multiple linear regression track irregularity on line detection Vibration Linear Regression Vehicle body railway system normal acceleration Ride quality Traffic safety

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The Ellipsoidal Invariant Set of Fractional Order systems Subject to Actuator Saturation:The Convex Combination Form

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IEEE/CAA Journal of Automatica Sinica 2016年第3期3卷 311-319页

作者： Kai Chen Junguo Lu Chuang Li School of Mechanical and Electrical Engineering Hainan University Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

The domain of attraction of a class of fractional order systems subject to saturating actuators is investigated in this paper. We show the domain of attraction is the convex hull of a set of ellipsoids. In this paper, the Lyapunov direct approach and fractional order inequality are applied to estimating the domain of attraction for fractional order systems subject to actuator saturation. We demonstrate that the convex hull of ellipsoids can be made invariant for saturating actuators if each ellipsoid with a bounded control of the saturating actuators is invariant. The estimation on the contractively invariant ellipsoid and construction of the continuous feedback law are derived in terms of linear matrix inequalities (LMIs). Two numerical examples illustrate the effectiveness of the developed method. © 2014 Chinese Association of automation.

关键词： Algebra Computational geometry Linear matrix inequalities Numerical methods Saturation (materials composition)

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Reliable Code Generation and Test Environment demonstrated on a PI-controller Design

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IFAC-PapersOnLine 2016年第3期49卷 465-470页

作者： Schwarz, M.H. Sheng, H. Üstoglu, I. Chabaan, W. Börcsök, J. Safety Computer Technology University of Kassel Germany Control and Automation Engineering Department Yildiz Technical University Istanbul Turkey Computer Architecture and System Programming University of Kassel Germany

This paper focuses on the latest version of a tool developed within the department to guide developer through the various steps of requirements, test-procedures and documentations to finally download the derived algorithm on a safety programmable logic controller (PLC). Requirements on how to develop and how to test software are steadily increasing due to international standards, which have to be obeyed in industries in general, and in the process- and automation industries in particular. A simple model is derived to be used to develop a PI controller that has to pass several steps to be qualified for execution on a PLC. The paper explains the different steps and describes the various problems that might occur. © 2016

关键词： controllers Accident prevention Reliability Software testing Automated code generation automation industry International standards P i controller designs PI control Programmable Logic controller (PLC) Simple modeling Test Environment

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Non-parametric modeling of double-link flexible robot manipulator based on NNARX model structure 19th

Non-parametric modeling of double-link flexible robot manipu...

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19th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, CLAWAR 2016

作者： Jamali, Annisa Mat Darus, Intan Zaurah Abdulhussain, Ali Tokhi, M.O. Automation and Control Laboratory Faculty of Mechanical Engineering Universiti Teknologi Malaysia SkudaiJohor81300 Malaysia Department of Automatic Control and System Engineering University of Sheffield United Kingdom

ISBN: (纸本)9789813149120

The double-link flexible robot manipulator (DLFR) is a highly non-linear system. The development of existing linear models involves a lot of assumptions and approximations in order to reduce the complex calculation. Due to that, this paper presents a non-linear Auto Regressive model with eXogenous inputs (NARX) for DLFR and neural network is used to predict the non-linear segment. Thus, NNARX structure is used to develop four separate model of double link flexible manipulator from torque input to hub angle and from torque input to end point accelerations of each link. The performance of NNARX models are validated via One Step Ahead, Mean Squared Error and correlation tests. © 2016, World Scientific Publishing Co. Pte Ltd. All rights reserved.

关键词： Flexible manipulators

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On-line Monitoring for Coal Low Heating Value in Coal-fired Power Plant Boiler Based on CM-LSSVM-PLS 35

On-line Monitoring for Coal Low Heating Value in Coal-fired ...

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第35届中国控制会议

作者： Shi Yuanhao Wang Jingcheng Ren Yifeng School of Computer Science and Control Engineering North University of China Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

ISBN: (纸本)9781509009107

A novel comprehensive real-time on-line calculation model of coal's Low Heating Value(LHV) in coal-fired boiler is presented in this ***,the training operational data is partitioned into several subsets by means of C-Means cluster ***,the Least Squares Support Vector Machine(LS-SVM) method is used to training the sub-models in each ***,the sub-models are combined into one model based on Partial Least Squares algorithm(PLS).The models' effectiveness is illustrated by the validation of online simulation in which the real operation data is *** result shows that it is potential to considerably fulfill not only the accuracy of online monitoring of LHV of the coal into the boiler,but also the real-time computations that are supplied by using indirect heat balance approach.

关键词： Coal-fired Power Plant Boiler Thermal Efficiency Low Heating Value C-Means Cluster LS-SVM PLS

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