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The Minimum Principle for Hybrid systems with Partitioned State Space and Unspecified Discrete State Sequence

The Minimum Principle for Hybrid Systems with Partitioned St...

引用

2010 49th IEEE Conference on Decision and control

作者： Benjamin Passenberg Peter E. Caines Marion Sobotka Olaf Stursberg Martin Buss Institute of Automatic Control Department of Electrical Engineering and Information Technology Technische Universitat Munchen Munchen Germany Department of Electrical and Computer Engineering and the Center for Intelligent Machines McGill University Montreal Canada Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Kassel Germany

ISBN: (纸本)9781424477456

The hybrid minimum principle (HMP) gives necessary conditions to be satisfied for optimal solutions of a hybrid dynamical system. In particular, the HMP accounts for autonomous switching between discrete states that occurs whenever the trajectory hits switching manifolds. In this paper, the existing HMP is extended for hybrid systems with partitioned state space to provide necessary conditions for optimal trajectories that pass through an intersection of switching manifolds. This extension is especially useful for the numerical solution of hybrid optimal control problems as it allows for algorithms with significant reduction of computational complexity. Algorithms based on previous versions of the HMP solve separate optimal control problems for each possible sequence of discrete states. The extension enables us to consider the optimal sequence as subject of optimal control that is varied and finally determined during a single optimization run. A first numerical result illustrates the effectiveness of an algorithm based on the extended HMP.

关键词： state space minimum principle hybrid systems Manifolds Optimal control DYNAMICAL systemS discrete element

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Noninvasive biosignal measurement of a subject in bed using ceramic sensors

Noninvasive biosignal measurement of a subject in bed using ...

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SICE Annual Conference

作者： Toshihiro Shino Kajiro Watanabe Kazuyuki Kobayashi Kaoru Suzuki Yosuke Kurihara System Control Engineering Department Faculty of Engineering Hosei University Koganei Tokyo Japan Department of Computer and Information Science Faculty of Science and Technology Seikei University Musashino Tokyo Japan

This paper describes a novel noninvasive method for sensing heartbeat, respiration and body-movement biosignals of a subject in bed by using ceramic piezo devices set under the legs of the bed.

ISBN: (纸本)9781424476428

This paper describes a novel noninvasive method for sensing heartbeat, respiration and body-movement biosignals of a subject in bed by using ceramic piezo devices set under the legs of the bed.

关键词： Heart beat Ceramics Leg Sensor phenomena and characterization Microphones Turning

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Development Methods for Low Cost Industrial control by WinPAC controller and Measurement Cards in Matlab Simulink

Development Methods for Low Cost Industrial Control by WinPA...

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International Conference on computer engineering and Applications (ICCEA)

作者： Michal Tutsch Zdenek Machacek Ondrej Krejcar Petr Konarik Department of Measurement and Control Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Control System and Instrumentation Faculty of Mechanical Engineering VSB-Technical University of Ostrava Ostrava Czech Republic

ISBN: (纸本)9781424460793;9780769539829

The approach to development methods which are described in paper allows possibility extension for minimizing costs and widely external hardware industrial control systems utilization. There is described development method of control applications by industrial WinPLC/WinPAC and REX control compiler in comparison to classical development methods that need expensive RT measurement cards and produce only one purpose development solution. The project is based on specification of development process of designed control schemas of prepared applications to an industrial utilization by direct connection and implementation to the chosen control system WinPLC/WinPAC. Paper deals with a way how to produce a solution for control applications that are prepared, designed and implemented in MATLAB-Simulink to the target platform. The multiplatform control system REX is used as a bridge between MATLAB and target platform.

关键词： Costs Industrial control control systems Electrical equipment industry Hardware Process design Process control computer languages Bridges MATLAB

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Modern development of low cost RT industrial process control based on Matlab-Simulink and PAC

Modern development of low cost RT industrial process control...

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Roedunet International Conference (RoEduNet)

作者： Michal Tutsch Petr Konarik Department of Measurement and Control Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Control System and Instrumentation Faculty of Mechanical Engineering VSB-Technical University of Ostrava Ostrava Czech Republic

The paper presents modern advanced development methods of control systems that minimizes the cost of development of applications which are widely applicable in industrial control of whole range of processes.

ISBN: (纸本)9781424473359

关键词： Costs Industrial control Process control computer languages

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Fuzzy C-means cluster segmentation algorithm based on hybridized particle swarm optimization

Fuzzy C-means cluster segmentation algorithm based on hybrid...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Yan-ling Li Yi Shen College of Computer and Information Technology Xinyang Normal University Xinyang China Institute of System Engineering Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

Fuzzy C-Means(FCM) algorithm is one of the most popular methods for image segmentation, but it is in essence a technology of searching local optimal solution. The algorithm's initial clustering centers are the stochastic selection which causes it to depend on the selection of the initial cluster centers excessively. It always converges at the local optimum and is sensitive to noise. In order to overcome those defects, the fuzzy C-means cluster segmentation algorithm based on hybridized particle swarm optimization is proposed in this paper. Firstly, the hybridized particle swarm algorithm is used to get the initial cluster centers. Then, the images are segmented using standard FCM algorithm. Experimental results show that the proposed algorithm used for image segmentation can segment images more effectively and can provide more robust segmentation results.

关键词： Magnetic resonance imaging Integrated circuits Legged locomotion Image segmentation Educational institutions

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Feature selection for semi-supervised multi-label learning with application to gene function analysis 10

Feature selection for semi-supervised multi-label learning w...

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Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology

作者： Li, Guo-Zheng You, Mingyu Ge, Lei Yang, Jack Y. Yang, Mary Qu MOE Key Laboratory of Embedded System and Service Computing Tongji University Shanghai 201804 China Department of Control Science and Engineering Tongji University Shanghai 201804 China School of Computer Science and Engineering Shanghai University Shanghai 200072 China Purdue Univ. ECE West Lafayette IN 47907 United States Indiana Univ. Bioinformatics Center Indianapolis IN 46202 United States

ISBN: (纸本)9781450304382

This paper investigates gene function annotation of Yeast by using semi-supervised multi-label learning. Multi-label learning has been a hot topic in the bioinformatics field, but there are many samples unlabeled. Semi-supervised learning may be employed to utilize the unlabeled data. This paper proposes a novel semi-supervised multi-label learning algorithm COMN by combining Co-Training with ML-kNN to utilize the unlabeled yeast gene data to improve modeling accuracy of function annotation. Furthermore, an embedded feature selection algorithm PRECOMN is proposed to perform feature selection for COMN to remove the irrelevant and redundant features. Experimental results on one benchmark data set of Yeast show COMN and PRECOMN perform better than the original multi-label learning algorithm ML-kNN. Furthermore PRECOMN improves generalization performance of COMN. Copyright © 2010 ACM.

关键词： Feature Selection

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Comparison of voxel-based morphometry (VBM) and tractography of diffusion tensor MRI (DT-MRI) in temporal lobe epilepsy

Comparison of voxel-based morphometry (VBM) and tractography...

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Iranian Conference on Electrical engineering (ICEE)

作者： Maryam Afzali Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

ISBN: (纸本)9781424467600

Temporal lobe epilepsy (TLE) is a neurological disease that affects millions of individuals in the world. Majority of TLE patients suffer from refractory seizures. Determining abnormal/damaged regions of the brain that harbor seizure focus is a critical step towards treatment of TLE patients. Diffusion tensor imaging (DTI) is a non-invasive method that we use in this work to determine damaged regions of white matter in the brain. To this end, we apply two methods, voxel based morphometry (VBM) and fiber tracking. We use these methods along with two anisotropy maps (EAR and FA) extracted from the DTI data. We use DTI data of 31 subjects (12 normal subjects and 19 TLE patients) for testing and evaluation studies. The VBM method shows that TLE is associated with reduction of both of FA and EAR values in several regions within the temporal lobes. The tractography method shows abnormal diffusion characteristics in three fiber bundles (fornix, uncinate fasciculus, and cingulum). The results show that the EAR maps are less sensitive to noise than the FA maps and the EAR values change more than the FA values in TLE.

关键词： Tensile stress Magnetic resonance imaging Diffusion tensor imaging Temporal lobe Epilepsy Ear Optical fiber testing Diseases Focusing Medical treatment

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Virtual production control system

Virtual production control system

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Haw-Ching Yang Ying-Liang Chen Min-Hsiung Hung Fan-Tien Cheng Institute of System Information and Control National Kaohsiung First University of Science and Technology Kaohsiung Taiwan Institute of Manufacturing Engineering National Cheng Kung University Tainan Taiwan Department of Computer Science Chinese Cultural University Taipei Taiwan

ISBN: (纸本)9781424454471

This work develops a novel virtual production control system (VPCS), which is allocated on a manufacturer side to adjust production pace of a supplier using a short-term demand plan for reducing inventory level. In addition to remotely monitoring production progress of a supplier, the proposed VPCS allows manufacturers to pre-schedule the latest outputs using an integer programming model, to simulate the short-term plan by a stochastic colored timed Petri Nets, and to adjust the production pace of the supplier via the plan. An industrial case study shows that the supplier inventory was reduced by 13.8% over that of the real inventory level with an order-fill rate exceeding 99.6% using the proposed VPCS.

关键词： Materials Programming Predictive models Data preprocessing Capacity planning

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

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International Conference on Intelligent and Advanced systems, ICIAS

作者： Mahdi Ramezani Amin Heidari Emad Fatemizadeh Hamid Soltanian-Zadeh Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearest-neighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Clustering algorithms Algorithm design and analysis Correlation Approximation methods Independent component analysis Time series analysis Approximation algorithms

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A methodology for power quality evaluation in distribution network with distributed generation

A methodology for power quality evaluation in distribution n...

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International Conference on Critical Infrastructures, CRIS

作者： Gengyin Li Zhe Zhang Xiang Li Song Wang Ming Zhou Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control under Ministry of Education North China Electric Power University Beijing China Department of Electrical Engineering Tsinghua University Haidian Beijing China School of Electrical and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781424480807

The issue of power quality in the distribution system is always in sense of the concern. With the high penetration of distributed generation (DG) currently, it tends to be more complicated. This paper presents a new approach to evaluate impacts of the DG on power quality of the distribution network. In the process an objective function will be modeled, which will be solved by the optimization toolbox, in order to calculate the result for the evaluating grade. Furthermore, the results of the overall evaluation will be given via the eigenvalue weighted method. The power quality ranking of each feeder with the distributed generators in the distribution network will be apparent with the given weight of influence caused by DGs divided in forms of energy resource.

关键词： Power quality Generators Indexes Distributed power generation Eigenvalues and eigenfunctions Optimization Voltage fluctuations

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