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IEEE International Conference on Mechatronics and Automation

作者： Shuxiang Guo Jiange Gao Jian Guo Weijie Zhang Yuye Hu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Biomedical Robot Laboratory Tianjin University of Technology Tianjin China Intelligent Mechanical Systems Engineering Department Kagawa University Takamatsu Japan Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System Tianjin China

ISBN: (纸本)9781509023974

The exoskeleton robotic rehabilitation training system is a branch of the field of robotics, it is the external mechanical system that is consistent with the similar joints of the human body, and attached to the human body. With the development of exoskeleton rehabilitation robotic system, the biomechanics influence of device should be considered in rehabilitation training. This paper proposes a novel upper limb exoskeleton rehabilitation device based on biomechanics, which can be used in rehabilitation of upper limb for hemi paralysis patients. This system aims at helping hemi paralysis patients recover motor function of upper limb; in addition it is suitable for variety of patients. This system is portable and wearable, which consists of exoskeleton device, hepatic device (PHANTOM Premium), motor controllers and work station (computer). This paper proposes a structural optimization scheme in order to solve some problems of bowl's structure of the rehabilitation robot. The Pro/ENGINEER Wildfire (Pro/E) software is applied to get a three-dimensional modelling, kinematics simulation and dynamic analysis of the rehabilitation robot. From the analysis, the robot end motion simulation curves were obtained to verify the optimization structure reasonable and better motion characteristics. In the future, this structure will have a wide application prospect in the rehabilitation therapy field.

关键词： Robots Exoskeletons Wrist Jacobian matrices Gears Optimization Acceleration

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Design and kinematic simulation of a novel exoskeleton rehabilitation hand robot

Design and kinematic simulation of a novel exoskeleton rehab...

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IEEE International Conference on Mechatronics and Automation

作者： Shuxiang Guo Weijie Zhang Jian Guo Jiange Gao Yuye Hu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Biomedical Robot Laboratory Tianjin University of Technology Tianjin China Intelligent Mechanical Systems Engineering Department Kagawa University Takamatsu Japan Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System Tianjin China

ISBN: (纸本)9781509023974

The rehabilitation exoskeleton robot is more and more used in the assisting stroke patients in implementing rehabilitation training. In this paper, a novel exoskeleton hand robot which was driven by cable has been proposed to aim at helping varieties of paralyses patients recover motor function. This exoskeleton hand rehabilitation robot system mainly consists of exoskeleton hand robot, EEG system, motor controllers unit, some sensors and a workstation. And the hand exoskeleton mechanism was portable, wearable and adjustable for patients doing home rehabilitation training. Based on the parameters from human hand, the kinematic model of hand robot was established to be used in designing and the kinematic simulation experiments about this exoskeleton hand robot were done. Through the simulation software ADAMS (Automatic Dynamic Analysis of Mechanical systems), the parameters of position, angle velocity and angle accelerated velocity (PVA) of proximate inter-phalanger (DIP) distal inter-phalanger joint were simulated. And then, the movement situation of the DIP joint was obtained according to the data from the position encoder. So the velocity curve and accelerated velocity curve were obtained by calculating the actual position function derivation. The simulated results showed that this exoskeleton hand robot has high movement ability to finish the continuous passive motion (CPM). Beside that, a comparison test was done to verify whether there were some motion blocks in wearing exoskeleton robot. Through analyzing the experimental data, the error between the actual position and the simulated position of the PIP joint of the finger was very small which verified the small interference of robot. These experiments demonstrated that the exoskeleton hand robot has high efficiency movement ability for stroke patients who need to do the finger rehabilitation training. In the future, the optimization design of the exoskeleton hand robot will be done in order to improve more mov

关键词： Exoskeletons Thumb Robot sensing systems Joints Training

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Unit Commitment Considering Demand Response Behavior Based on Utility Maximization

Unit Commitment Considering Demand Response Behavior Based o...

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IEEE Conference on Energy Internet and Energy system Integration

作者： Yumin Zhang Xueshan Han Bo Xu Li Zhang Donglei Sun Xiaofeng Miao Jiayin Jiang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment (Department of Electrical Engineering Tsinghua University) Economic & Technology Research Institute of State Grid Shandong Electric Power Company State Grid Shandong Electric Power Company Yantai Electric Power Company

ISBN: (纸本)9781538614280

The active participation of demand side resources in power grid operation not only benefits the individual participant but also benefits the whole system. The optimal goal can promote by excavating the active behaviors of demand side. The welfare maximization of market participant is the driving force of such active behaviors. Considering the independence of each user's behavior, the consumer's utility function is selected to depict consumer's preference and demand response behavior. In order to coordinate the consumers' maximum welfare with social welfare maximization, consumers' utility function and units' operation cost are integrated into Unit Commitment (UC) model. The objective function is to maximize social welfare, by subtracting units' operation cost from consumers' total utility, and this objective can be acquired. Considering the proposed model should be solved in a distributed manner, the idea of the centralized coordination and the decentralized decision-making is proposed. Based on the Lagrangian relaxation (LR) principle and distributed real-time pricing scheme, a closed-loop feedback mechanism is constructed to reflect the relationship among generator output, price level, and load demand. The ten generating units example can illustrate the effectiveness of the proposed method.

关键词： Demand utility Decomposition coordination Electricity market Lagrangian relaxation Real-time pricing Unit commitment

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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A Two-Step Fault Diagnosis Framework for Rolling Element Bearings with Imbalanced Data

A Two-Step Fault Diagnosis Framework for Rolling Element Bea...

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International Conference on Ubiquitous Robots and Ambient Intelligence

作者： Yuan Lan Weiwei Zong Xiaojian Ding Xiaoyan Xiong Xiaohang Han Jiahai Huang Bing Ma Key Laboratory of Ministry of Education in Advance Transducers and Intelligent Control System Institute of Mechatronics Engineering under School of Mechanical Engineering Taiyuan University of Technology Department of Computer Science Wayne State University Science and Technology on Information Systems Engineering Laboratory The Second Research Institute of China Electronic Technology Group Corporation

ISBN: (纸本)9781509008223

Rolling element bearings constitute the key parts on rotating machinery and their fault diagnosis are of great importance. In this paper, a novel Two-Step fault diagnosis framework is proposed to diagnose the status of rolling element bearings with imbalanced data. The Wavelet Packet Transform (WPT) is used to determine the feature vectors. 16-dimensional wavelet packet node energies were extracted from the original datasets as the feature vectors prepared to input to the classifiers. Next, our proposed framework consists of two steps for the fault diagnosis, where Step One makes use of Weighted Extreme Learning Machine (weighted ELM) in an effort to classify the normal or abnormal categories, and Step Two further diagnoses the underlying anomaly in details. The effectiveness of our proposed approach is testified on the raw data collected from the rolling element bearing experiments conducted in our Institute, and the empirical results showed that our approach is really fast and can achieve the diagnosis accuracies more than 95%.

关键词： Two-Step fault diagnosis framework Weighed ELM ELM Bearing fault diagnosis

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A Two-Step Fault Diagnosis Framework for Rolling Element Bearings with Imbalanced Data

A Two-Step Fault Diagnosis Framework for Rolling Element Bea...

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2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Yuan Lan Weiwei Zong Xiaojian Ding Xiaoyan Xiong Xiaohang Han Jiahai Huang Bing Ma Key Laboratory of Ministry of Education in Advance Transducers and Intelligent Control System Institute of Mechatronics Engineering under School of Mechanical EngineeringTaiyuan University of Technology Department of Computer Science Wayne State University Science and Technology on Information Systems Engineering Laboratory The Second Research Institute of China Electronic Technology Group Corporation

Rolling element bearings constitute the key parts on rotating machinery and their fault diagnosis are of great importance. In this paper, a novel Two-Step fault diagnosis framework is proposed to diagnose the status of rolling element bearings with imbalanced data. The Wavelet Packet Transform(WPT) is used to determine the feature vectors. 16-dimensional wavelet packet node energies were extracted from the original datasets as the feature vectors prepared to input to the ***, our proposed framework consists of two steps for the fault diagnosis, where Step One makes use of Weighted Extreme Learning Machine(weighted ELM) in an effort to classify the normal or abnormal categories, and Step Two further diagnoses the underlying anomaly in details. The effectiveness of our proposed approach is testified on the raw data collected from the rolling element bearing experiments conducted in our Institute,and the empirical results showed that our approach is really fast and can achieve the diagnosis accuracies more than 95%.

关键词： Two-Step fault diagnosis framework Weighed ELM ELM Bearing fault diagnosis

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Communication scheduling in robust self-triggered MPC for linear discrete-time systems 5

Communication scheduling in robust self-triggered MPC for li...

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5th IFAC Workshop on Distributed Estimation and control in Networked systems, NecSys 2015

作者： Brunner, Florian D. Gommans, T.M.P. Heemels, W.P.M.H. Allgöwer, Prank Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 Stuttgart70569 Germany Control System Technology Group Department of Mechanical Engineering Eindhoven University of Technology Netherlands

We consider a networked control system consisting of a physical plant, an actuator, a sensor, and a controller that is connected to the actuator and sensor via a communication network. The plant is described by a linear discrete-time system subject to additive disturbances. In order to reduce the required number of communications in the system, we propose a robust self-triggered model predictive controller based on rollout techniques that robustly asymptotically stabilizes a certain periodic sequence of sets in the state space while guaranteeing robust satisfaction of hard state and input constraints. At periodically occurring scheduling times, the self-triggered model predictive control algorithm determines the times at which the control input and plant measurement are updated in the time span until the next scheduling time. We establish a certain upper bound on the average sampling rate in the closed-loop system. Moreover, we show how increasing the asymptotic bound on the system state, which is a design parameter in the control scheme, can be used to further reduce the average number of communications in the system. © 2015, IF AC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Closed loop systems

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Asteroid ryugu before the Hayabusa2 encounter

arXiv

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arXiv 2018年

作者： Wada, Koji Grott, Matthias Michel, Patrick Walsh, Kevin J. Barucci, Antonella M. Biele, Jens Blum, Jürgen Ernst, Carolyn M. Grundmann, Jan T. Gundlach, Bastian Hagermann, Axel Hamm, Maximilian Jutzi, Martin Kim, Myung-Jin Kührt, Ekkehard Le Corre, Lucille Libourel, Guy Lichtenheldt, Roy Maturilli, Alessandro Messenger, Scott R. Michikami, Tatsuhiro Miyamoto, Hideaki Mottola, Stefano Nakamura, Akiko M. Müller, Thomas Nittler, Larry R. Ogawa, Kazunori Okada, Tatsuaki Palomba, Ernesto Sakatani, Naoya Schröder, Stefan Takir, Driss Zolensky, Michael E. Tsudanuma 2-17-1 Narashino Chiba275-0016 Japan DLR Institute for Planetary Research Rutherfordstr. 2 Berlin12489 Germany Université Côte d'Azur Observatoire de la Côte d'Azur CNRS Lagrange Laboratory Southwest Research Institute Boulder United States Observatoire de Paris PSL Research University CNRS Université Paris Diderot Sorbonne Paris Cité UPMC Université Paris 06 Sorbonne Universités 5 Place J. Janssen Meudon Principal Cedex92195 France DLR RB-MSC German Aerospace Center Cologne51147 Germany Institut für Geophysik und extraterrestrische Physik Technische Universität Braunschweig Mendelssohnstr. 3 BraunschweigD-38106 Germany Johns Hopkins University Applied Physics Laboratory LaurelMD United States DLR German Aerospace Center Institute of Space Systems System Engineering and Project Office Robert-Hooke-Strasse 7 BremenD-28359 Germany Department of Biological and Environmental Sciences University of Stirling FK9 4LA United Kingdom Physics Institute University of Bern Switzerland Center for Space Situational Awareness Korea Astronomy and Space Science Institute 776 Daedeokdae-ro Yuseong-gu Daejeon305-348 Korea Republic of Planetary Science Institute 1700 East Fort Lowell Suite 106 TucsonAZ85719 United States DLR Institute of System Dynamics and Control Oberpfaffenhoffen Germany Robert M Walker for Space Sciences Astromaterials Research and Exploration Science NASA Johnson Space Center HoustonTX77058 United States Faculty of Engineering Kindai University Hiroshima Campus 1 Takaya Umenobe Higashi-Hiroshima Hiroshima739-2116 Japan Deptartment of Systems Innovation University of Tokyo Tokyo Japan Department of Planetology Graduate School of Science Kobe University 1-1 Rokkodai Nada-ku Kobe657-8501 Japan Max-Planck Institute for Extraterrestrial Physics Garching Germany Department of Terrestrial Magnetism Carnegie Institution of Washington 5241 Broad Branch Rd NW 20015 United States Institute of Space and Astronautical Sc

Asteroid (162173) Ryugu is the target object of Hayabusa2, an asteroid exploration and sample return mission led by Japan Aerospace Exploration Agency (JAXA). Ground-based observations indicate that Ryugu is a C-type near-Earth asteroid with a diameter of less than 1 km, but the knowledge of its detailed properties is still very limited. This paper summarizes our best understanding of the physical and dynamical properties of Ryugu based on remote sensing and theoretical modeling. This information is used to construct a design reference model of the asteroid that is used for formulation of mission operations plans in advance of asteroid arrival. Particular attention is given to the surface properties of Ryugu that are relevant to sample acquisition. This reference model helps readers to appropriately interpret the data that will be directly obtained by Hayabusa2 and promotes scientific studies not only for Ryugu itself and other small bodies but also for the Solar system evolution that small bodies shed light on. Copyright © 2018, The Authors. All rights reserved.

关键词： Asteroids

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Congestion management in deregulated electricity market using FACTS & multi-objective optimization

Congestion management in deregulated electricity market usin...

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Indian control Conference (ICC)

作者： Vrushali Khatavkar Madhuri Namjoshi Anjali Dharme PHD in restructured and deregulated power systems from Bharti Vidyapeeth pune Department of Electrical Engineering Progressive Education Society's Modern College of Engineering Pune India Master's degree in Control Systems from Progressive Education Society's modern College of Engineering Pune Indian Navy as Lieutenant Commander and also worked in MANIT Bachelor of Engineering degree in Electrical Engineering from Maulana Azad National Institute of Technology Bhopal Degree in electrical engineering University of Pune India Electrical power system Restructuring and deregulation Micro-grid Distribution system Demand side management and energy conservation

This paper presents placement of FACTS controllers by using genetic algorithm for single objective optimization and strength Pareto evolutionary algorithm for three objective optimization simultaneously in power systems. The testing is done using Matlab on IEEE 30 bus system. Placement of two types of FACT devices is carried out for single objective optimization three objective optimization and the result of the three objective optimization are compared with the base case. The system is uniformly loaded for optimization at 110 % and 120%. Two FACTS are considered for placement i) TCSC Thyristor controlled series capacitor ii) SVC (Static Var compensator) in order to improve the branch loading index of the system, reduce losses and improve the voltage stability index. The placement of FACTs is obtained with location, type and value.

关键词： Optimization Linear programming Thyristors Static VAr compensators Power system stability Power capacitors Sociology

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A comparative study on D converter based on control schemes of maximum extracted power

A comparative study on D converter based on control schemes ...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ahmad El Khateb M.N. Uddin N. A. Rahim Barry W. Williams Automatic Control and Human-Machine Systems LAMIH UMR/CNRS Valenciennes France Electronic Engineering Department Tsinghua University Tsinghua National Laboratory for Information Science and Technology (TNList) Beijing P. R. China Shenzhen City Key Laboratory of Digital TV System Valeo Powertrain Systems Amiens France National Engineering Lab. for DTV(Beijing) Beijing P. R. China

ISBN: (纸本)9781479983988

This paper presents analysis and control of D converter, which has continuous input and output current to obtain maximum power transfer from a photovoltaic (PV) system. Examining the maximum power involves optimization and control techniques that ensure maximum power extraction enhancement. Traditional converters have rather high input ripple current that originates considerable loss of power extraction when linked to photovoltaic panels. Operating with zero input ripple current enlarges the power obtained from the PV panel without employing electrolytic capacitor. Experiment and simulation of the converter performance support and extol the system concept and establish a balanced view among several types of used controllers as well.

关键词： Inverters Capacitors Photovoltaic systems Radiation effects control systems Fuel cells

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