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第25届中国过程控制会议

作者： Qifeng Tang Dewei Li Yugeng Xi Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information ProcessingMinistry of Education

Soft sensing has been widely used in chemical industry to build an online monitor of the variables which are unmeasurable online or measurable online but with a high ***,one inherent difficulty is insufficiency of the training samples because the labeled data is *** this,the traditional soft-sensing structure has no online correction *** forecasting result may be incorrect if the working condition is *** this work,a semi-supervised method is proposed to build the soft-sensing model by use of the unlabeled ***,an online correction mechanism is proposed to establish a soft-sensing approach,which estimates the input variables at each step by a prediction model and calibrates the output variables by a compensation *** experimental results show that the proposed method has better prediction accuracy and generalization ability than other approaches.

关键词： soft-sensing,semi-supervised learning(SSL),online correction,neural network(NN).

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Distributed stretching control of web production system

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Journal of Donghua University (English Edition) 2014年第2期31卷 141-146页

作者： Li, Xiao-Li Ren, Li-Hong Liu, Hao College of Information Science and Technology Donghua University Shanghai 201620 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China

The stretching process, as a key phase of web production system, pursues the target velocities of rollers and the web tensions of spans between the successive rollers to guarantee proper stretching ratios. This requires the stable velocities and velocity ratios of large number rollers separated throughout the workshop. To this goal, a distributed cooperative controller is designed to coordinate the velocities of the rollers to the desired values as well as the target ratios between the upper and lower rollers. During the whole evolution, only the neighbor rollers can exchange the working information, and neither global information nor central controller is required. It is proven that all the rollers asymptotically achieve the desired velocity ratios via the proposed control law, which is also demonstrated by numerical simulation. Copyright © 2014.

关键词： Velocity

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Energy-aware effectiveness analysis in two-link MIMO networks

Energy-aware effectiveness analysis in two-link MIMO network...

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World Congress on Intelligent control and Automation (WCICA)

作者： Zhenzhe Sun Jing Wu Chengnian Long Dept. of Automation Key Lab. of System Control and Information Processing

This paper investigates energy effectiveness problem for 802.11 n+ protocol in heterogeneous MIMO networks. Specifically, we consider a two-link network, where a 2 × 2 MIMO link transmits concurrently with an 1 × 1 link. We show that the completely cancelling out all the interference may result in an ineffective transmission for the incoming link. It consumes much energy on eliminating interference but achieving low transmission rate. Based on the observation, we propose a compromising nulling approach to mitigate the energy effectiveness problem. Compromising nulling takes an energy metric for transmission and interference design, which can be converted into an optimal pre-coding design problem. Numerical results show that compromising nulling strikes a balance between interfering other transmissions and maintain its own transmission effectiveness.

关键词： Interference Measurement Signal to noise ratio MIMO Blogs Antennas Receivers

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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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Descriptor systems State-space Conditions to Guarantee Negative Imaginary Properties without Minimality Restrictions

Descriptor Systems State-space Conditions to Guarantee Negat...

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IEEE Annual Conference on Decision and control

作者： Junlin Xiong Alexander Lanzon Ian R. Petersen CAS Key Lab of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei 230026 China Control Systems Centre School of Electrical and Electronic Engineering University of Manchester Manchester M13 9PL U.K. School of Engineering and Information Technology University of New South Wales at the Australian Defence Force Academy Canberra ACT 2600 Australia

ISBN: (纸本)9781479978878

This paper is concerned with negative imaginary lemmas for descriptor systems. Without the minimal state-space realization assumption, sufficient conditions are developed for a negative imaginary lemma and a strictly negative imaginary lemma, respectively. As corollaries, sufficient conditions are derived to ensure the systems are both admissible and negative imaginary. Also, new sufficient negative imaginary lemmas are found for standard linear systems as special cases. The developed negative imaginary lemmas are applicable to descriptor systems with impulse modes. Two examples are used to illustrate the theory.

关键词： Theorem Negative Linear system Descriptors Lemma Sufficient conditions

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Flocking of partially-informed multi-agent systems avoiding obstacles with arbitrary shape

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Autonomous Agents and Multi-Agent systems 2014年第5期29卷 943-972页

作者： Li, Jiaojie Zhang, Wei Su, Housheng Yang, Yupu Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Measurement and Control Technology Shanghai Dian Ji University Shanghai China School of Automation Key Laboratory of Image Information Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education National Key Laboratory of Science and Technology on Multispectral Information Processing Huazhong University of Science and Technology Wuhan China

In this paper, we study the flocking problem of multi-agent systems with obstacle avoidance, in the situation when only a fraction of the agents have information on the obstacles. Obstacles of arbitrary shape are allowed, no matter if their boundary is smooth or non-smooth, and no matter it they are convex or non-convex. A novel geometry representation rule is proposed to transfer obstacles to a dense obstacle-agents lattice structure. Non-convex regions of the obstacles are detected and supplemented using a geometric rule. The uninformed agents can detect a section of the obstacles boundary using only a range position sensor. We prove that with the proposed protocol, uninformed agents which maintain a joint path with any informed agent can avoid obstacles that move uniformly and assemble around a point along with the informed agents. Eventually all the assembled agents reach consensus on their velocity. In the entire flocking process, no distinct pair of agents collide with each other, nor collide with obstacles. The assembled agents are guaranteed not to be lost in any non-convex region of the obstacles within a distance constraint. Numerical simulations demonstrate the flocking algorithm with obstacle avoidance both in 2D and 3D space. The situation when every agent is informed is considered as a special case.

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Virtual simulation and driver evaluation platform for smart wheelchairs

Communications in Computer and Information Science

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Communications in Computer and information Science 2014年 461卷 307-318页

作者： Liu, L. Wang, Jingchuan Chen, Weidong Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9783662452820

Driver training systemfor disable and elderly people to use electric wheelchairs has an important role for their independent mobility. In this paper a simulator platform of smart wheelchairs is presented for driver training and evaluation. Based on the smart wheelchair, integrated with kinematics, dynamics, sensors, and the 3D model of real wheelchairs and environment, it is implemented in Gazebo and ROS. The sensors inlcude an encoder, a laser range finder and a set of Kinect. Without nursing staff’s company, the user could complete driver training and assessment procedures by himself. Experiments verify that this platform can be used as a valid tool for driver training and evaluation. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Wheelchairs

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Semi-supervised Fisher-Markov Selector via Manifold Regularization

Semi-supervised Fisher-Markov Selector via Manifold Regulari...

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2012 International Conference on Applied Informatics and Communication(ICAIC 2012)

作者： Dong Chen Lin Zhu JieYang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China

Feature subset selection is an important approach to deal with high-dimensional data. But selecting the best subset of data is NP hard. So most of feature selection methods cannot handle high-dimensional data efficiently, or they can only obtain local optimum instead of global optimum. In these cases, when the data consist of both labeled and unlabeled data, semi-supervised feature selection can make full use of data information. In this paper, we introduce a novel semi-supervised feature selection algorithm, which is a filter method based on Fisher-Markov selector, thus ours can achieve global optimum and computational efficiency under certain kernels.

关键词： Feature selection, Dimensionality reduction, Manifold regularization, Semi-supervised learning

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Compound Fuzzy PID control for Thrust Hydraulic system of Hard Rock Tunnel Boring Machine

Compound Fuzzy PID Control for Thrust Hydraulic System of Ha...

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第25届中国过程控制会议

作者： Huajiang Liu Jingcheng Wang Langwen Zhang Guanglei Zhao Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of China

This paper presents a compound fuzzy PID control strategy for the thrust hydraulic control system of hard rock tunnel boring *** dynamic mathematical model of thrust hydraulic system is built and implemented in DSHplus software *** control strategy of speed and pressure is proposed to handle the control problem of thrust hydraulic *** logic PID technique is adopted to deal with the nonlinearity of the thrust hydraulic *** are carried out to verify the performance of proposed compound control strategy.

关键词： Hard Rock TBM Thrust hydraulic system DSHplus Compound control

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Dynamic Modeling and Trajectory Tracking control of Tunnel Boring Machine

Dynamic Modeling and Trajectory Tracking Control of Tunnel B...

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第26届中国控制与决策会议

作者： Huajiang Liu Jingcheng Wang Langwen Zhang Ling Fei Guanglei Zhao Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

ISBN: (纸本)9781479937097

In this paper, we investigate the dynamic modeling and trajectory tracking control of hard rock Tunnel Boring Machine(TBM). The acceleration equation, moment of momentum equation, kinematics equation and orientation equation of TBM are built up. The dynamic mathematical model of TBM attitude is presented by composing of these four equations. The model provides a foundation for the trajectory tracking control of TBM behavior. Fuzzy PID controller is used to design velocity controller, vertical controller and lateral controller. The effectiveness of the proposed methods is shown by illustrative example.

关键词： Hard Rock TBM,Dynamic modeling,Trajectory tracking control,Fuzzy PID

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