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8th International Conference on Integrated Modeling and Analysis in Applied Control and automation, IMAACA 2015

作者： Moustris, George P. Dometios, Athanasios Tzafestas, Costas S. Intelligent Robotics and Automation Laboratory School of Electrical and Computer Engineering National Technical University of Athens Greece

ISBN: (纸本)9788897999546

We present a robot following behavior, which enables a mobility assistance robot to follow the user from the front. Although this behavior is desirable in various circumstances, it has received scarce attention. Our proposed solution consists of a kinematic control scheme, tied to a human position estimator based on a Laser Range Finder. Experiments have been performed in an indoor environment with ten users, and the results have been analyzed and presented. We show that the control is feasible but inserts a cognitive load on the users, who tend to "drive" the robot to the optimal paths they would take under normal conditions.

关键词： Robots

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Distributed multi-agent optimization subject to nonidentical constraints and communication delays

Distributed multi-agent optimization subject to nonidentical...

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作者： Lin, Peng Ren, Wei Song, Yongduan School of Electronic and Information Engineering Xi'An Jiaotong University China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering University of California Riverside United States Key Laboratory of Dependable Service Computing Cyber Physical Society Ministry of Education Chongqing University China School of Automation Chongqing University China

In this paper, we study a distributed optimization problem using a subgradient projection algorithm for multi-agent systems subject to nonidentical constraints and communication delays under local communication. Here the agents capable of communicating with their local neighbors are constrained to remain in possibly different closed convex sets and optimize a global objective function composed of a sum of local objective functions, each of which is known to only one agent. First, we consider the case of fixed graphs and show that distributed optimization might not be achieved on general strongly connected directed graphs. Instead, the agents optimize a weighted sum of the local objective functions. Then we consider the case of switching graphs and show that distributed optimization can be achieved when the adjacency matrices are doubly stochastic and the union of the directed graphs is strongly connected among each time interval of a certain bounded length. Furthermore, we consider the case of communication delays, where the delays are mutually independent. It is shown that the distributed optimization problem can be solved by introducing additional delays to the subgradient projection algorithm and the communication delays can be arbitrarily bounded. Finally, numerical examples are included to show the obtained theoretical results. © 2015 Elsevier Ltd. All rights reserved.

关键词： Multi agent systems

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Plant model inference for closed-loop verification of control systems: Initial explorations 14th

Plant model inference for closed-loop verification of contro...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Igor Buzhinsky Valeriy Vyatkin Computer Technologies Laboratory ITMO University St. Petersburg Russia Department of Electrical Engineering and Automation Aalto University Finland Department of Computer Science Luleå University of Technology Sweden

ISBN: (纸本)9781509028719

Closed-loop model checking, a formal verification technique for industrial automation systems, increases the richness of specifications to be checked and often helps to reduce size of the state space to be verified compared with the open-loop case. To be applied, it needs two components - the controller and the plant models - to be coupled. While there are approaches for obtaining controller models from implementation, specification or behavior examples, little has been done regarding automation of plant model construction. This paper aims to solve the problem of automatic plant model construction from existing specification, which is represented in the form of plant behavior examples and temporal properties.

关键词： Automata Solid modeling automation Software Control systems Aerospace electronics Model checking

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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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Cyber-physical Modeling and Control of Crowd of Pedestrians:A Review and New Framework

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IEEE/CAA Journal of Automatica Sinica 2015年第3期2卷 334-344页

作者： Kecai Cao Yangquan Chen Dan Stuart Dong Yue the College of Automation Nanjing University of Posts and Telecommunications Mechatronics Embedded Systems and Automation Laboratory School of EngineeringUniversity of California the Department of Electrical and Computer Engineering Utah State University

Recent advances in modeling and control of crowd of pedestrians are briefly surveyed in this paper. Possibilities of applying fractional calculus in the modeling of crowd of pedestrians have been shortly reviewed and discussed from different aspects such as descriptions of motion, interactions of long range and effects of memory. Control of the crowd of pedestrians have also been formulated using the framework of cyber-physical systems and been realized using networked Segways with onboard emergency response personnels to regulate the velocity and flux of the crowd. Platform for verification of the theoretical results are also provided in this paper. © 2014 Chinese Association of automation.

关键词： Calculations Embedded systems

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Communication-efficient weighted ADMM for decentralized network optimization

Communication-efficient weighted ADMM for decentralized netw...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Qing Ling Yaohua Liu Wei Shi Zhi Tian Department of Automation University of Science and Technology of China Coordinated Science Laboratory University of Illinois at Urbana-Chamnaign Department of Electrical and Computer Engineering George Mason University

ISBN: (纸本)9781479999897

In this paper, we propose a weighted alternating direction method of multipliers (ADMM) to solve the consensus optimization problem over a decentralized network. Compared with the conventional ADMM that is popular in decentralized network optimization, the weighted ADMM is able to tune its weight matrices for the purpose of reducing the communication cost spent in the optimization process. We first prove convergence and establish linear convergence rate of the weighted ADMM. Second, we maximize the derived convergence speed and obtain the best weight matrices on a given topology. Third, observing that exchanging information with all the neighbors is expensive, we maximize the convergence speed while limit the number of communication arcs. This strategy finds a subgraph within the underlying topology to fulfill the optimization task and leads to a favorable tradeoff between the number of iterations and the communication cost per iteration. Numerical experiments demonstrate advantages of the weighted ADMM over its conventional counterpart in expediting the convergence speed and reducing the communication cost.

关键词： Convergence Linear programming Optimization Nickel Symmetric matrices Topology Decision making

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Multimodal Fusion of Brain Imaging Data: A Key to Finding the Missing Link(s) in Complex Mental Illness

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Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2016年第3期1卷 230-244页

作者： Calhoun, Vince D. Sui, Jing Mind Research Network Lovelace Biomedical and Environmental Research Institute Albuquerque NM United States Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM United States Brainnetome Center National Laboratory of Pattern Recognition Beijing China Chinese Academy of Sciences Center for Excellence in Brain Science Institute of Automation Beijing China

It is becoming increasingly clear that combining multimodal brain imaging data provides more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e., capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multimodal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this article, we start by introducing the basic reasons why multimodal data fusion is important and what it can do and, importantly, how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multimodal fusion including deep learning and multimodal classification that show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential to mitigate misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. © 2016 Society of Biological Psychiatry.

关键词： Brain function Connectivity Data fusion Independent component analysis Psychosis Schizophrenia

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Exploring the use of coupled oscillators for humanoid gait control 2

Exploring the use of coupled oscillators for humanoid gait c...

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2014 Joint Conference on 2nd SBR Brazilian robotics Symposium, 11th LARS Latin American robotics Symposium and 6th Robocontrol Workshop on Applied robotics and automation, SBR LARS Robocontrol 2014

作者： Ramos, Felipe Moreira Bo, Antonio Padilha Lanari Laboratory of Automation and Robotics Department of Electrical Engineering University of Brasília Brasília Brazil

ISBN: (纸本)9781479967117

The dream of a world where robots assist and cooperate with humans has long inhabits the imagination of our society. In books and movies, the relationship between people and artificial beings has assumed tragic proportions, for example when the machines rebelled against humanity. In other works, however, robots with high intelligence and skill gently help people in many tasks. Currently, industrial robots are employed in the areas of handling and transport, involving manipulator arms and automatic transport vehicles. Seeking go a step further, this project aims to develop techniques using coupled oscillators that enable robots to move in ambients made for humans while interacting with them. © 2014 IEEE.

关键词： Anthropomorphic robots

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Linearized PID control in a nonlinear model of an active hydromagnetic journal bearing

Linearized PID control in a nonlinear model of an active hyd...

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作者： Farmakopoulos, Michael G Thanou, Michalis D Nikolakopoulos, Pantelis G Papadopoulos, Chris A Tzes, Anthony P Machine Design Laboratory Department of Mechanical Engineering and Aeronautics University of Patras Patras26504 Greece Automation and Robotics Laboratory Electrical and Computer Engineering Department University of Patras Patras Greece

A proportional-integral-derivative (PID) control model of an active hydromagnetic journal bearing (AHJB) is presented here and its design guidelines are explicitly described. The nonlinear rotor equations of motion, is introduced. Then, the linearization of these equations in the bearing specific equilibrium point is performed and presented along with the appropriate PID gains. Consequentially, the linear equation is transformed via Laplace method and the control model of the AHJB is finally developed. The multiphysics module of Ansys is used to calculate the forces that the hydrodynamic lubrication applies to the rotor, in every position of the rotor, during its movement inside the bearing. This has been done, in order not to have linear equations of the hydrodynamic forces, but the real, nonlinear equations. The nonlinear equations are used for the electromagnetic forces too. The Matlab software is used to simulate the components that the AHJB is consisted of. The P, I, and D gains are the obtained results of this simulations, which are produced via robust control method, in single-input-single-output tool module. Finally, the Simulink module of Matlab is energized to check the control characteristics of the developed AHJB system, taking into account the nonlinear equations of motion of the system, in combination with the rotor unbalance and gyroscopic effects and the saturation of the coils. The rotor response, the overshoot, the rotor center vibration are controlled using the above produced P, I, and D gains. Several plots are constructed and presented, such as the rotor orbits, to show the possibility of the AHJB control. © 2014 IMechE.

关键词： Simulink

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Data-Driven PID Controller and its Application to Pulp Neutralization Process

Data-Driven PID Controller and its Application to Pulp Neutr...

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第27届中国过程控制会议（CPCC2016）

作者： Yajun Zhang Tianyou Chai Dianhui Wang Yao Jia Wei Dai Key Laboratory of Synthetical Automation for Process Industries (Northeastern University) Department of Computer Science and Information Technology Engineering La Trobe University Department of Information and Electrical Engineering China University of Mining and Technology

The pulp neutralization process is a classic complex industrial process with strong nonlinear and *** processes generally cannot be controlled well using the traditionalproportional-integral-derivative(PID) controller because of the linear feature of that control *** on this problem,a novel PID controlmethod is proposed by integrating multiple technologies,namely,data-driven compensation of un-modelled dynamicsand multi-step ahead of optimal *** the new PID control structure,the measured data from the pulp neutralizationprocess and the historical data from the unmodelled dynamics are fully used,and a data-based unmodelled dynamicscompensator is integrated with a feedback *** the performance of the proposed algorithm further,its stability and convergence are ***,the proposed approach is applied to a cobalt nickel hydroxide pulpneutralization process to solve the problem of the p H value under random disturbances caused by total acid flow duringautoclave leaching,residual acid flow,and feeding pulp p H ***,the simulations are carried out using data froman actual pulp neutralization process,and then industrial experiments confirm the simulation conclusion:the p H value ofthe pulp neutralization process can be effectively maintained within the desired technical range with slight fluctuations.

关键词： Data-Driven PID Controller and its Application to Pulp Neutralization Process Controller

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