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arXiv 2017年

作者： Tyukin, Ivan Yu. Gorban, Alexander N. Sofeikov, Konstantin I. Romanenko, Ilya University of Leicester Department of Mathematics University Road LeicesterLE1 7RH United Kingdom Department of Automation and Control Processes St. Petersburg State University of Electrical Engineering Prof. Popova str. 5 Saint-Petersburg197376 Russia UnivAI Ltd 5 Park Court Pyrford Road West Byfleet KT14 6SD United Kingdom Imaging and Vision Group ARM Ltd 1 Summerpool Rd Loughborough LE11 5RD United Kingdom

We consider the fundamental question: how a legacy "student" Artificial Intelligent (AI) system could learn from a legacy "teacher" AI system or a human expert without complete re-training and, most importantly, without requiring significant computational resources. Here "learning" is understood as an ability of one system to mimic responses of the other and vice-versa. We call such learning an Artificial Intelligence knowledge transfer. We show that if internal variables of the "student" Artificial Intelligent system have the structure of an n-dimensional topological vector space and n is sufficiently high then, with probability close to one, the required knowledge transfer can be implemented by simple cascades of linear functionals. In particular, for n sufficiently large, with probability close to one, the "student" system can successfully and non-iteratively learn k n new examples from the "teacher" (or correct the same number of mistakes) at the cost of two additional inner products. The concept is illustrated with an example of knowledge transfer from a pre-trained convolutional neural network to a simple linear classifier with HOG *** Codes 68T05, 68T30 Copyright © 2017, The Authors. All rights reserved.

关键词： Knowledge management

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Coordination control of dual-arm robot based on modeled predictive control

Coordination control of dual-arm robot based on modeled pred...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Ming Jiang Ming-Qu Fan Ai-Min Li Xue-Wen Rong Hui Kong Rui Song College of Electronic Communication and Physics Shandong University of Science and Technology Qingdao China College of Electrical Engineering and Automation Shandong University of Science and Technology Jinan China Shandong University of Science and Technology Qingdao Shandong CN School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9781467389600

This paper presents a master-slave force hybrid coordinated motion control method which is based on the model predictive control (MPC) algorithm. In the paper, the kinematics model of the dual 6-DOF arms is build. Six axis force sensors are installed at the ends of the two arms, the master arm adopts the position control method and the based on the model predictive control algorithm DMC theory force/position hybrid control method is adopted in the slave arm. According to the kinematic model of the dual-arms, the end pose and joint angle rule conversion library is established, and the motion prediction model of the manipulator also is established. By using these models, the slave arm can acquire the position and direction of the master arm synchronously, and the current end position of the master arm is also used as the reference input value of the end position of the slave arm. The rotation operation sequence of the joint angle rule conversion library predicted model and end pose apply to the joint motor, drive the end of the robot arm to move to the target position. After doing these we could synchronously realize position tracking. In our experiment the current position tracking could be realized through the simulation analysis of six degree of freedom dual arm robot.

关键词： Handheld computers Decision support systems Conferences Real-time systems Robots

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Odor sources mapping with D-S inference in time variant airflow environments via a mobile robot 5

Odor sources mapping with D-S inference in time variant airf...

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5th Annual IEEE International Conference on Cyber Technology in automation, control and Intelligent Systems, IEEE-CYBER 2015

作者： Li, Ji-Gong Zhou, Jie-Yong Biao, Sun Jia, Liu Li, Yang School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China School of Electrical Engineering and Automation Tianjin University Tianjin China Tianjin Key Laboratory of Process Measurement and Control Tianjin China

ISBN: (纸本)9781479987290

This paper addresses the problem of localization of multiple odor sources using a mobile robot in a time-variant airflow environment, and provides a mapping method which uses the Dempster-Shafer (D-S) theory to reason the possible locations of several odor sources. In the proposed method, the robot carries out the D-S inference and iteratively updates a grid map in which each cell has two states (i.e., occupied by an odor source, and not occupied by odor source), using the successive measurements from a gas sensor and an anemometer when the robot is cruising in the given search area. Considering the fact that in outdoor environments air almost always flow and vary with time, estimated air-mass paths are used to construct the belief mass functions of the D-S inference. Here the air-mass path is defined as the trajectory most likely taken by an air mass encountered with the mobile robot in a time-varying airflow environment, and an air mass can contain odor molecules and bring them to the robot, or not contain odor molecule and just pass by the robot. Simulations are carried out and the results in a time-variant airflow environment show that the locations of the multiple odor sources can be mapped online with the proposed method. © 2015 IEEE.

关键词： Mobile robots

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Estimation for power quality frequency based on a variable-step ANF algorithm 10

Estimation for power quality frequency based on a variable-s...

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10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015

作者： Su, Junsen Jie, Gao Zheng, Changbao Hu, Cungang School of Electrical Engineering and Automation Anhui University Hefei China National Engineering Laboratory of Energy-Saving Motor and Control Technology Anhui University Hefei China

ISBN: (纸本)9781467373173

In this paper, a variable-step ANF for estimation of power quality frequency is presented. This algorithm is fast and accurate. It still get a satisfied result under a high sampling rate. The algorithm of adaptive IIR notch filter with variable-step is presented in detail, and some variable-step method is presented. At last, the simulation is performed by Matlab and the result is compared under different SNR. © 2015 IEEE.

关键词： Frequency estimation

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A novel policy iteration based deterministic Q-learning for discrete-time nonlinear systems

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Science China Chemistry 2015年第12期58卷 143-157页

作者： WEI QingLai LIU DeRong State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing

In this paper, a novel iterative Q-learning algorithm, called "policy iteration based deterministic Qlearning algorithm", is developed to solve the optimal control problems for discrete-time deterministic nonlinear systems. The idea is to use an iterative adaptive dynamic programming(ADP) technique to construct the iterative control law which optimizes the iterative Q function. When the optimal Q function is obtained, the optimal control law can be achieved by directly minimizing the optimal Q function, where the mathematical model of the system is not necessary. Convergence property is analyzed to show that the iterative Q function is monotonically non-increasing and converges to the solution of the optimality equation. It is also proven that any of the iterative control laws is a stable control law. Neural networks are employed to implement the policy iteration based deterministic Q-learning algorithm, by approximating the iterative Q function and the iterative control law, respectively. Finally, two simulation examples are presented to illustrate the performance of the developed algorithm.

关键词： adaptive critic designs adaptive dynamic programming approximate dynamic programming Q-learning policy iteration neural networks nonlinear systems optimal control

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Author Correction: A consensus protocol for functional connectivity analysis in the rat brain

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Nature neuroscience 2023年 2023 Apr 18页

作者： Joanes Grandjean Gabriel Desrosiers-Gregoire Cynthia Anckaerts Diego Angeles-Valdez Fadi Ayad David A Barrière Ines Blockx Aleksandra Bortel Margaret Broadwater Beatriz M Cardoso Marina Célestine Jorge E Chavez-Negrete Sangcheon Choi Emma Christiaen Perrin Clavijo Luis Colon-Perez Samuel Cramer Tolomeo Daniele Elaine Dempsey Yujian Diao Arno Doelemeyer David Dopfel Lenka Dvořáková Claudia Falfán-Melgoza Francisca F Fernandes Caitlin F Fowler Antonio Fuentes-Ibañez Clément M Garin Eveline Gelderman Carla E M Golden Chao C G Guo Marloes J A G Henckens Lauren A Hennessy Peter Herman Nita Hofwijks Corey Horien Tudor M Ionescu Jolyon Jones Johannes Kaesser Eugene Kim Henriette Lambers Alberto Lazari Sung-Ho Lee Amanda Lillywhite Yikang Liu Yanyan Y Liu Alejandra López-Castro Xavier López-Gil Zilu Ma Eilidh MacNicol Dan Madularu Francesca Mandino Sabina Marciano Matthew J McAuslan Patrick McCunn Alison McIntosh Xianzong Meng Lisa Meyer-Baese Stephan Missault Federico Moro Daphne M P Naessens Laura J Nava-Gomez Hiroi Nonaka Juan J Ortiz Jaakko Paasonen Lore M Peeters Mickaël Pereira Pablo D Perez Marjory Pompilus Malcolm Prior Rustam Rakhmatullin Henning M Reimann Jonathan Reinwald Rodrigo Triana Del Rio Alejandro Rivera-Olvera Daniel Ruiz-Pérez Gabriele Russo Tobias J Rutten Rie Ryoke Markus Sack Piergiorgio Salvan Basavaraju G Sanganahalli Aileen Schroeter Bhedita J Seewoo Erwan Selingue Aline Seuwen Bowen Shi Nikoloz Sirmpilatze Joanna A B Smith Corrie Smith Filip Sobczak Petteri J Stenroos Milou Straathof Sandra Strobelt Akira Sumiyoshi Kengo Takahashi Maria E Torres-García Raul Tudela Monica van den Berg Kajo van der Marel Aran T B van Hout Roberta Vertullo Benjamin Vidal Roël M Vrooman Victora X Wang Isabel Wank David J G Watson Ting Yin Yongzhi Zhang Stefan Zurbruegg Sophie Achard Sarael Alcauter Dorothee P Auer Emmanuel L Barbier Jürgen Baudewig Christian F Beckmann Nicolau Beckmann Guillaume J P C Becq Erwin L A Blezer Radu Bolbos Susann Boretius Sandrine Bouvard Eike Budinger Joseph D Buxbaum Diana Cash Victor Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands. joanes.grandjean@radboudumc.nl. Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands. joanes.grandjean@radboudumc.nl. Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada. Integrated Program in Neuroscience McGill University Montreal QC Canada. Bio-imaging Lab University of Antwerp Antwerp Belgium. µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium. Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico. Biological and Biomedical Engineering McGill University Montreal QC Canada. McConnell Brain Imaging Centre McGill University Montreal QC Canada. Montreal Neurological Institute McGill University Montreal QC Canada. UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France. Department of Neurology and Neurosurgery McGill University Montreal QC Canada. Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA. Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA. Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA. Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal. Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France. Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México. Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cyberneti

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Sliding Mode control for Mars Entry with Flatness and Extended State Observer 34

Sliding Mode Control for Mars Entry with Flatness and Extend...

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第三十四届中国控制会议

作者： LU Kunfeng XIA Yuanqing YU Chunmei ZHOU Liuyu Beijing Aerospace Automatic Control Institute National key laboratory of science and technology on aerospace intelligent control School of Automation Beijing Institute of Technology Aerospace and Materials Engineering National University of Defense Technology Electrical Engineering Stanford University

ISBN: (纸本)9781467374439

This paper addresses high-precision Mars entry guidance and control approach via sliding mode control(SMC) and Extended State Observer(ESO). First, differential flatness(DF) approach is applied to the dynamic equations of the entry *** presented control law requires no information on high uncertainties that are estimated by ESO. Finally, simulation results are presented to demonstrate the effectiveness of the proposed approach.

关键词： Mars entry guidance and control,sliding mode control,Extended State Observer,Monte Carlo

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Guest Editorial for Special Issue on Cyber-Physical Systems

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IEEE/CAA Journal of Automatica Sinica 2015年第3期2卷 233-234页

作者： Youxian Sun Xinping Guan Jiming Chen Yilin Mo Zhejiang University the Chinese Academy of Engineering the Institute of Industrial Process Control and the National Engineering Research Center of Industrial Automation Zhejiang University Department of Automation Shanghai Jiao Tong University University Research Management Office Shanghai Jiao Tong University the Key Laboratory of Systems Control and Information Processing Ministry of Education of China the prestigious Innovative Research Team of the National Natural Science Foundation of China(NSFC) Department of Control Science and Engineering group of Networked Sensing and Control in the State Key laboratory of Industrial Control Technology Institute of Industrial Process Control at Zhejiang University the School of Electrical and Electronic Engineering at Nanyang Technological University

Ⅰ.Introduction CYBER-PHYSICAL system is a system of collaborating computational elements to control physical *** coordination and the tight link between computational,virtual and physical resources in cyber-physical system will have a pervasive effect on our everyday *** development of cyber-physical system will create new opportunities for the introduction of services that will enhance the quality of life

关键词： for WSAN Guest Editorial for Special Issue on Cyber-Physical Systems of into on WSN is

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Attitude synchronization of multiple rigid bodies in SE(3) over proximity networks

Attitude synchronization of multiple rigid bodies in SE(3) o...

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第35届中国控制会议

作者： Juan Deng Zhixin Liu Lin Wang John S.Baras Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceCAS Department of Automation Shanghai Jiao Tong Universityand the Key Laboratory of System Control and Information ProcessingMinistry of Education Department of Electrical and Computer Engineering and the Institute for Systems Research University of MarylandCollege Park

ISBN: (纸本)9781509009107

This paper investigates the attitude synchronization of a group of moving rigid bodies whose states including positions and rotation matrices evolve in the Lie group SE(3).The commonly used circular neighborhood is adopted,and the neighbor graphs are described by proximity *** order to avoid introducing discussions on the abrupt changes of neighbor graphs,a dwell time is *** distributed sampled-data control law for the angular velocity is *** the assumptions on the initial states,we provide sufficient conditions for the attitude synchronization of multiple rigid body *** with the existing results,our condition depends only on the neighborhood radius,the moving velocity and the dwell time.

关键词： rigid body SE(3) attitude synchronization sampled-data control proximity network

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Soil resistivity study and simulation with finite elements method

Soil resistivity study and simulation with finite elements m...

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IEEE International Conference on Environment and electrical engineering

作者： Thiago Martins Pereira Rodrigo Alves de Lima Viviane Margarida Gomes Sóstenes Gutembergue Aylton José Alves Wesley Pacheco Calixto Electrical Mechanical & Computer Engineering School EMC Federal University of Goias UFG Experimental & Technological Research and Study Group NExT Federal Institute of Goias IFG Program in Electronic Systems and Automation PGEA University of Brasilia UnB

ISBN: (纸本)9781509023219

This work purpose is to study the influence of concrete buried structures in grounding systems. Comparison of soil characteristics between dry and rainy seasons and soil electrical behavior was carried out. Simulations in finite element method was performed for tree layer stratified soil and the electrostatic equipotential surfaces were mapped into the region of interest.

关键词： Grounding systems finite elements method climate seasonality

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