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IEEE International Conference on automation Science and engineering (CASE)

作者： Ancai Zhang Jianlong Qiu Chaomin Luo Chengdong Yang Zhenxing Li School of Automation and Electrical Engineering Linyi University Linyi Shandong China Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong (Linyi University) Linyi Shandong China Department of Electrical and Computer Engineering University of Detroit Mercy MI USA School of Information Science and Engineering Linyi University Linyi Shandong China

This paper discusses the motion trajectory design and tracking control problem for an underactuated mechanical system called Furuta pendulum. Firstly, the dynamic equations of a Furuta pendulum system are given. And the dynamic properties of this mechanical system are analyzed. Secondly, we construct a trajectory for the Furuta pendulum in its motion space based on the analysis properties. Afterwards, a tracking controller is designed to track the constructed motion trajectory. This guarantees the stabilization of the Furuta pendulum from an initial point to an objective point to be achieved. To demonstrate the validity of our proposed theoretical analysis results, a numerical example is presented finally.

关键词： Trajectory Tracking Mathematical model Mechanical systems Aerospace electronics Dynamics

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Search for non-standard neutrino interactions with the first six detection units of KM3NeT/ORCA

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Journal of Cosmology and Astroparticle Physics 2025年第2期2025卷 073-073页

作者： Aiello, S. Albert, A. Alhebsi, A.R. Alshamsi, M. Alves Garre, S. Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Aublin, J. Badaracco, F. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Bennani, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Bouasla, A.B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J.A.B. Coleiro, A. Condorelli, A. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. Dallier, R. De Benedittis, A. De Martino, B. De Wasseige, G. Decoene, V. Del Rosso, I. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goswami, P. Gozzini, S.R. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J.J. Idrissi Ibnsalih, W. Illuminati, G. Joly, D. de Jong, M. de Jong, P. Jung, B.J. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y.Y. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Lamoureux, M. Larosa, G. Lastoria, C. Lazar, J. Lazo, A. Le Stum, S. Lehaut, G. Lemaître, V. Leonora, E. Lessing, N. Levi, G. Lindsey Clark, M. Longhitano, F. Magnani, F. Majumdar, J. Malerba, L. Mamedov, F. Manfreda, A. Marconi, M. Margiotta, A. Marinelli, A. Mar INFN Sezione di Catania INFN-CT Via Santa Sofia 64 Catania 95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 Strasbourg F-67000 France Department of Physics Khalifa University PO Box 127788 Abu Dhabi 0000 United Arab Emirates Aix Marseille Univ CNRS IN2P3 CPPM Marseille France IFIC-Instituto de Física Corpuscular CSIC Universitat de València c/Catedrático José Beltrán 2 Paterna Valencia 46980 Spain INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli 80126 Italy Dip. Scienze Fisiche “E. Pancini” Università di Napoli “Federico II” Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli 80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma 00185 Italy Universitat Politècnica de Catalunya Laboratori d'Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú 08800 Spain Subatech IMT Atlantique IN2P3-CNRS Nantes Université 4 rue Alfred Kastler — La Chantrerie BP Nantes 20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia 46730 Spain Université Paris Cité CNRS Astroparticule et Cosmologie Paris F-75013 France Università di Genova Via Dodecaneso 33 Genova 16146 Italy INFN Sezione di Genova Via Dodecaneso 33 Genova 16146 Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen 14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague 110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava 842 48 Slovakia INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna 40127 Italy Università di Bologna Dipartimento di Fisica e Astronomia v.le C. Berti-Pichat 6/2 Bologna 40127 Italy Università degli Studi della Campania “Luigi Vanvitelli” Dipartime

KM3NeT/ORCA is an underwater neutrino telescope under construction in the Mediterranean Sea. Its primary scientific goal is to measure the atmospheric neutrino oscillation parameters and to determine the neutrino mass ordering. ORCA can constrain the oscillation parameters Δm ²₃₁ and θ ₂₃ by reconstructing the arrival direction and energy of multi-GeV neutrinos crossing the Earth. Searches for deviations from the Standard Model of particle physics in the forward scattering of neutrinos inside Earth matter, produced by Non-Standard Interactions, can be conducted by investigating distortions of the standard oscillation pattern of neutrinos of all flavours. This work reports on the results of the search for non-standard neutrino interactions using the first six detection units of ORCA and 433 kton-years of exposure. No significant deviation from standard interactions was found in a sample of 5828 events reconstructed in the 1 GeV-1 TeV energy range. The flavour structure of the non-standard coupling was constrained at 90% confidence level to be |ϵ_μτ | ≤ 5.4 × 10^-3, |ϵ_eτ | ≤ 7.4 × 10^-2, |ϵ_eμ | ≤ 5.6 × 10^-2 and -0.015 ≤ ϵ_ττ - ϵ_μμ ≤ 0.017. The results are comparable to the current most stringent limits placed on the parameters by other experiments. © 2025 The Author(s)

关键词： neutrino experiments neutrino properties solar and atmospheric neutrinos

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First searches for dark matter with the KM3NeT neutrino telescopes

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Journal of Cosmology and Astroparticle Physics 2025年第3期2025卷 058-058页

作者： Aiello, S. Albert, A. Alhebsi, A.R. Alshamsi, M. Alves Garre, S. Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Aublin, J. Badaracco, F. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Bennani, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Bouasla, A.B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J.A.B. Coleiro, A. Condorelli, A. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. Dallier, R. De Benedittis, A. De Martino, B. De Wasseige, G. Decoene, V. Del Rosso, I. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goswami, P. Gozzini, S.R. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J.J. Idrissi Ibnsalih, W. Illuminati, G. Joly, D. de Jong, M. de Jong, P. Jung, B.J. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y.Y. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Lamoureux, M. Larosa, G. Lastoria, C. Lazar, J. Lazo, A. Le Stum, S. Lehaut, G. Lemaître, V. Leonora, E. Lessing, N. Levi, G. Lindsey Clark, M. Longhitano, F. Magnani, F. Majumdar, J. Malerba, L. Mamedov, F. Manfreda, A. Marconi, M. Margiotta, A. Marinelli, A. Mar INFN Sezione di Catania (INFN-CT) Via Santa Sofia 64 Catania 95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 Strasbourg F-67000 France Khalifa University Department of Physics PO Box 127788 Abu Dhabi 0000 United Arab Emirates Aix Marseille Univ CNRS IN2P3 CPPM Marseille France IFIC Instituto de Física Corpuscular (CSIC — Universitat de València) c/Catedrático José Beltrán 2 Valencia Paterna 46980 Spain INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli 80126 Italy Università di Napoli “Federico II” Dip. Scienze Fisiche “E. Pancini” Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli 80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma 00185 Italy Universitat Politècnica de Catalunya Laboratori d'Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú 08800 Spain Subatech IMT Atlantique IN2P3 CNRS Nantes Université 4 rue Alfred Kastler — La Chantrerie Nantes BP 20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia 46730 Spain Université Paris Cité CNRS Astroparticule et Cosmologie Paris F-75013 France Università di Genova Via Dodecaneso 33 Genova 16146 Italy INFN Sezione di Genova Via Dodecaneso 33 Genova 16146 Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen 14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague 110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava 842 48 Slovakia INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna 40127 Italy Università di Bologna Dipartimento di Fisica e Astronomia v.le C. Berti-Pichat 6/2 Bologna 40127 Italy Università degli Studi della Campania “Luigi Vanvitelli” Dip

Indirect dark matter detection methods are used to observe the products of dark matter annihilations or decays originating from astrophysical objects where large amounts of dark matter are thought to accumulate. With neutrino telescopes, an excess of neutrinos is searched for in nearby dark matter reservoirs, such as the Sun and the Galactic Centre, which could potentially produce a sizeable flux of Standard Model particles. The KM3NeT infrastructure, currently under construction, comprises the ARCA and ORCA undersea Čerenkov neutrino detectors located at two different sites in the Mediterranean Sea, offshore of Italy and France, respectively. The two detector configurations are optimised for the detection of neutrinos of different energies, enabling the search for dark matter particles with masses ranging from a few GeV/c² to hundreds of TeV/c². In this work, searches for dark matter annihilations in the Galactic Centre and the Sun with data samples taken with the first configurations of both detectors are presented. No significant excess over the expected background was found in either of the two analyses. Limits on the velocity-averaged self-annihilation cross section of dark matter particles are computed for five different primary annihilation channels in the Galactic Centre. For the Sun, limits on the spin-dependent and spin-independent scattering cross sections of dark matter with nucleons are given for three annihilation channels. © 2025 The Author(s)

关键词： dark matter detectors neutrino astronomy neutrino detectors

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and computing 2018年 620卷 v-vi页

作者： Omatu, Sigeru Rodríguez, Sara Villarrubia, Gabriel Faria, Pedro Sitek, Pawel Prieto, Javier Faculty of Engineering Department of Electronics Information and Communication Engineering Osaka Institute of Technology OsakaOsaka Japan Faculty of Science Department of Computer Science and Automation Control University of Salamanca Salamanca Spain GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Instituto Superior de Engenharia do Porto Porto Portugal Faculty of Electrical Engineering and Computer Science Department of Control and Management Systems Department of Information Systems Kielce University of Technology Kielce Poland

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An Advanced Inventory Data Mining System for Business Intelligence

An Advanced Inventory Data Mining System for Business Intell...

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IEEE International Conference on Big Data computing Service and Applications (BigDataService)

作者： Qifeng Zhou Bin Xia Wei Xue Chunqiu Zeng Ruyuan Han Tao Li Automation Department Xiamen University Xiamen Fujian China School of Computer Science Technology and Engineering Nanjing University of Science and Technology Nanjing China School of Computing and Information Sciences Florida International University FL USA Florida International University Miami FL US

ISBN: (纸本)9781509063192

Inventory management plays a critical role to track inventory levels, orders, and sales of the retailing business. Effective inventory management is a capability necessary to lead in the global marketplace. In the current retailing market, a huge amount of data regarding stocked items in inventory is generated and collected every day. Due to the increasing volume of transaction data and their correlated relations, it is often a non-trivial task to efficiently manage stocked goods, yet it is imperative to explore the underlying dependencies of the inventory items and give insights into implementing intelligent management systems. However, existing inventory management systems rely on statistical analysis of the historical inventory data, and have a limited capability of intelligent management. For example, they usually do not have the ability to forecast item demand and detect anomalous patterns of item inventory transactions. There is little work reported in implementing intelligent inventory management solutions to reveal hidden relations with integrated data-driven analysis. In this paper, we present an intelligent system, called iMiner, to facilitate managing enormous inventory data. We utilize distributed computing resources to process the huge volume of inventory data and incorporate the latest advances in data mining technologies. iMiner provides comprehensive support for conducting many inventory management tasks, such as forecasting inventory, detecting anomalous items, and analyzing inventory aging.

关键词： Inventory management Forecasting Data analysis Time series analysis Predictive models Data mining

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State Estimation for BAM Neural Networks with Mixed Time Delays

State Estimation for BAM Neural Networks with Mixed Time Del...

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IEEE International Conference on automation Science and engineering

作者： Guoquan Liu Chaomin Luo Jianlong Qiu Xianxi Luo Jiakai Ding Jiangxi Province Engineering University of Technology Nanchang China Department of Electrical and Computer Engineering University of Detroit Mercy Michigan USA School of Automation and Electrical Engineering Key Laboratory of Complex systems and Intelligent Computing in Universities of Shandong (Linyi University) Linyi Shandong Province China Jiangxi Province Engineering East China University of Technology Nanchang China School of mechanical and electronic engineering East China University of Technology Nanchang China

This paper is concerned with the state estimation problem of BAM neural networks with mixed time delays. By constructing a suitable Lyapunov-Krasovskii functional (LKF), a new criterion is obtained so that the BAM neural networks error system is asymptotically stable. A simulation example is given to demonstrate the effectiveness of the proposed method.

关键词： LKF concerned estimation

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Author Correction: Observation of an ultra-high-energy cosmic neutrino with KM3NeT

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Nature 2025年第8057期640卷 E3页

作者： S. Aiello R. Bruno G. Ferrara E. Leonora F. Longhitano N. Randazzo A. Sinopoulou I. Tosta e Melo A. Albert D. Drouhin T. Pradier A. R. Alhebsi S. Thoudam A. van Vliet M. Alshamsi V. Bertin M. Breuhaus J. Brunner J. Busto L. Cerisy P. Coyle B. De Martino D. Dornic J.-G. Ducoin A. Enzenhöfer S. Henry D. Joly S. Lancelin S. Le Stum N. Lumb F. Magnani C. Paries M. Perrin-Terrin G. Vannoye S. Alves Garre A. Bariego-Quintana D. Calvo V. Cecchini A. Garcia Soto S. R. Gozzini J. J. Hernández-Rey A. Lazo N. Lessing J. Palacios González E. J. Pastor Gomez J. Prado D. Real A. Šaina F. Salesa Greus A. Sánchez Losa J. D. Zornoza J. Zúñiga A. Ambrosone M. Bendahman M. Benhassi C. Bozza R. M. Bozza R. Buompane A. Condorelli A. De Benedittis L. A. Fusco L. Gialanella W. Idrissi Ibnsalih A. Manfreda A. Marinelli F. Marzaioli S. Mastroianni G. Miele P. Migliozzi M. L. Mitsou C. M. Mollo L. Morales-Gallegos M. R. Musone V. Oliviero C. Poirè I. C. Rea A. Simonelli B. Spisso D. Vivolo F. Ameli A. Capone S. Celli I. Di Palma S. Gagliardini M. Mastrodicasa C. A. Nicolau A. Tudorache A. Veutro A. Zegarelli M. Andre M. Anghinolfi F. Badaracco B. Caiffi V. Ellajosyula C. Guidi V. Kulikovskiy L. Malerba M. Marconi B. Ó Fearraigh V. Parisi A. Romanov M. Sanguineti M. Taiuti S. Zavatarelli L. Aphecetche F. Bretaudeau R. Dallier V. Decoene L. Martin M. Ardid S. Ardid J. García Méndez C. A. Quiroz-Rangel C. Argüelles N. Kamp A. Y. Wen H. Atmani J. Boumaaza A. Eddymaoui Y. Tayalati J. Aublin B. Baret Y. Becherini T. Cartraud J. A. B. Coelho A. Coleiro S. Colonges A. Creusot C. Donzaud M. Eff S. El Hedri I. Goos P. Goswami A. Ilioni A. Kouchner M. Lindsey Clark E. Oukacha S. Peña Martínez R. Pestes A. Sharma B. Trocmé V. Van Elewyck C. Verilhac I. Lhenry-Yvon L. Bailly-Salins M. Bennani B. Guillon M. Labalme C. Lastoria G. Lehaut I. Mozun Mateo V. Pestel A. Vacheret Z. Bardačová E. Eckerová F. Mamedov Y. Shitov I. Štekl R. Dvornický F. Šimkovic F. Benfenati Gualandi F. Carenini P. Castaldi T. Chiarusi I. Del Rosso G. Levi A. Margiotta R. Muller INFN Sezione di Catania (INFN-CT) Catania Italy INFN Laboratori Nazionali del Sud (LNS) Catania Italy Dipartimento di Fisica e Astronomia “Ettore Majorana” Università di Catania (INFN-CT) Catania Italy Université de Strasbourg CNRS IPHC UMR 7178 Strasbourg France Université de Haute Alsace Mulhouse France Department of Physics Khalifa University Abu Dhabi United Arab Emirates Aix Marseille Université CNRS/IN2P3 CPPM Marseille France IFIC - Instituto de Física Corpuscular (CSIC - Universitat de València) Paterna Spain INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Napoli Italy Università di Napoli “Federico II” Dip. Scienze Fisiche “E. Pancini” Complesso Universitario di Monte S. Angelo Napoli Italy Dipartimento di Matematica e Fisica Università degli Studi della Campania “Luigi Vanvitelli” Caserta Italy Dipartimento di Fisica Università di Salerno e INFN Gruppo Collegato di Salerno Fisciano Italy INFN Sezione di Roma Roma Italy Dipartimento di Fisica Università La Sapienza Roma Italy Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Universitat Politècnica de Catalunya Vilanova i la Geltrú Spain INFN Sezione di Genova Genova Italy Università di Genova Genova Italy LPC CAEN Normandie Université ENSICAEN UNICAEN CNRS/IN2P3 Caen France Subatech IMT Atlantique IN2P3-CNRS Nantes Université Nantes France Instituto de Investigación para la Gestión Integrada de las Zonas Costeras Universitat Politècnica de València Gandia Spain Department of Physics Harvard University Cambridge MA USA Laboratory for Particle Physics and Cosmology Lyman Laboratory Harvard University Cambridge MA USA Faculty of Sciences University Mohammed V in Rabat Rabat Morocco Institute of Applied Physics Mohammed VI Polytechnic University Ben Guerir Morocco Astroparticule et Cosmologie Université Paris Cité CNRS Paris France Institut Universitaire de France Paris France Institute of Experimental and Applied Physics

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Fully distributed flocking with a moving leader for Lagrange networks with parametric uncertainties

Fully distributed flocking with a moving leader for Lagrange...

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作者： Ghapani, Sheida Mei, Jie Ren, Wei Song, Yongduan Department of Electrical and Computer Engineering University of California Riverside United States School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Key Laboratory of Dependable Service Computing Cyber Physical Society Ministry of Education Chongqing University China School of Automation Chongqing University China

This paper addresses the leader-follower flocking problem with a moving leader for networked Lagrange systems with parametric uncertainties under a proximity graph. Here a group of followers move cohesively with the moving leader to maintain connectivity and avoid collisions for all time and also eventually achieve velocity matching. In the proximity graph, the neighbor relationship is defined according to the relative distance between each pair of agents. Each follower is able to obtain information from only the neighbors in its proximity, involving only local interaction. We consider two cases: (i) the leader moves with a constant velocity, and (ii) the leader moves with a varying velocity. In the first case, a distributed continuous adaptive control algorithm accounting for unknown parameters is proposed in combination with a distributed continuous estimator for each follower. In the second case, a distributed discontinuous adaptive control algorithm and estimator are proposed. Then the algorithm is extended to be fully distributed with the introduction of gain adaptation laws. In all proposed algorithms, only one-hop neighbors' information (e.g., the relative position and velocity measurements between the neighbors and the absolute position and velocity measurements) is required, and flocking is achieved as long as the connectivity and collision avoidance are ensured at the initial time and the control gains are designed properly. Numerical simulations are presented to illustrate the theoretical results. © 2016 Elsevier Ltd. All rights reserved.

关键词： Multi agent systems

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Random number generator influence on differential search performance 6

Random number generator influence on differential search per...

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6th IASTED International Conference on Modelling, Simulation and Identification, MSI 2016

作者： Alhalabi, Wadee S. Dragoi, Elena-Niculina Alsaadi, Areej A. Department of Computer Science Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Chemical Engineering Applied Informatics and Automation Chemical Engineering and Environmental Protection Gheorghe Asachi Technical University of Iasi Iasi700050 Romania

ISBN: (纸本)9780889869837

Differential Search is an optimization approach that simulates the Brownian like random walk movement of migration organisms. Its inner workings relay on Random Number Generators (RNG) to emulate the probability of the natural driven process and therefore, the properties and performance of the RNG used has an influence on the overall algorithm performance. This study focuses on assessing this influence and on the manner in which the best suited RNG must be selected in order to achieve the optimal results for different types of problems. The results showed that depending on the properties of the problem, different RNGs provide the best solutions. However, as the number of function evaluation rises in report to the problem dimensionality, the influence on the RNG becomes smaller.

关键词： Number theory

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Hibrid drive dimensioning using MATLAB software package

Hibrid drive dimensioning using MATLAB software package

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International Conference on Development and Application Systems

作者： Damir Vuljaj Branko Ban Mario Vrazic Department of Electric Machines Drives and Automation Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9781509019946

The paper analyses vehicle dynamics during operation (drive wheel load). Parameters for the vehicle model were calculated from the vehicle force equations. To validate the model, speed and torque measurements on the conventional car (Fiat Punto) were carried out as well as a comparison between the measured and the simulated values. The electric motor, inverter and batteries were dimensioned on the basis of the vehicle traction characteristics. Models of the internal combustion engine (ICE), gear box and electrical drive (a motor with an inverter and batteries) were made. A comparison of hybrid and conventional drives and fuel consumption were made.

关键词： electric vehicle hybrid vehicle vehicle simulation fuel consumption

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