Littérature scientifique sur le sujet « Autonomous network control »
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Articles de revues sur le sujet "Autonomous network control"
Kim, Jae-Hoon, Seungchul Lee et Sengphil Hong. « Autonomous Operation Control of IoT Blockchain Networks ». Electronics 10, no 2 (17 janvier 2021) : 204. http://dx.doi.org/10.3390/electronics10020204.
Texte intégralAlsuwian, Turki, Mian Hamza Usman et Arslan Ahmed Amin. « An Autonomous Vehicle Stability Control Using Active Fault-Tolerant Control Based on a Fuzzy Neural Network ». Electronics 11, no 19 (1 octobre 2022) : 3165. http://dx.doi.org/10.3390/electronics11193165.
Texte intégralKim, Eric J., et Ruben E. Perez. « Neuroevolutionary Control for Autonomous Soaring ». Aerospace 8, no 9 (17 septembre 2021) : 267. http://dx.doi.org/10.3390/aerospace8090267.
Texte intégralBotchkaryov, A. « METHOD FOR DECENTRALIZED CONTROL OF ADAPTIVE DATA COLLECTION PROCESSES IN AUTONOMOUS DISTRIBUTED SYSTEMS ». Computer systems and network 5, no 1 (16 décembre 2023) : 8–19. http://dx.doi.org/10.23939/csn2023.01.008.
Texte intégralAkimoto, Y., H. Tanaka, H. Ogi, H. Taoka, S. Nishida et T. Sakaguchi. « Autonomous Distributed Network Architecture for Control System ». IFAC Proceedings Volumes 21, no 12 (septembre 1988) : 21–27. http://dx.doi.org/10.1016/b978-0-08-036938-9.50009-1.
Texte intégralJain, Ankur, et B. K. Roy. « Online Control of a Nonlinear Autonomous Vehicle in the Presence of Network Delay ». Journal of Advanced Research in Dynamical and Control Systems 11, no 12-SPECIAL ISSUE (31 décembre 2019) : 344–51. http://dx.doi.org/10.5373/jardcs/v11sp12/20193230.
Texte intégralJawad, Luay, Arshdeep Singh-Chudda, Abhishek Shankar et Abhilash Pandya. « A Deep Learning Approach to Merge Rule-Based and Human-Operated Camera Control for Teleoperated Robotic Systems ». Robotics 13, no 3 (11 mars 2024) : 47. http://dx.doi.org/10.3390/robotics13030047.
Texte intégralKumar, Dr A. Dinesh. « Underwater Gripper using Distributed Network and Adaptive Control ». Journal of Electrical Engineering and Automation 2, no 1 (25 mars 2020) : 43–49. http://dx.doi.org/10.36548/jeea.2020.1.005.
Texte intégralGao, Youtao, Zhicheng You et Bo Xu. « Integrated Design of Autonomous Orbit Determination and Orbit Control for GEO Satellite Based on Neural Network ». International Journal of Aerospace Engineering 2020 (21 janvier 2020) : 1–13. http://dx.doi.org/10.1155/2020/3801625.
Texte intégralFujii, Teruo, et Tamaki Ura. « Control with Neural Network For Autonomous Underwater Vehicle ». Journal of the Society of Naval Architects of Japan 1989, no 166 (1989) : 503–11. http://dx.doi.org/10.2534/jjasnaoe1968.1989.166_503.
Texte intégralThèses sur le sujet "Autonomous network control"
Dutta, Rajdeep. « Cooperative control of autonomous network topologies ». Thesis, The University of Texas at San Antonio, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10151348.
Texte intégralIn this dissertation, we present novel solutions to cooperative control of autonomous multi-agent network topologies pertaining to the area of hostile target tracking by multiple unmanned aerial vehicles (UAVs). The present work assumes an undirected graph comprising point-mass UAVs with time-varying communication topology among agents. The level of information sharing ability among agents in a multi-agent network, i.e. the network connectivity, plays pivotal role in group dynamics. A neighborhood information based decentralized controller is proposed in order to drive UAVs into a symmetric formation of polygon shape surrounding a mobile target, simultaneously with maintaining and controlling connectivity during the formation process. Appropriate controller parameter selection schemes, both for controller weights and gains, are adapted for dynamic topologies to maintain the connectivity measure above zero at all times. A challenging task of tracking a desired connectivity profile along with the formation control, is accomplished by using time-varying controller gains throughout agents dynamics. We next present a generalized formation controller, which in fact generates a family of UAV trajectories satisfying the control criteria. The proposed decentralized controller contains additional tuning parameters as fractional powers on proportional and derivative terms, rendering flexibility in achieving the control objective. The proposed controller with proper fractional powers, results in gradual state changes in UAV dynamics by using limited control inputs. Moreover, we extend our work by addressing a ground target tracking and reacquiring problem using the visual information gathered by flying UAV. The proposed guidance law uses line-of-sight guidance to track the target pushing it towards the image center captured by UAV, and exploits UAV-target mutual information to reacquire the target in case it steers away from the field-of-view for a short time. The convergence of the closed loop systems under the proposed controllers are shown using Lyapunov theory. Simulation results validate the effectiveness and novelty of the proposed control laws.
In addition to the above, this work focuses on categorizing multi-agent topologies in concern with the network dynamics and connectivity to analyze, realize, and visualize multi-agent interactions. In order to explore various useful agents reconfiguration possibilities without compromising the network connectivity, the present work aims at determining distinct topologies with the same connectivity or isoconnected topologies. Different topologies with identical connectivity are found out with the help of analytic techniques utilizing matrix algebra and calculus of variation. Elegant strategies for preserving connectivity in a network with a single mobile agent and rest of the stationary members, are proposed in this work as well. The proposed solutions are validated with the help of sufficient examples. For visual understanding of how agents locations and topology configurations influence the network connectivity, a MATLAB based graphical user interface is designed to interact with multi-agent graphs in a user-friendly manner.
To this end, the present work succeeds to determine solutions to challenging multi-UAV cooperative control problems, such as: (1) Symmetric formation control surrounding a mobile target; (2) Maintaining, improving and controlling the network connectivity during a mission; and (3) Categorizing different multi-agent topologies to unravel useful reconfiguration options for a group. The proposed theories with appropriate analysis, and the simulation results suffice to show the contribution and novelty of this work.
Tung, Charles P. (Charles Patrick) 1974. « A distributed processing network for autonomous micro-rover control ». Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/47542.
Texte intégralIncludes bibliographical references (leaf 77).
by Charles P. Tung.
B.S.
M.Eng.
Hemlin, Karl, et Frida Persson. « Remote Control Operation of Autonomous Cars Over Cellular Network Using PlayStation Controller ». Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254218.
Texte intégralGarratt, Matthew Adam, et m. garratt@adfa edu au. « Biologically Inspired Vision and Control for an Autonomous Flying Vehicle ». The Australian National University. Research School of Biological Sciences, 2008. http://thesis.anu.edu.au./public/adt-ANU20090116.154822.
Texte intégralDalamagkidis, Konstantinos. « Autonomous vertical autorotation for unmanned helicopters ». [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003147.
Texte intégralYoumans, Elisabeth A. « Neural network control of space vehicle orbit transfer, intercept, and rendezvous maneuvers ». Diss., This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-06062008-162101/.
Texte intégralDarr, Matthew John. « DEVELOPMENT AND EVALUATION OF A CONTROLLER AREA NETWORK BASED AUTONOMOUS VEHICLE ». UKnowledge, 2004. http://uknowledge.uky.edu/gradschool_theses/192.
Texte intégralPuttige, Vishwas Ramadas Engineering & Information Technology Australian Defence Force Academy UNSW. « Neural network based adaptive control for autonomous flight of fixed wing unmanned aerial vehicles ». Awarded by:University of New South Wales - Australian Defence Force Academy. Engineering & ; Information Technology, 2009. http://handle.unsw.edu.au/1959.4/43736.
Texte intégralLivianu, Mathew Joseph. « Human-in-the-loop neural network control of a planetary rover on harsh terrain ». Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26576.
Texte intégralCommittee Chair: Dr. Ayanna Howard; Committee Member: Dr. Patricio Vela; Committee Member: Dr. Yoria Wardi. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Kam, Khim Yee. « High bandwidth communications links between heterogeneous autonomous vehicles using sensor network modeling and extremum control approaches ». Thesis, Monterey, Calif. : Naval Postgraduate School, 2008. http://edocs.nps.edu/npspubs/scholarly/theses/2008/Dec/08Dec%5FKam.pdf.
Texte intégralThesis Advisor(s): Kaminer, Isaac I. ; Lee, Deok Jin. "December 2008." Description based on title screen as viewed on January 29, 2009. Includes bibliographical references (p. 57-58). Also available in print.
Livres sur le sujet "Autonomous network control"
W, Protzel Peter, Palumbo Daniel L et Langley Research Center, dir. Automatic learning rate adjustment for self-supervising autonomous robot control. Hampton, Va : National Aeronautics and Space Administration, Langley Research Center, 1992.
Trouver le texte intégralVarlamov, Oleg. Fundamentals of creating MIVAR expert systems. ru : INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1513119.
Texte intégralGanchev, Ivan. Autonomous Control for a Reliable Internet of Services : Methods, Models, Approaches, Techniques, Algorithms, and Tools. Cham : Springer Nature, 2018.
Trouver le texte intégralVarlamov, Oleg. Mivar databases and rules. ru : INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.
Texte intégralYoung, Forrest C. Phoenix autonomous underwater vehicle (AUV) : Networked control of multiple analog and digital devices using LonTalk. Monterey, Calif : Naval Postgraduate School, 1997.
Trouver le texte intégralTucci, Mario, et Marco Garetti, dir. Proceedings of the third International Workshop of the IFIP WG5.7. Florence : Firenze University Press, 2002. http://dx.doi.org/10.36253/88-8453-042-3.
Texte intégralAndo, Noriaki. Simulation, Modeling, and Programming for Autonomous Robots : Second International Conference, SIMPAR 2010, Darmstadt, Germany, November 15-18, 2010. Proceedings. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010.
Trouver le texte intégralGuillermo, Navarro-Arribas, Cavalli Ana, Leneutre Jean et SpringerLink (Online service), dir. Data Privacy Management and Autonomous Spontaneous Security : 5th International Workshop, DPM 2010 and 3rd International Workshop, SETOP 2010, Athens, Greece, September 23, 2010, Revised Selected Papers. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
Trouver le texte intégral1935-, Lasker G. E., International Institute for Advanced Studies in Systems Research and Cybernetics. et International Conference on Systems Research, Informatics, and Cybernetics. (10th : 1998 : Baden-Baden, Germany), dir. Advances in artificial intelligence and engineering cybernetics : Neural networks, anticipatory systems, the evolution of autonomous agents, multi-agent systems development, intelligent systems in process control, knowledge organization, formal representation of meaning, space-time logic, logic networks, time and threshold dependent logic operators, natural language processing. Windsor, Ont : International Institute for Advanced Studies in Systems Research and Cybernetics, 1999.
Trouver le texte intégralChapman, Airlie. Semi-Autonomous Networks : Effective Control of Networked Systems Through Protocols, Design, and Modeling. Springer, 2015.
Trouver le texte intégralChapitres de livres sur le sujet "Autonomous network control"
Bao, Jie, et Shichao Xu. « Plantwide Control via a Network of Autonomous Controllers ». Dans Plantwide Control, 385–416. Chichester, UK : John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119968962.ch18.
Texte intégralSchönberger, Jörn, et Herbert Kopfer. « Approaching the Application Borders of Network Capacity Control in Road Haulage ». Dans Autonomous Cooperation and Control in Logistics, 45–59. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19469-6_5.
Texte intégralSekiyama, Kosuke, Katsuhiro Suzuki, Shigeru Fukunaga et Masaaki Date. « Autonomous Synchronization Scheme Access Control for Sensor Network ». Dans Lecture Notes in Computer Science, 487–95. Berlin, Heidelberg : Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11554028_68.
Texte intégralZhang, Xiaokai, et Tianfang Yao. « A Study of Network Informal Language Using Minimal Supervision Approach ». Dans Autonomous Systems – Self-Organization, Management, and Control, 169–75. Dordrecht : Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-8889-6_18.
Texte intégralNodland, David, H. Zargarzadeh, Arpita Ghosh et S. Jagannathan. « Neural Network-Based Optimal Control of an Unmanned Helicopter ». Dans Advances in Intelligent and Autonomous Aerospace Systems, 33–57. Reston, VA : American Institute of Aeronautics and Astronautics, Inc., 2012. http://dx.doi.org/10.2514/5.9781600868962.0033.0058.
Texte intégralIsa, Khalid, et M. R. Arshad. « Neural Network Control of Buoyancy-Driven Autonomous Underwater Glider ». Dans Recent Advances in Robotics and Automation, 15–35. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37387-9_2.
Texte intégralAnwar, Mohd, Philip W. L. Fong, Xue-Dong Yang et Howard Hamilton. « Visualizing Privacy Implications of Access Control Policies in Social Network Systems ». Dans Data Privacy Management and Autonomous Spontaneous Security, 106–20. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11207-2_9.
Texte intégralGrosspietsch, Karl-Erwin, et Tanya A. Silayeva. « Modified ART Network Architectures for the Control of Autonomous Systems ». Dans Product-Focused Software Process Improvement, 309–19. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31063-8_24.
Texte intégralMing, Yan, Wang Jiaxing, Li Heqi et Liu Kai. « Research on Direct Lift Landing Control Based on Neural Network ». Dans Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022), 2534–45. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0479-2_234.
Texte intégralGarcía, Juan Carlos, Marta Marrón, J. A. García, M. A. Sotelo, Jesús Ureña, J. L. Lázaro, F. J. Rodriguez, M. Mazo et Marisol Escudero. « An Autonomous Wheelchair with a LonWorks Network based Distributed Control System ». Dans Field and Service Robotics, 405–10. London : Springer London, 1988. http://dx.doi.org/10.1007/978-1-4471-1273-0_61.
Texte intégralActes de conférences sur le sujet "Autonomous network control"
Coombes, Matthew, William Eaton, Owen McAree et Wen-Hua Chen. « Development of a generic network enabled autonomous vehicle system ». Dans 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915211.
Texte intégralKarimi Shahri, Pouria, Shubhankar Chintamani Shindgikar, Baisravan HomChaudhuri et Amir H. Ghasemi. « Optimal Lane Management in Heterogeneous Traffic Network ». Dans ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9040.
Texte intégralChapman, Airlie, et Mehran Mesbahi. « Semi-autonomous networks : Network resilience and adaptive trees ». Dans 2010 49th IEEE Conference on Decision and Control (CDC). IEEE, 2010. http://dx.doi.org/10.1109/cdc.2010.5717850.
Texte intégralCui, Rongxin, Chenguang Yang, Yang Li et Sanjay Sharma. « Neural network based reinforcement learning control of autonomous underwater vehicles with control input saturation ». Dans 2014 UKACC 10th International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915114.
Texte intégralLu, Qiang, et Zhaochen Zhang. « Chaotic Autonomous Developmental Neural Network ». Dans 2019 5th International Conference on Control, Automation and Robotics (ICCAR). IEEE, 2019. http://dx.doi.org/10.1109/iccar.2019.8813424.
Texte intégralQuader, Niamul, S. M. Masudur Rahman Al-Arif, Md Al Mamun Shaon, Kazi Khairul Islam et Abdur Raquib Ridwan. « Control of autonomous nanorobots in neural network ». Dans 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2011. http://dx.doi.org/10.1109/bmei.2011.6098609.
Texte intégralTusing, Nathan, et Richard Brooks. « Access Control Requirements for Autonomous Robotic Fleets ». Dans WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0104.
Texte intégralXie, Yuanrai, Zhixin Liu, Kai Ma et Yazhou Yuan. « Robust Power Control in D2D-Enabled Vehicular Communication Network ». Dans 2019 3rd International Symposium on Autonomous Systems (ISAS). IEEE, 2019. http://dx.doi.org/10.1109/isass.2019.8757748.
Texte intégralKurokawa, Ryota, Go Hasegawa et Masayuki Murata. « Biochemical-Inspired Autonomous Control of Virtualized Network Functions ». Dans 2019 International Conference on Information Networking (ICOIN). IEEE, 2019. http://dx.doi.org/10.1109/icoin.2019.8718124.
Texte intégralHarrington, Peter, Wai Pang Ng et Richard Binns. « Autonomous drone control within a Wi-Fi network ». Dans 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). IEEE, 2020. http://dx.doi.org/10.1109/csndsp49049.2020.9249585.
Texte intégralRapports d'organisations sur le sujet "Autonomous network control"
Pearl, Judea. Dynamic Network Techniques for Autonomous Planning and Control. Fort Belvoir, VA : Defense Technical Information Center, novembre 2000. http://dx.doi.org/10.21236/ada387551.
Texte intégralTzonev, Nick. PR-396-183905-R01 Autonomous System For Monitoring Pipeline River Crossings. Chantilly, Virginia : Pipeline Research Council International, Inc. (PRCI), juin 2021. http://dx.doi.org/10.55274/r0012110.
Texte intégralHovakimyan, Naira, Hunmin Kim, Wenbin Wan et Chuyuan Tao. Safe Operation of Connected Vehicles in Complex and Unforeseen Environments. Illinois Center for Transportation, août 2022. http://dx.doi.org/10.36501/0197-9191/22-016.
Texte intégralEvent-Triggered Adaptive Robust Control for Lateral Stability of Steer-by-Wire Vehicles with Abrupt Nonlinear Faults. SAE International, juillet 2022. http://dx.doi.org/10.4271/2022-01-5056.
Texte intégral