Auswahl der wissenschaftlichen Literatur zum Thema „Autonomous network control“
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Zeitschriftenartikel zum Thema "Autonomous network control"
Kim, Jae-Hoon, Seungchul Lee und Sengphil Hong. „Autonomous Operation Control of IoT Blockchain Networks“. Electronics 10, Nr. 2 (17.01.2021): 204. http://dx.doi.org/10.3390/electronics10020204.
Der volle Inhalt der QuelleAlsuwian, Turki, Mian Hamza Usman und Arslan Ahmed Amin. „An Autonomous Vehicle Stability Control Using Active Fault-Tolerant Control Based on a Fuzzy Neural Network“. Electronics 11, Nr. 19 (01.10.2022): 3165. http://dx.doi.org/10.3390/electronics11193165.
Der volle Inhalt der QuelleKim, Eric J., und Ruben E. Perez. „Neuroevolutionary Control for Autonomous Soaring“. Aerospace 8, Nr. 9 (17.09.2021): 267. http://dx.doi.org/10.3390/aerospace8090267.
Der volle Inhalt der QuelleBotchkaryov, A. „METHOD FOR DECENTRALIZED CONTROL OF ADAPTIVE DATA COLLECTION PROCESSES IN AUTONOMOUS DISTRIBUTED SYSTEMS“. Computer systems and network 5, Nr. 1 (16.12.2023): 8–19. http://dx.doi.org/10.23939/csn2023.01.008.
Der volle Inhalt der QuelleAkimoto, Y., H. Tanaka, H. Ogi, H. Taoka, S. Nishida und T. Sakaguchi. „Autonomous Distributed Network Architecture for Control System“. IFAC Proceedings Volumes 21, Nr. 12 (September 1988): 21–27. http://dx.doi.org/10.1016/b978-0-08-036938-9.50009-1.
Der volle Inhalt der QuelleJain, Ankur, und 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, Nr. 12-SPECIAL ISSUE (31.12.2019): 344–51. http://dx.doi.org/10.5373/jardcs/v11sp12/20193230.
Der volle Inhalt der QuelleJawad, Luay, Arshdeep Singh-Chudda, Abhishek Shankar und Abhilash Pandya. „A Deep Learning Approach to Merge Rule-Based and Human-Operated Camera Control for Teleoperated Robotic Systems“. Robotics 13, Nr. 3 (11.03.2024): 47. http://dx.doi.org/10.3390/robotics13030047.
Der volle Inhalt der QuelleKumar, Dr A. Dinesh. „Underwater Gripper using Distributed Network and Adaptive Control“. Journal of Electrical Engineering and Automation 2, Nr. 1 (25.03.2020): 43–49. http://dx.doi.org/10.36548/jeea.2020.1.005.
Der volle Inhalt der QuelleGao, Youtao, Zhicheng You und Bo Xu. „Integrated Design of Autonomous Orbit Determination and Orbit Control for GEO Satellite Based on Neural Network“. International Journal of Aerospace Engineering 2020 (21.01.2020): 1–13. http://dx.doi.org/10.1155/2020/3801625.
Der volle Inhalt der QuelleFujii, Teruo, und Tamaki Ura. „Control with Neural Network For Autonomous Underwater Vehicle“. Journal of the Society of Naval Architects of Japan 1989, Nr. 166 (1989): 503–11. http://dx.doi.org/10.2534/jjasnaoe1968.1989.166_503.
Der volle Inhalt der QuelleDissertationen zum Thema "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.
Der volle Inhalt der QuelleIn 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.
Der volle Inhalt der QuelleIncludes bibliographical references (leaf 77).
by Charles P. Tung.
B.S.
M.Eng.
Hemlin, Karl, und 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.
Der volle Inhalt der QuelleGarratt, Matthew Adam, und 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.
Der volle Inhalt der QuelleDalamagkidis, Konstantinos. „Autonomous vertical autorotation for unmanned helicopters“. [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003147.
Der volle Inhalt der QuelleYoumans, 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/.
Der volle Inhalt der QuelleDarr, Matthew John. „DEVELOPMENT AND EVALUATION OF A CONTROLLER AREA NETWORK BASED AUTONOMOUS VEHICLE“. UKnowledge, 2004. http://uknowledge.uky.edu/gradschool_theses/192.
Der volle Inhalt der QuellePuttige, 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.
Der volle Inhalt der QuelleLivianu, 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.
Der volle Inhalt der QuelleCommittee 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.
Der volle Inhalt der QuelleThesis 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.
Bücher zum Thema "Autonomous network control"
W, Protzel Peter, Palumbo Daniel L und Langley Research Center, Hrsg. Automatic learning rate adjustment for self-supervising autonomous robot control. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1992.
Den vollen Inhalt der Quelle findenVarlamov, Oleg. Fundamentals of creating MIVAR expert systems. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1513119.
Der volle Inhalt der QuelleGanchev, Ivan. Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools. Cham: Springer Nature, 2018.
Den vollen Inhalt der Quelle findenVarlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.
Der volle Inhalt der QuelleYoung, Forrest C. Phoenix autonomous underwater vehicle (AUV): Networked control of multiple analog and digital devices using LonTalk. Monterey, Calif: Naval Postgraduate School, 1997.
Den vollen Inhalt der Quelle findenTucci, Mario, und Marco Garetti, Hrsg. 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.
Der volle Inhalt der QuelleAndo, 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.
Den vollen Inhalt der Quelle findenGuillermo, Navarro-Arribas, Cavalli Ana, Leneutre Jean und SpringerLink (Online service), Hrsg. 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.
Den vollen Inhalt der Quelle finden1935-, Lasker G. E., International Institute for Advanced Studies in Systems Research and Cybernetics. und International Conference on Systems Research, Informatics, and Cybernetics. (10th : 1998 : Baden-Baden, Germany), Hrsg. 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.
Den vollen Inhalt der Quelle findenChapman, Airlie. Semi-Autonomous Networks: Effective Control of Networked Systems Through Protocols, Design, and Modeling. Springer, 2015.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Autonomous network control"
Bao, Jie, und Shichao Xu. „Plantwide Control via a Network of Autonomous Controllers“. In Plantwide Control, 385–416. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119968962.ch18.
Der volle Inhalt der QuelleSchönberger, Jörn, und Herbert Kopfer. „Approaching the Application Borders of Network Capacity Control in Road Haulage“. In 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.
Der volle Inhalt der QuelleSekiyama, Kosuke, Katsuhiro Suzuki, Shigeru Fukunaga und Masaaki Date. „Autonomous Synchronization Scheme Access Control for Sensor Network“. In Lecture Notes in Computer Science, 487–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11554028_68.
Der volle Inhalt der QuelleZhang, Xiaokai, und Tianfang Yao. „A Study of Network Informal Language Using Minimal Supervision Approach“. In 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.
Der volle Inhalt der QuelleNodland, David, H. Zargarzadeh, Arpita Ghosh und S. Jagannathan. „Neural Network-Based Optimal Control of an Unmanned Helicopter“. In 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.
Der volle Inhalt der QuelleIsa, Khalid, und M. R. Arshad. „Neural Network Control of Buoyancy-Driven Autonomous Underwater Glider“. In 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.
Der volle Inhalt der QuelleAnwar, Mohd, Philip W. L. Fong, Xue-Dong Yang und Howard Hamilton. „Visualizing Privacy Implications of Access Control Policies in Social Network Systems“. In 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.
Der volle Inhalt der QuelleGrosspietsch, Karl-Erwin, und Tanya A. Silayeva. „Modified ART Network Architectures for the Control of Autonomous Systems“. In 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.
Der volle Inhalt der QuelleMing, Yan, Wang Jiaxing, Li Heqi und Liu Kai. „Research on Direct Lift Landing Control Based on Neural Network“. In 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.
Der volle Inhalt der QuelleGarcía, Juan Carlos, Marta Marrón, J. A. García, M. A. Sotelo, Jesús Ureña, J. L. Lázaro, F. J. Rodriguez, M. Mazo und Marisol Escudero. „An Autonomous Wheelchair with a LonWorks Network based Distributed Control System“. In Field and Service Robotics, 405–10. London: Springer London, 1988. http://dx.doi.org/10.1007/978-1-4471-1273-0_61.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Autonomous network control"
Coombes, Matthew, William Eaton, Owen McAree und Wen-Hua Chen. „Development of a generic network enabled autonomous vehicle system“. In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915211.
Der volle Inhalt der QuelleKarimi Shahri, Pouria, Shubhankar Chintamani Shindgikar, Baisravan HomChaudhuri und Amir H. Ghasemi. „Optimal Lane Management in Heterogeneous Traffic Network“. In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9040.
Der volle Inhalt der QuelleChapman, Airlie, und Mehran Mesbahi. „Semi-autonomous networks: Network resilience and adaptive trees“. In 2010 49th IEEE Conference on Decision and Control (CDC). IEEE, 2010. http://dx.doi.org/10.1109/cdc.2010.5717850.
Der volle Inhalt der QuelleCui, Rongxin, Chenguang Yang, Yang Li und Sanjay Sharma. „Neural network based reinforcement learning control of autonomous underwater vehicles with control input saturation“. In 2014 UKACC 10th International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915114.
Der volle Inhalt der QuelleLu, Qiang, und Zhaochen Zhang. „Chaotic Autonomous Developmental Neural Network“. In 2019 5th International Conference on Control, Automation and Robotics (ICCAR). IEEE, 2019. http://dx.doi.org/10.1109/iccar.2019.8813424.
Der volle Inhalt der QuelleQuader, Niamul, S. M. Masudur Rahman Al-Arif, Md Al Mamun Shaon, Kazi Khairul Islam und Abdur Raquib Ridwan. „Control of autonomous nanorobots in neural network“. In 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2011. http://dx.doi.org/10.1109/bmei.2011.6098609.
Der volle Inhalt der QuelleTusing, Nathan, und Richard Brooks. „Access Control Requirements for Autonomous Robotic Fleets“. In WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0104.
Der volle Inhalt der QuelleXie, Yuanrai, Zhixin Liu, Kai Ma und Yazhou Yuan. „Robust Power Control in D2D-Enabled Vehicular Communication Network“. In 2019 3rd International Symposium on Autonomous Systems (ISAS). IEEE, 2019. http://dx.doi.org/10.1109/isass.2019.8757748.
Der volle Inhalt der QuelleKurokawa, Ryota, Go Hasegawa und Masayuki Murata. „Biochemical-Inspired Autonomous Control of Virtualized Network Functions“. In 2019 International Conference on Information Networking (ICOIN). IEEE, 2019. http://dx.doi.org/10.1109/icoin.2019.8718124.
Der volle Inhalt der QuelleHarrington, Peter, Wai Pang Ng und Richard Binns. „Autonomous drone control within a Wi-Fi network“. In 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). IEEE, 2020. http://dx.doi.org/10.1109/csndsp49049.2020.9249585.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Autonomous network control"
Pearl, Judea. Dynamic Network Techniques for Autonomous Planning and Control. Fort Belvoir, VA: Defense Technical Information Center, November 2000. http://dx.doi.org/10.21236/ada387551.
Der volle Inhalt der QuelleTzonev, Nick. PR-396-183905-R01 Autonomous System For Monitoring Pipeline River Crossings. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), Juni 2021. http://dx.doi.org/10.55274/r0012110.
Der volle Inhalt der QuelleHovakimyan, Naira, Hunmin Kim, Wenbin Wan und Chuyuan Tao. Safe Operation of Connected Vehicles in Complex and Unforeseen Environments. Illinois Center for Transportation, August 2022. http://dx.doi.org/10.36501/0197-9191/22-016.
Der volle Inhalt der QuelleEvent-Triggered Adaptive Robust Control for Lateral Stability of Steer-by-Wire Vehicles with Abrupt Nonlinear Faults. SAE International, Juli 2022. http://dx.doi.org/10.4271/2022-01-5056.
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