Gotowa bibliografia na temat „Autonomous network control”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Spis treści
Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Autonomous network control”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Artykuły w czasopismach na temat "Autonomous network control"
Kim, Jae-Hoon, Seungchul Lee i Sengphil Hong. "Autonomous Operation Control of IoT Blockchain Networks". Electronics 10, nr 2 (17.01.2021): 204. http://dx.doi.org/10.3390/electronics10020204.
Pełny tekst źródłaAlsuwian, Turki, Mian Hamza Usman i Arslan Ahmed Amin. "An Autonomous Vehicle Stability Control Using Active Fault-Tolerant Control Based on a Fuzzy Neural Network". Electronics 11, nr 19 (1.10.2022): 3165. http://dx.doi.org/10.3390/electronics11193165.
Pełny tekst źródłaKim, Eric J., i Ruben E. Perez. "Neuroevolutionary Control for Autonomous Soaring". Aerospace 8, nr 9 (17.09.2021): 267. http://dx.doi.org/10.3390/aerospace8090267.
Pełny tekst źródłaBotchkaryov, 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.
Pełny tekst źródłaAkimoto, Y., H. Tanaka, H. Ogi, H. Taoka, S. Nishida i T. Sakaguchi. "Autonomous Distributed Network Architecture for Control System". IFAC Proceedings Volumes 21, nr 12 (wrzesień 1988): 21–27. http://dx.doi.org/10.1016/b978-0-08-036938-9.50009-1.
Pełny tekst źródłaJain, Ankur, i 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.
Pełny tekst źródłaJawad, Luay, Arshdeep Singh-Chudda, Abhishek Shankar i 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.
Pełny tekst źródłaKumar, 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.
Pełny tekst źródłaGao, Youtao, Zhicheng You i 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.
Pełny tekst źródłaFujii, Teruo, i 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.
Pełny tekst źródłaRozprawy doktorskie na temat "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.
Pełny tekst źródłaIn 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.
Pełny tekst źródłaIncludes bibliographical references (leaf 77).
by Charles P. Tung.
B.S.
M.Eng.
Hemlin, Karl, i 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.
Pełny tekst źródłaGarratt, Matthew Adam, i 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.
Pełny tekst źródłaDalamagkidis, Konstantinos. "Autonomous vertical autorotation for unmanned helicopters". [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003147.
Pełny tekst źródłaYoumans, 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/.
Pełny tekst źródłaDarr, Matthew John. "DEVELOPMENT AND EVALUATION OF A CONTROLLER AREA NETWORK BASED AUTONOMOUS VEHICLE". UKnowledge, 2004. http://uknowledge.uky.edu/gradschool_theses/192.
Pełny tekst źródłaPuttige, 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.
Pełny tekst źródłaLivianu, 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.
Pełny tekst źródłaCommittee 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.
Pełny tekst źródłaThesis 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.
Książki na temat "Autonomous network control"
W, Protzel Peter, Palumbo Daniel L i Langley Research Center, red. Automatic learning rate adjustment for self-supervising autonomous robot control. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1992.
Znajdź pełny tekst źródłaVarlamov, Oleg. Fundamentals of creating MIVAR expert systems. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1513119.
Pełny tekst źródłaGanchev, Ivan. Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools. Cham: Springer Nature, 2018.
Znajdź pełny tekst źródłaVarlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.
Pełny tekst źródłaYoung, Forrest C. Phoenix autonomous underwater vehicle (AUV): Networked control of multiple analog and digital devices using LonTalk. Monterey, Calif: Naval Postgraduate School, 1997.
Znajdź pełny tekst źródłaTucci, Mario, i Marco Garetti, red. 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.
Pełny tekst źródłaAndo, 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.
Znajdź pełny tekst źródłaGuillermo, Navarro-Arribas, Cavalli Ana, Leneutre Jean i SpringerLink (Online service), red. 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.
Znajdź pełny tekst źródła1935-, Lasker G. E., International Institute for Advanced Studies in Systems Research and Cybernetics. i International Conference on Systems Research, Informatics, and Cybernetics. (10th : 1998 : Baden-Baden, Germany), red. 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.
Znajdź pełny tekst źródłaChapman, Airlie. Semi-Autonomous Networks: Effective Control of Networked Systems Through Protocols, Design, and Modeling. Springer, 2015.
Znajdź pełny tekst źródłaCzęści książek na temat "Autonomous network control"
Bao, Jie, i Shichao Xu. "Plantwide Control via a Network of Autonomous Controllers". W Plantwide Control, 385–416. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119968962.ch18.
Pełny tekst źródłaSchönberger, Jörn, i Herbert Kopfer. "Approaching the Application Borders of Network Capacity Control in Road Haulage". W 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.
Pełny tekst źródłaSekiyama, Kosuke, Katsuhiro Suzuki, Shigeru Fukunaga i Masaaki Date. "Autonomous Synchronization Scheme Access Control for Sensor Network". W Lecture Notes in Computer Science, 487–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11554028_68.
Pełny tekst źródłaZhang, Xiaokai, i Tianfang Yao. "A Study of Network Informal Language Using Minimal Supervision Approach". W 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.
Pełny tekst źródłaNodland, David, H. Zargarzadeh, Arpita Ghosh i S. Jagannathan. "Neural Network-Based Optimal Control of an Unmanned Helicopter". W 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.
Pełny tekst źródłaIsa, Khalid, i M. R. Arshad. "Neural Network Control of Buoyancy-Driven Autonomous Underwater Glider". W 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.
Pełny tekst źródłaAnwar, Mohd, Philip W. L. Fong, Xue-Dong Yang i Howard Hamilton. "Visualizing Privacy Implications of Access Control Policies in Social Network Systems". W 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.
Pełny tekst źródłaGrosspietsch, Karl-Erwin, i Tanya A. Silayeva. "Modified ART Network Architectures for the Control of Autonomous Systems". W 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.
Pełny tekst źródłaMing, Yan, Wang Jiaxing, Li Heqi i Liu Kai. "Research on Direct Lift Landing Control Based on Neural Network". W 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.
Pełny tekst źródłaGarcía, Juan Carlos, Marta Marrón, J. A. García, M. A. Sotelo, Jesús Ureña, J. L. Lázaro, F. J. Rodriguez, M. Mazo i Marisol Escudero. "An Autonomous Wheelchair with a LonWorks Network based Distributed Control System". W Field and Service Robotics, 405–10. London: Springer London, 1988. http://dx.doi.org/10.1007/978-1-4471-1273-0_61.
Pełny tekst źródłaStreszczenia konferencji na temat "Autonomous network control"
Coombes, Matthew, William Eaton, Owen McAree i Wen-Hua Chen. "Development of a generic network enabled autonomous vehicle system". W 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915211.
Pełny tekst źródłaKarimi Shahri, Pouria, Shubhankar Chintamani Shindgikar, Baisravan HomChaudhuri i Amir H. Ghasemi. "Optimal Lane Management in Heterogeneous Traffic Network". W ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9040.
Pełny tekst źródłaChapman, Airlie, i Mehran Mesbahi. "Semi-autonomous networks: Network resilience and adaptive trees". W 2010 49th IEEE Conference on Decision and Control (CDC). IEEE, 2010. http://dx.doi.org/10.1109/cdc.2010.5717850.
Pełny tekst źródłaCui, Rongxin, Chenguang Yang, Yang Li i Sanjay Sharma. "Neural network based reinforcement learning control of autonomous underwater vehicles with control input saturation". W 2014 UKACC 10th International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915114.
Pełny tekst źródłaLu, Qiang, i Zhaochen Zhang. "Chaotic Autonomous Developmental Neural Network". W 2019 5th International Conference on Control, Automation and Robotics (ICCAR). IEEE, 2019. http://dx.doi.org/10.1109/iccar.2019.8813424.
Pełny tekst źródłaQuader, Niamul, S. M. Masudur Rahman Al-Arif, Md Al Mamun Shaon, Kazi Khairul Islam i Abdur Raquib Ridwan. "Control of autonomous nanorobots in neural network". W 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2011. http://dx.doi.org/10.1109/bmei.2011.6098609.
Pełny tekst źródłaTusing, Nathan, i Richard Brooks. "Access Control Requirements for Autonomous Robotic Fleets". W WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0104.
Pełny tekst źródłaXie, Yuanrai, Zhixin Liu, Kai Ma i Yazhou Yuan. "Robust Power Control in D2D-Enabled Vehicular Communication Network". W 2019 3rd International Symposium on Autonomous Systems (ISAS). IEEE, 2019. http://dx.doi.org/10.1109/isass.2019.8757748.
Pełny tekst źródłaKurokawa, Ryota, Go Hasegawa i Masayuki Murata. "Biochemical-Inspired Autonomous Control of Virtualized Network Functions". W 2019 International Conference on Information Networking (ICOIN). IEEE, 2019. http://dx.doi.org/10.1109/icoin.2019.8718124.
Pełny tekst źródłaHarrington, Peter, Wai Pang Ng i Richard Binns. "Autonomous drone control within a Wi-Fi network". W 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). IEEE, 2020. http://dx.doi.org/10.1109/csndsp49049.2020.9249585.
Pełny tekst źródłaRaporty organizacyjne na temat "Autonomous network control"
Pearl, Judea. Dynamic Network Techniques for Autonomous Planning and Control. Fort Belvoir, VA: Defense Technical Information Center, listopad 2000. http://dx.doi.org/10.21236/ada387551.
Pełny tekst źródłaTzonev, Nick. PR-396-183905-R01 Autonomous System For Monitoring Pipeline River Crossings. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), czerwiec 2021. http://dx.doi.org/10.55274/r0012110.
Pełny tekst źródłaHovakimyan, Naira, Hunmin Kim, Wenbin Wan i Chuyuan Tao. Safe Operation of Connected Vehicles in Complex and Unforeseen Environments. Illinois Center for Transportation, sierpień 2022. http://dx.doi.org/10.36501/0197-9191/22-016.
Pełny tekst źródłaEvent-Triggered Adaptive Robust Control for Lateral Stability of Steer-by-Wire Vehicles with Abrupt Nonlinear Faults. SAE International, lipiec 2022. http://dx.doi.org/10.4271/2022-01-5056.
Pełny tekst źródła