Добірка наукової літератури з теми "Scalable modeling and control"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Scalable modeling and control".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Статті в журналах з теми "Scalable modeling and control":
Voice, Thomas. "STOCHASTICALLY SCALABLE FLOW CONTROL." Probability in the Engineering and Informational Sciences 23, no. 4 (July 14, 2009): 675–98. http://dx.doi.org/10.1017/s0269964809990076.
Zengin, Ahmet. "Modeling discrete event scalable network systems." Information Sciences 181, no. 5 (March 2011): 1028–43. http://dx.doi.org/10.1016/j.ins.2010.10.023.
Chernyi, Sergei G., Aleksei V. Vyngra, and Bogdan P. Novak. "Physical modeling of an automated ship’s list control system." Journal of Intelligent & Fuzzy Systems 39, no. 6 (December 4, 2020): 8399–408. http://dx.doi.org/10.3233/jifs-189158.
Kim, Byungju, Dongha Lee, Jinoh Oh, and Hwanjo Yu. "Scalable disk-based topic modeling for memory limited devices." Information Sciences 516 (April 2020): 353–69. http://dx.doi.org/10.1016/j.ins.2019.12.058.
Yin, Hang, Anastasia Varava, and Danica Kragic. "Modeling, learning, perception, and control methods for deformable object manipulation." Science Robotics 6, no. 54 (May 26, 2021): eabd8803. http://dx.doi.org/10.1126/scirobotics.abd8803.
Gómez, Abel, Xabier Mendialdua, Konstantinos Barmpis, Gábor Bergmann, Jordi Cabot, Xabier de Carlos, Csaba Debreceni, Antonio Garmendia, Dimitrios S. Kolovos, and Juan de Lara. "Scalable modeling technologies in the wild: an experience report on wind turbines control applications development." Software and Systems Modeling 19, no. 5 (January 22, 2020): 1229–61. http://dx.doi.org/10.1007/s10270-020-00776-8.
Rocha, André M., Pedro Casau, and Rita Cunha. "A Control Algorithm for Early Wildfire Detection Using Aerial Sensor Networks: Modeling and Simulation." Drones 6, no. 2 (February 11, 2022): 44. http://dx.doi.org/10.3390/drones6020044.
Vermulst, Bas J. D., Jorge L. Duarte, Elena A. Lomonova, and Korneel G. E. Wijnands. "Scalable multi‐port active‐bridge converters: modelling and optimised control." IET Power Electronics 10, no. 1 (January 2017): 80–91. http://dx.doi.org/10.1049/iet-pel.2016.0191.
Yang, Jingyu, Wen Shi, Huanjing Yue, Kun Li, Jian Ma, and Chunping Hou. "Spatiotemporally scalable matrix recovery for background modeling and moving object detection." Signal Processing 168 (March 2020): 107362. http://dx.doi.org/10.1016/j.sigpro.2019.107362.
Wydrowski, B., L. L. H. Andrew, and M. Zukerman. "MaxNet: a congestion control architecture for scalable networks." IEEE Communications Letters 7, no. 10 (October 2003): 511–13. http://dx.doi.org/10.1109/lcomm.2003.818888.
Дисертації з теми "Scalable modeling and control":
Jordan, Philip [Verfasser]. "Scalable Modelling of Aircraft Environmental Control Systems / Philip Jordan." München : Verlag Dr. Hut, 2019. http://d-nb.info/118151441X/34.
Kumar, Vibhore. "Enabling scalable self-management for enterprise-scale systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24788.
Committee Chair: Schwan, Karsten; Committee Member: Cooper, Brian F.; Committee Member: Feamster, Nick; Committee Member: Liu, Ling; Committee Member: Sahai, Akhil.
Chuku, Ejike E. "Security and Performance Engineering of Scalable Cognitive Radio Networks. Sensing, Performance and Security Modelling and Analysis of ’Optimal’ Trade-offs for Detection of Attacks and Congestion Control in Scalable Cognitive Radio Networks." Thesis, University of Bradford, 2019. http://hdl.handle.net/10454/18448.
May, Brian 1975. "Scalable access control." Monash University, School of Computer Science and Software, 2001. http://arrow.monash.edu.au/hdl/1959.1/8043.
Aroua, Ayoub. "Mise à l'échelle des entraînements électromécaniques pour la conception au niveau système dans les premières phases de développement des véhicules électriques." Electronic Thesis or Diss., Université de Lille (2022-....), 2023. http://www.theses.fr/2023ULILN042.
The automotive industry is required to accelerate the development and deployment of electrified vehicles at a faster pace than ever, to align the transportation sector with the climate goals. Reducing the development time of electric vehicles becomes an urgent priority. On the other hand, the industry is challenged by the increasing complexity and large design space of the emerging electrified powertrains. The existing approaches to address component design, such as numerical methods exemplified by finite element method, computational fluid dynamic, etc., are based on a detailed design process. This leads to a long computational burden when trying to incorporate them at system-level. Speeding up the early development phases of electrified vehicles necessitates new methodologies and tools, supporting the exploration of the system-level design space. These methodologies should allow for assessing different sizing choices of electrified powertrains in the early development phases, both efficiently in terms of computational time and with reliable results in terms of energy consumption at system-level. To address this challenge, this Ph.D. thesis aims to develop a scaling methodology for electric axles, allowing system-level investigation of different power-rated electric vehicles. The electric axle considered in this thesis comprises a voltage source inverter, an electric machine, a gearbox, and a control unit. The scaling procedure is aimed at predicting the data of a newly defined design of a given component with different specifications based on a reference design, without redoing time and effort-consuming steps. For this purpose, different derivations of scaling laws of the electric axle components are thoroughly discussed and compared at component-level in terms of power loss scaling. A particular emphasis is placed on examining the linear losses-to-power scaling method, which is widely employed in system-level studies. This is because, this method presents questionable assumptions, and has not been the subject of a comprehensive examination. A key contribution of the presented work is the derivation of power loss scaling laws of gearboxes, which has been identified as a gap in the current literature. This is achieved through an intensive experimental campaign using commercial gearboxes. To incorporate the scaling laws at system-level and study the interaction between the scaled components, the energetic macroscopic representation formalism is employed. The novelty of the proposed method lies in structuring a scalable model and control for a reference electric axle to be used in system-level simulation. The novel organization consists of a reference model and control complemented by two power adaptation elements at the electrical and mechanical sides. These latter elements consider the scaling effects, including the power losses. The methodology is applied for different study cases of battery electric vehicles, ranging from light to heavy-duty vehicles. Particular attention is paid to assessing the impact of the linear power-to-losses scaling method on the energy consumption considering different power scaling factors and driving cycles, as compared to high-fidelity scaling methods
TUCCI, MICHELE. "Scalable control of islanded microgrids." Doctoral thesis, Università degli studi di Pavia, 2018. http://hdl.handle.net/11571/1214890.
In the recent years, the increasing penetration of renewable energy sources has motivated a growing interest for microgrids, energy networks composed of interconnected Distributed Generation Units (DGUs) and loads. Microgrids are self-sustained electric systems that can operate either connected to the main grid or detached from it. In this thesis, we focus on the latter case, thus dealing with the so-called Islanded microGrids (ImGs). We propose scalable control design methodologies for both AC and DC ImGs, allowing DGUs and loads to be connected in general topologies and enter/leave the network over time. In order to ensure safe and reliable operations, we mirror the flexibility of ImGs structures in their primary and secondary control layers. Notably, off-line control design hinges on Plug-and-Play (PnP) synthesis, meaning that the computation of individual regulators is complemented by local optimization-based tests for denying dangerous plug-in/out requests. The solutions presented in this work aim to address some of the key challenges arising in control of AC and DC ImGs, while overcoming the limitations of the existing approaches. More precisely, this thesis comprises the following main contributions: (i) the development of decentralized primary control schemes for load-connected networks (i.e. where local loads appear only at the output terminals of each DGU) ensuring voltage stability in DC ImGs, and voltage and frequency stability in AC ImGs. In contrast with the most commonly used control strategies available in the literature, our regulators guarantee offset-free tracking of reference signals. Moreover, the proposed primary local controllers can be designed or updated on-the-fly when DGUs are plugged in/out, and the closed-loop stability of the ImG is always preserved. (ii) Novel approximate network reduction methods for handling totally general interconnections of DGUs and loads in AC ImGs. We study and exploit Kron reduction in order to derive an equivalent load-connected model of the original ImG, and designing stabilizing voltage and frequency regulators, independently of the ImG topology. (iii) Distributed secondary control schemes, built on top of primary layers, for accurate reactive power sharing in AC ImGs, and current sharing and voltage balancing in DC ImGs. In the latter case, we prove that the desired coordinated behaviors are achieved in a stable fashion and we describe how to design secondary regulators in a PnP manner when DGUs are added/removed to/from the network. (iv) Theoretical results are validated through extensive simulations, and some of the proposed design algorithms have been successfully tested on real ImG platforms.
Liu, Xin. "Scalable online simulation for modeling grid dynamics /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2004. http://wwwlib.umi.com/cr/ucsd/fullcit?p3158471.
Gramsamer, Ferdinand. "Scalable flow control for interconnection networks /." [Zürich] : [Institut für Technische Informatik und Kommunikationsnetze TIK, ETH Zürich], 2003. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=15020.
Gevros, Panagiotis. "Congestion control mechanisms for scalable bandwidth sharing." Thesis, University College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.249696.
Roman, Alexandru Bogdan. "Scalable cross-layer wireless medium access control." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609506.
Книги з теми "Scalable modeling and control":
Pelikan, Martin, Kumara Sastry, and Erick CantúPaz, eds. Scalable Optimization via Probabilistic Modeling. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-34954-9.
Chiuso, Alessandro, Stefano Pinzoni, and Augusto Ferrante, eds. Modeling, Estimation and Control. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73570-0.
Isermann, Rolf. Engine Modeling and Control. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-39934-3.
Babuška, Robert. Fuzzy Modeling for Control. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-4868-9.
Piegat, Andrzej. Fuzzy Modeling and Control. Heidelberg: Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1824-6.
IIASA, Conference on "Discrete Event Systems" (1987 Sopron Hungary). Modeling and adaptive control. Berlin: Springer-Verlag, 1988.
Eyman, Earl D. Modeling, simulation, and control. St. Paul: West Pub. Co., 1988.
Spong, Mark W. Robot modeling and control. Hoboken, NJ: John Wiley & Sons, 2006.
Babuška, Robert. Fuzzy modeling for control. Boston: Kluwer Academic Publishers, 1998.
Babuška, Robert. Fuzzy modeling for control. New York: Springer, 1998.
Частини книг з теми "Scalable modeling and control":
Gómez, Abel, Xabier Mendialdua, Gábor Bergmann, Jordi Cabot, Csaba Debreceni, Antonio Garmendia, Dimitrios S. Kolovos, Juan de Lara, and Salvador Trujillo. "On the Opportunities of Scalable Modeling Technologies: An Experience Report on Wind Turbines Control Applications Development." In Modelling Foundations and Applications, 300–315. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61482-3_18.
Spinelli, Stefano. "Optimal Management and Control of Smart Thermal-Energy Grids." In Special Topics in Information Technology, 15–27. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85918-3_2.
Mertes, J., M. Glatt, L. Yi, M. Klar, B. Ravani, and J. C. Aurich. "Modeling and Implementation of a 5G-Enabled Digital Twin of a Machine Tool Based on Physics Simulation." In Proceedings of the 3rd Conference on Physical Modeling for Virtual Manufacturing Systems and Processes, 90–110. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35779-4_6.
Ko, Kwang O., Doug Young Suh, Young Soo Kim, and Jin Sang Kim. "Feedback Control Using State Prediction and Channel Modeling Using Lower Layer Information for Scalable Multimedia Streaming Service." In Networking - ICN 2005, 901–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31956-6_106.
Sosnowski, Markus, Johannes Zirngibl, Patrick Sattler, and Georg Carle. "DissecTLS: A Scalable Active Scanner for TLS Server Configurations, Capabilities, and TLS Fingerprinting." In Passive and Active Measurement, 110–26. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28486-1_6.
Farina, Marcello, Giancarlo Ferrari-Trecate, Colin Jones, Stefano Riverso, and Melanie Zeilinger. "Scalable MPC Design." In Handbook of Model Predictive Control, 259–83. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77489-3_12.
Jónsson, Björn Þór, Marcel Worring, Jan Zahálka, Stevan Rudinac, and Laurent Amsaleg. "Ten Research Questions for Scalable Multimedia Analytics." In MultiMedia Modeling, 290–302. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27674-8_26.
Takahashi, Keichi, Kohei Ichikawa, and Gerald M. Pao. "Toward Scalable Empirical Dynamic Modeling." In Sustained Simulation Performance 2022, 61–69. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-41073-4_5.
Cao, Qian, Dongdong Zhang, and Chengyu Sun. "Quality Scalable Video Coding Based on Neural Representation." In MultiMedia Modeling, 396–409. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53305-1_30.
Heinz, Ernst A. "Modeling the “Go Deep” Behaviour." In Scalable Search in Computer Chess, 145–56. Wiesbaden: Vieweg+Teubner Verlag, 2000. http://dx.doi.org/10.1007/978-3-322-90178-1_10.
Тези доповідей конференцій з теми "Scalable modeling and control":
Shiming Chen and Huajing Fang. "Modeling and Control of Scalable Engineering Swarm." In 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1712395.
Wei, Xi, and Giorgio Rizzoni. "A Scalable Approach for Energy Converter Modeling and Supervisory Control Design." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/dsc-24541.
Su Sheng. "A scalable agent based load-modeling system." In 6th International Conference on Advances in Power System Control, Operation and Management. Proceedings. APSCOM 2003. IEE, 2003. http://dx.doi.org/10.1049/cp:20030626.
Ghaemi, Reza, Aditya Kumar, Pierino Bonanni, and Nikita Visnevski. "Scalable Optimal Flexibility Control, modeling and estimation of commercial buildings." In 2020 American Control Conference (ACC). IEEE, 2020. http://dx.doi.org/10.23919/acc45564.2020.9147398.
Sirisena, H., and V. Sreeram. "Modeling of scalable TCP for AQM design in high speed networks." In 2006 American Control Conference. IEEE, 2006. http://dx.doi.org/10.1109/acc.2006.1657612.
Kerley, Daniel, Edward J. Park, and Jennifer Dunn. "Distributed Modeling and Decentralized H∞ Control of a Segmented Telescope Mirror." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-44145.
Weinstein, Jason, and Aleksandar Prodic. "Plug-and-play digital controllers for scalable low-power SMPS." In 2008 11th Workshop on Control and Modeling for Power Electronics (COMPEL). IEEE, 2008. http://dx.doi.org/10.1109/compel.2008.4634706.
Solomentsev, Michael, and Alex J. Hanson. "Highly-Scalable Differential Power Processing Architecture for On-Vehicle Photovoltaics." In 2023 IEEE 24th Workshop on Control and Modeling for Power Electronics (COMPEL). IEEE, 2023. http://dx.doi.org/10.1109/compel52896.2023.10220974.
Jeong, Hoejeong, Hyeun-Tae Cho, Taewon Kim, Yu-Chen Liu, and Katherine A. Kim. "A Scalable Unit Differential Power Processing System Design for Photovoltaic Applications." In 2018 IEEE 19th Workshop on Control and Modeling for Power Electronics (COMPEL). IEEE, 2018. http://dx.doi.org/10.1109/compel.2018.8460157.
Yishen Sun, C. C. Lee, R. Berry, and A. H. Haddad. "An application of the control theoretic modeling for a scalable TCP ACK pacer." In Proceedings of the 2004 American Control Conference. IEEE, 2004. http://dx.doi.org/10.23919/acc.2004.1383809.
Звіти організацій з теми "Scalable modeling and control":
Szymanski, Boleslaw, Shivkumar Kalyanaraman, Biplab Sikdar, and Christopher Carothers. Scalable Online Network Modeling and Simulation. Fort Belvoir, VA: Defense Technical Information Center, August 2005. http://dx.doi.org/10.21236/ada437818.
Maxey, Martin. Modeling Mesoscale Processes of Scalable Synthesis. Office of Scientific and Technical Information (OSTI), May 2018. http://dx.doi.org/10.2172/1496226.
Xu, Jinchao. Modeling Mesoscale Processes of Scalable Synthesis. Office of Scientific and Technical Information (OSTI), November 2020. http://dx.doi.org/10.2172/1709100.
Melin, Alexander M., Yichen Zhang, and Mohammed M. Olama. Scalable Coordination and Control for Multiple Microgrids. Office of Scientific and Technical Information (OSTI), September 2016. http://dx.doi.org/10.2172/1454409.
E, Weinan, and Amit Samanta. Modeling Mesoscale Processes of Scalable Synthesis (Final Report). Office of Scientific and Technical Information (OSTI), March 2019. http://dx.doi.org/10.2172/1501890.
Johnson, Jay Tillay. Secure Scalable Control and Communications for Distributed PV. Office of Scientific and Technical Information (OSTI), January 2019. http://dx.doi.org/10.2172/1491602.
von Meier, Alexandra. Phasor-Based Control for Scalable Solar PV Integration. Office of Scientific and Technical Information (OSTI), January 2021. http://dx.doi.org/10.2172/1763038.
Yang, Zhaoqing, Alicia Gorton, Taiping Wang, Jonathan Whiting, Andrea Copping, Kevin Haas, Phillip Wolfram, and Solomon Yim. Multi-resolution, Multi-scale Modeling for Scalable Macroalgae Production. Office of Scientific and Technical Information (OSTI), May 2020. http://dx.doi.org/10.2172/1642475.
Keromytis, Angelos D., and Jonathan M. Smith. Requirements for Scalable Access Control and Security Management Architectures. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada437426.
Amiri, Khalil, Garth Gibson, and Richard Golding. Scalable Concurrency Control and Recovery for Shared Storage Arrays. Fort Belvoir, VA: Defense Technical Information Center, February 1999. http://dx.doi.org/10.21236/ada363551.