Bibliografías temáticas / Distributed Moving Horizon Estimation

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Literatura académica sobre el tema "Distributed Moving Horizon Estimation"

Autor: Grafiati
Publicado: 25 de mayo de 2024
Última modificación: 31 de julio de 2025

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Artículos de revistas sobre el tema "Distributed Moving Horizon Estimation"

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Venturino, Antonello, Cristina Stoica Maniu, Sylvain Bertrand, Teodoro Alamo, and Eduardo F. Camacho. "Distributed moving horizon state estimation for sensor networks with low computation capabilities." SYSTEM THEORY, CONTROL AND COMPUTING JOURNAL 1, no. 1 (2021): 81–87. http://dx.doi.org/10.52846/stccj.2021.1.1.14.

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This paper focuses on distributed state estimation for sensor network observing a discrete-time linear system. The provided solution is based on a Distributed Moving Horizon Estimation (DMHE) algorithm considering a pre-estimating Luenberger observer in the formulation of the local problem solved by each sensor. This leads to reduce the computation load, while preserving the accuracy of the estimation. Moreover, observability properties of local sensors are used for tuning the weights related to consensus information fusion built on a rank-based condition, in order to improve the convergence o
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Farina, Marcello, Giancarlo Ferrari-Trecate, and Riccardo Scattolini. "Distributed moving horizon estimation for nonlinear constrained systems." IFAC Proceedings Volumes 43, no. 14 (2010): 909–14. http://dx.doi.org/10.3182/20100901-3-it-2016.00103.

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Farina, Marcello, Giancarlo Ferrari-Trecate, and Riccardo Scattolini. "Distributed Moving Horizon Estimation for Linear Constrained Systems." IEEE Transactions on Automatic Control 55, no. 11 (2010): 2462–75. http://dx.doi.org/10.1109/tac.2010.2046058.

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Battistelli, Giorgio. "Distributed Moving-Horizon Estimation With Arrival-Cost Consensus." IEEE Transactions on Automatic Control 64, no. 8 (2019): 3316–23. http://dx.doi.org/10.1109/tac.2018.2879598.

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Farina, Marcello, Giancarlo Ferrari-Trecate, and Riccardo Scattolini. "Distributed moving horizon estimation for nonlinear constrained systems." International Journal of Robust and Nonlinear Control 22, no. 2 (2010): 123–43. http://dx.doi.org/10.1002/rnc.1676.

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Wang, Shoudong, and Binqiang Xue. "Distributed Moving Horizon Fusion Estimation for Nonlinear Constrained Uncertain Systems." Mathematics 11, no. 6 (2023): 1507. http://dx.doi.org/10.3390/math11061507.

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This paper studies the state estimation of a class of distributed nonlinear systems. A new robust distributed moving horizon fusion estimation (DMHFE) method is proposed to deal with the norm-bounded uncertainties and guarantee the estimation performance. Based on the given relationship between a state covariance matrix and an error covariance matrix, estimated values of the unknown parameters in the system model can be obtained. Then, a local moving horizon estimation optimization algorithm is constructed by using the measured values of sensor nodes themselves, the measured information of adj
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Meynen, Sönke, Sören Hohmann, and Dirk Feẞler. "Fault Detection for Distributed Uncertain Systems using Moving Horizon Estimation." IFAC-PapersOnLine 55, no. 6 (2022): 234–41. http://dx.doi.org/10.1016/j.ifacol.2022.07.135.

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Zeng, Jing, and Jinfeng Liu. "Distributed State Estimation Based Distributed Model Predictive Control." Mathematics 9, no. 12 (2021): 1327. http://dx.doi.org/10.3390/math9121327.

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In this work, we consider output-feedback distributed model predictive control (DMPC) based on distributed state estimation with bounded process disturbances and output measurement noise. Specifically, a state estimation scheme based on observer-enhanced distributed moving horizon estimation (DMHE) is considered for distributed state estimation purposes. The observer-enhanced DMHE ensures that the state estimates of the system reach a small neighborhood of the actual state values quickly and then maintain within the neighborhood. This implies that the estimation error is bounded. Based on the
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Zhang, Jing, and Jinfeng Liu. "Two triggered information transmission algorithms for distributed moving horizon state estimation." Systems & Control Letters 65 (March 2014): 1–12. http://dx.doi.org/10.1016/j.sysconle.2013.12.003.

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Zhang, Jing, and Jinfeng Liu. "Distributed moving horizon state estimation for nonlinear systems with bounded uncertainties." Journal of Process Control 23, no. 9 (2013): 1281–95. http://dx.doi.org/10.1016/j.jprocont.2013.08.005.

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Tesis sobre el tema "Distributed Moving Horizon Estimation"

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Philipp, Peter [Verfasser]. "Centralized and Distributed Moving Horizon Strategies for State Estimation of Networked Control Systems / Peter Philipp." München : Verlag Dr. Hut, 2014. http://d-nb.info/1050331699/34.

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Venturino, Antonello. "Constrained distributed state estimation for surveillance missions using multi-sensor multi-robot systems." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST118.

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Les algorithmes distribués sont dorénavant présents dans de nombreux aspects de l'Automatique avec des applications pour des systèmes multi-robots, des réseaux de capteurs, couvrant des sujets tels que la commande, l'estimation d'état, la détection de défauts, la détection et l'atténuation des cyberattaques sur les systèmes cyber-physiques, etc. En effet, les systèmes distribués sont confrontés à des problèmes tels que l'extensibilité à un grand nombre d'agents et la communication entre eux. Dans les applications de systèmes multi-agents (par exemple, flotte de robots mobiles, réseaux de capte
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Philipp, Peter [Verfasser], Boris [Akademischer Betreuer] Lohmann, and Jan [Akademischer Betreuer] Lunze. "Centralized and Distributed Moving Horizon Strategies for State Estimation of Networked Control Systems / Peter Philipp. Gutachter: Jan Lunze ; Boris Lohmann. Betreuer: Boris Lohmann." München : Universitätsbibliothek der TU München, 2014. http://d-nb.info/1048176207/34.

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Philipp, Peter Verfasser], Boris [Akademischer Betreuer] Lohmann, and Jan [Akademischer Betreuer] [Lunze. "Centralized and Distributed Moving Horizon Strategies for State Estimation of Networked Control Systems / Peter Philipp. Gutachter: Jan Lunze ; Boris Lohmann. Betreuer: Boris Lohmann." München : Universitätsbibliothek der TU München, 2014. http://nbn-resolving.de/urn:nbn:de:bvb:91-diss-20140131-1175508-0-0.

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Segovia, Castillo Pablo. "Model-based control and diagnosis of inland navigation networks." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/671004.

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This thesis regards the problem of optimal management of water resources in inland navigation networks from a control theory perspective. In particular, the main objective to be attained consists in guaranteeing the navigability condition of the network, i.e., ensuring that the water levels are such that vessels can travel safely. More specifically, the water levels must be kept within an interval around the setpoint. Other common objectives include minimizing the operational cost and ensuring a long lifespan of the equipment. However, inland navigation networks are large-scale systems charact
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Ramalingam, Mohan Kumar. "Moving Horizon Estimation with Dynamic Programming." Cleveland State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=csu1386778712.

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Schneider, René [Verfasser]. "Iterative Partition-Based Moving-Horizon State Estimation / René Schneider." Aachen : Shaker, 2017. http://d-nb.info/1138178179/34.

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Schneider, René [Verfasser], Wolfgang [Akademischer Betreuer] Marquardt, and Riccardo [Akademischer Betreuer] Scattolini. "Iterative partition-based moving-horizon state estimation / René Schneider ; Wolfgang Marquardt, Riccardo Scattolini." Aachen : Universitätsbibliothek der RWTH Aachen, 2017. http://d-nb.info/1162845856/34.

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Zhang, Hanzhong. "A moving boundary problem in a distributed parameter system with application to diode modeling." Access restricted to users with UT Austin EID, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3037035.

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Volker, Anna. "Explicit/multi-parametric moving horizon estimation and model : predictive control & application to small unmanned aerial vehicles." Thesis, Imperial College London, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538787.

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Libros sobre el tema "Distributed Moving Horizon Estimation"

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Gharbi, Meriem. Proximity Moving Horizon Estimation. Logos Verlag Berlin, 2022.

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Capítulos de libros sobre el tema "Distributed Moving Horizon Estimation"

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Li, Shaoyuan, Yi Zheng, and Binqiang Xue. "Moving Horizon State Estimation for Networked Systems with Random Packet Loss." In Intelligent Optimal Control for Distributed Industrial Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0268-2_2.

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Rawlings, James B. "Moving Horizon Estimation." In Encyclopedia of Systems and Control. Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-5058-9_4.

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Rawlings, James B. "Moving Horizon Estimation." In Encyclopedia of Systems and Control. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5102-9_4-1.

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Rawlings, James B., and Douglas A. Allan. "Moving Horizon Estimation." In Encyclopedia of Systems and Control. Springer London, 2020. http://dx.doi.org/10.1007/978-1-4471-5102-9_4-2.

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Rawlings, James B., and Douglas A. Allan. "Moving Horizon Estimation." In Encyclopedia of Systems and Control. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_4.

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Allan, Douglas A., and James B. Rawlings. "Moving Horizon Estimation." In Handbook of Model Predictive Control. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77489-3_5.

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Rao, Christopher V., and James B. Rawlings. "Nonlinear Moving Horizon State Estimation." In Nonlinear Model Predictive Control. Birkhäuser Basel, 2000. http://dx.doi.org/10.1007/978-3-0348-8407-5_3.

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Muske, Kenneth R., and James B. Rawlings. "Nonlinear Moving Horizon State Estimation." In Methods of Model Based Process Control. Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0135-6_14.

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Liu, Qinyuan, Zidong Wang, and Xiao He. "Moving-Horizon Estimation with Binary Encoding Schemes." In Stochastic Control and Filtering over Constrained Communication Networks. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00157-5_11.

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Georgesan, Gejo, and K. Surender. "Road Vehicle Tracking Using Moving Horizon Estimation." In Algorithms for Intelligent Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5747-4_22.

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Actas de conferencias sobre el tema "Distributed Moving Horizon Estimation"

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D'Amato, Egidio. "Distributed Moving Horizon Estimation and Consensus for Enhanced Satellite Orbit Determination Within Constellations." In 31st IAA Symposium on Small Satellite Missions, Held at the 75th International Astronautical Congress (IAC 2024). International Astronautical Federation (IAF), 2024. https://doi.org/10.52202/078365-0158.

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Wang, Bingheng, Xuyang Chen, and Lin Zhao. "Trust-Region Neural Moving Horizon Estimation for Robots." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10611703.

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Krauss, Isabelle, Julian D. Schiller, Victor G. Lopez, and Matthias A. Müller. "Event-triggered moving horizon estimation for nonlinear systems." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10886849.

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Venturino, Antonello, Sylvain Bertrand, Cristina Stoica Maniu, Teodoro Alamo, and Eduardo F. Camacho. "Distributed moving horizon estimation with pre-estimating observer." In 2020 24th International Conference on System Theory, Control and Computing (ICSTCC). IEEE, 2020. http://dx.doi.org/10.1109/icstcc50638.2020.9259766.

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Philipp, Peter, and Thomas Schmid-Zurek. "Distributed moving horizon estimation via dual decomposition." In 2012 IEEE 51st Annual Conference on Decision and Control (CDC). IEEE, 2012. http://dx.doi.org/10.1109/cdc.2012.6426275.

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Chen, Tengpeng, Dexiang Zhou, Tri Tran, et al. "Distributed Moving Horizon Estimation for power systems." In 2015 IEEE Power & Energy Society General Meeting. IEEE, 2015. http://dx.doi.org/10.1109/pesgm.2015.7286281.

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Farina, Marcello, Giancarlo Ferrari-Trecate, and Riccardo Scattolini. "A moving horizon scheme for distributed state estimation." In 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC). IEEE, 2009. http://dx.doi.org/10.1109/cdc.2009.5400244.

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Zhang, Jing, and Jinfeng Liu. "Distributed moving horizon state estimation with triggered communication." In 2014 American Control Conference - ACC 2014. IEEE, 2014. http://dx.doi.org/10.1109/acc.2014.6859097.

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Hasan, Agus, and Lars Imsland. "Moving horizon estimation in managed pressure drilling using distributed models." In 2014 IEEE Conference on Control Applications (CCA). IEEE, 2014. http://dx.doi.org/10.1109/cca.2014.6981406.

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Jing Zeng and Jinfeng Liu. "Distributed moving horizon estimation subject to communication delays and losses." In 2015 American Control Conference (ACC). IEEE, 2015. http://dx.doi.org/10.1109/acc.2015.7172205.

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Informes sobre el tema "Distributed Moving Horizon Estimation"

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Yang, Yu, Hen-Geul Yeh, and Cesar Ortiz. Battery Management System Development for Electric Vehicles and Fast Charging Infrastructure Improvement. Mineta Transportation Institute, 2024. http://dx.doi.org/10.31979/mti.2024.2325.

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The electric vehicle (EV) has become increasingly popular due to its being zero-emission. However, a significant challenge faced by EV drivers is the range anxiety associated with battery usage. Addressing this concern, this project develops a more efficient battery management system (BMS) for electric vehicles based on a real-time, state-of-charge (SOC) estimation. The proposed study delivers three modules: (1) a new equivalent circuit model (ECM) for lithium-ion batteries, (2) a new SOC estimator based on the moving horizon method, and (3) an on-board FPGA implementation of the classical Cou
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