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Artykuły w czasopismach na temat "Multiple model adaptive control"
Kuipers, Matthew, i Petros Ioannou. "Multiple Model Adaptive Control With Mixing". IEEE Transactions on Automatic Control 55, nr 8 (sierpień 2010): 1822–36. http://dx.doi.org/10.1109/tac.2010.2042345.
Pełny tekst źródłaYang, Xinhao, i Ze Li. "Congestion Control Based on Multiple Model Adaptive Control". Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/714320.
Pełny tekst źródłaLourenco, J. M. A., i J. M. Lemos. "Learning in switching multiple model adaptive control". IEEE Instrumentation and Measurement Magazine 9, nr 3 (czerwiec 2006): 24–29. http://dx.doi.org/10.1109/mim.2006.1637975.
Pełny tekst źródłaKim, Youngchol, Sunwook Choi i Taeshin Cho. "Multiple model adaptive control for interval systems". IFAC Proceedings Volumes 32, nr 2 (lipiec 1999): 4699–704. http://dx.doi.org/10.1016/s1474-6670(17)56801-9.
Pełny tekst źródłaZhang, Yingzhao, Weicun Zhang, Xiao Wang i Handong Li. "Multiple Model Adaptive Control of Flexible Arm". Proceedings of International Conference on Artificial Life and Robotics 24 (10.01.2019): 391–94. http://dx.doi.org/10.5954/icarob.2019.os14-2.
Pełny tekst źródłaNasr, Tamer Ahmed, Hossam A. Abdel Fattah i Adel A. R. Hanafy. "Multiple-model adaptive control for interval plants". International Journal of Control, Automation and Systems 10, nr 1 (luty 2012): 11–19. http://dx.doi.org/10.1007/s12555-012-0102-5.
Pełny tekst źródłaAnderson, Brian D. O., Thomas Brinsmead, Daniel Liberzon i A. Stephen Morse. "Multiple model adaptive control with safe switching". International Journal of Adaptive Control and Signal Processing 15, nr 5 (2001): 445–70. http://dx.doi.org/10.1002/acs.684.
Pełny tekst źródłaHespanha, Jo�o, Daniel Liberzon, A. Stephen Morse, Brian D. O. Anderson, Thomas S. Brinsmead i Franky De Bruyne. "Multiple model adaptive control. Part 2: switching". International Journal of Robust and Nonlinear Control 11, nr 5 (2001): 479–96. http://dx.doi.org/10.1002/rnc.594.
Pełny tekst źródłaMaybeck, P. S., i R. D. Stevens. "Reconfigurable flight control via multiple model adaptive control methods". IEEE Transactions on Aerospace and Electronic Systems 27, nr 3 (maj 1991): 470–80. http://dx.doi.org/10.1109/7.81428.
Pełny tekst źródłaHe, W. G., Howard Kaufman i Rob Roy. "Multiple Model Adaptive Control Procedure for Blood Pressure Control". IEEE Transactions on Biomedical Engineering BME-33, nr 1 (styczeń 1986): 10–19. http://dx.doi.org/10.1109/tbme.1986.325833.
Pełny tekst źródłaRozprawy doktorskie na temat "Multiple model adaptive control"
Buchstaller, Dominic. "Robust stability and performance for multiple model switched adaptive control". Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/72334/.
Pełny tekst źródłaWang, Yu. "Adaptive control and learning using multiple models". Thesis, Yale University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10783473.
Pełny tekst źródłaAdaptation can have different objectives. Compared to a learning behavior, which is mainly to optimize the rewards/experience obtained through the learning process, adaptive control is a type of adaptation that follows a specific target guided by a controller. Although the targets may be different, the two types of adaption share common research interests.
One of the popular research techniques for studying adaptation is the use of multiple models, where the system will utilize information from multiple environment observers instead of one to improve the adaptation behavior in terms of stability, speed and accuracy. In this thesis, applications of multiple models for two types of adaptation, adaptive control and learning, will be investigated separately. For adaptive control, the research focuses on second-level adaptation, which is a new multiple-model-based approach; for learning, the multiple model concept is designed and embedded into a type of reinforcement scheme: learning automata.
The stability, robustness and performance of second-level adaptation will be first investigated in the context of various environments, including time-varying plants and noisy disturbances. Then, a new design of second-level adaptation for general systems and input-output accessible systems will be discussed. The reasons for the improved performance using second-level adaptation are analyzed theoretically. The second part of the thesis contributes to a new method of learning automata using multiple models. The method is first applied to a two-state (binary) reward environment in the simplest case, and it is later extended to the feed-forward case when multiple states or actions are presented. Finally, general reinforcement learning automata for network cases will be discussed. In all cases, simulation studies are given, wherever appropriate, to demonstrate the improvement in performance compared to conventional approaches.
Brend, O. "Implementation and experimental evaluation of multiple model switched adaptive control for FES-based rehabilitation". Thesis, University of Southampton, 2014. https://eprints.soton.ac.uk/364612/.
Pełny tekst źródłaWang, Xiaoru. "Multi-Core Implementation of F-16 Flight Surface Control System Using GA Based Multiple Model Reference Adaptive Control Algorithm". University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1302130339.
Pełny tekst źródłaKamalasadan, Sukumar. "A New Generation of Adaptive Control: An Intelligent Supervisory Loop Approach". University of Toledo / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1087223752.
Pełny tekst źródłaSova, Václav. "Adaptivní řízení elektromechanických aktuátorů s využitím dopředného kompenzátoru založeného na více-modelovém přístupu". Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-391815.
Pełny tekst źródłaChoi, Jinbae. "Closed-Loop Optimal Control of Discrete-Time Multiple Model Linear Systems with Unknown Parameters". Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1441178373.
Pełny tekst źródłaNi, Lingli. "Fault-Tolerant Control of Unmanned Underwater Vehicles". Diss., Virginia Tech, 2001. http://hdl.handle.net/10919/28187.
Pełny tekst źródłaPh. D.
Pinguet, Jérémy. "Contribution à la synthèse de contrôleurs neuronaux robustes par imitation". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG002.
Pełny tekst źródłaThis thesis focuses on developing control systems by imitating behaviors or decisions meeting complex requirements. The objective is to perform the learning of a neural controller efficiently and robustly on a database containing these behaviors.The chosen approach unifies robust control tools with those of neural network modeling. Methods for identifying dynamic systems are first developed according to neural structures in cohesion with the representations of linear systems with varying parameters. Access to this field of study opens the way to stability and performance analysis of these neural models.The work then proposes to exploit these properties to address the robustness issues inherent to the learning of control laws. The proposed method of identifying robust controllers is based on evaluating the stability margins of the neural feedback loop. It is then possible to consolidate the robustness of the controllers through a learning strategy with stability optimization by a multi-objective formulation. In addition, the deployment of the controllers is performed using a multi-model adaptive control method.The approach is finally applied to aircraft autopilots via a co-simulation with a flight simulator characterized by its high modeling reliability. The control issues addressed are, in the first step, to guide the aircraft according to a given heading and altitude, while a second experiment focuses on following a flight path consisting of a series of waypoints. The neural autopilots are developed by imitating an existing autopilot and then by imitating a pilot
Gendron, Sylvain. "Model weighting adaptive control". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0007/NQ44437.pdf.
Pełny tekst źródłaKsiążki na temat "Multiple model adaptive control"
Jeon, Jung Taek. Multiple model adaptive control with application to DemoDICE. [Downsview, Ont.]: University of Toronto, Institute for Aerospace Studies, 2002.
Znajdź pełny tekst źródłaJeon, Jung Taek. Multiple model adaptive control with application to DemoDICE. Ottawa: National Library of Canada, 2002.
Znajdź pełny tekst źródłaDatta, Aniruddha. Adaptive Internal Model Control. London: Springer London, 1998. http://dx.doi.org/10.1007/978-0-85729-331-2.
Pełny tekst źródłaNguyen, Nhan T. Model-Reference Adaptive Control. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-56393-0.
Pełny tekst źródłaAdaptive internal model control. London: Springer, 1998.
Znajdź pełny tekst źródłaGoodwin, Graham, red. Model Identification and Adaptive Control. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0711-8.
Pełny tekst źródłaModel reference adaptive control of manipulators. Taunton, Somerset, England: Research Studies Press, 1990.
Znajdź pełny tekst źródłaUnited States. National Aeronautics and Space Administration., red. Model reference adaptive control of robots. Troy, N.Y: Rensselaer Polytechnic Institute, Electrical, Computer and Systems Engineering, 1991.
Znajdź pełny tekst źródłaRoderick, Murray-Smith, i Johansen Tor Arne, red. Multiple model approaches to modelling and control. London: Taylor & Francis, 1997.
Znajdź pełny tekst źródłaZourntos, Takis. Nonlinear adaptive control based on the related model. Ottawa: National Library of Canada, 1996.
Znajdź pełny tekst źródłaCzęści książek na temat "Multiple model adaptive control"
Lemos, João M., Rui Neves-Silva i José M. Igreja. "Multiple Model Adaptive Control". W Adaptive Control of Solar Energy Collector Systems, 105–30. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06853-4_4.
Pełny tekst źródłaSchott, Kevin D., i B. Wayne Bequette. "Multiple Model Adaptive Control (MMAC)". W Nonlinear Model Based Process Control, 33–57. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5094-1_2.
Pełny tekst źródłaFabri, Simon G., i Visakan Kadirkamanathan. "Multiple Model Dual Adaptive Control of Spatial Multimodal Systems". W Communications and Control Engineering, 213–41. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0319-6_10.
Pełny tekst źródłaFabri, Simon G., i Visakan Kadirkamanathan. "Multiple Model Dual Adaptive Control of Jump Nonlinear Systems". W Communications and Control Engineering, 187–212. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0319-6_9.
Pełny tekst źródłaLi, Jiayi, i Weicun Zhang. "Research on Weighted Multiple Model Adaptive Control Based on U-Model". W Lecture Notes in Electrical Engineering, 217–24. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8450-3_23.
Pełny tekst źródłaNarendra, Kumpati S., Osvaldo A. Driollet i Koshy George. "Adaptive Control Using Multiple Models: A Methodology". W Modeling, Control and Optimization of Complex Systems, 83–110. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-1139-7_5.
Pełny tekst źródłaZhang, Weicun, i Qing Li. "Stable Weighted Multiple Model Adaptive Control of Continuous-Time Plant". W Virtual Equivalent System Approach for Stability Analysis of Model-based Control Systems, 111–27. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5538-1_6.
Pełny tekst źródłaZhang, Yuzhen, Weicun Zhang i Jiqiang Wang. "New Progress on Research of Weighted Multiple Model Adaptive Control". W Lecture Notes in Electrical Engineering, 167–76. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6499-9_17.
Pełny tekst źródłaJi, Zhicheng, Rongjia Zhu i Yanxia Shen. "Fuzzy Multiple Reference Models Adaptive Control Scheme Study". W Advances in Machine Learning and Cybernetics, 387–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11739685_41.
Pełny tekst źródłaZhang, Weicun, i Qing Li. "Stable Weighted Multiple Model Adaptive Control of Discrete-Time Stochastic Plant". W Virtual Equivalent System Approach for Stability Analysis of Model-based Control Systems, 65–87. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5538-1_4.
Pełny tekst źródłaStreszczenia konferencji na temat "Multiple model adaptive control"
Burakov, M. V. "Fuzzy Multiple Model Adaptive Control". W 2019 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF). IEEE, 2019. http://dx.doi.org/10.1109/weconf.2019.8840624.
Pełny tekst źródłaBaar, Tamas, Bence Beke, Peter Bauer, Balint Vanek i Jozsef Bokor. "Smoothed multiple model adaptive estimation". W 2016 European Control Conference (ECC). IEEE, 2016. http://dx.doi.org/10.1109/ecc.2016.7810442.
Pełny tekst źródłaChang Tan, Gang Tao i Ruiyun Qi. "Direct adaptive multiple-model control schemes". W 2013 American Control Conference (ACC). IEEE, 2013. http://dx.doi.org/10.1109/acc.2013.6580603.
Pełny tekst źródłaLiu, Jiazhen, Zhenlei Wang, Xin Wang, Dahai Wang i Feng Qian. "Multiple models robust adaptive control with reduced model". W 2010 8th IEEE International Conference on Control and Automation (ICCA). IEEE, 2010. http://dx.doi.org/10.1109/icca.2010.5524307.
Pełny tekst źródłaRajagopal, A., i K. Krishnamurthy. "Adaptive Control Using Multiple Models and Model Weighting". W ASME 1996 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/imece1996-0413.
Pełny tekst źródłaKnoebel, Nathan, i Jovan Boskovic. "Model Selection Analysis in Multiple Model Adaptive Control". W AIAA Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2009. http://dx.doi.org/10.2514/6.2009-6063.
Pełny tekst źródłaWang, Ya, Zhuo Kong i Baoyong Zhao. "Multiple-Model Adaptive Control - Disturbance Rejection Study". W 2015 International Conference on Electromechanical Control Technology and Transportation. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/icectt-15.2015.8.
Pełny tekst źródłaMaybeck, P. S., i R. D. Stevens. "Reconfigurable flight control via multiple model adaptive control methods". W 29th IEEE Conference on Decision and Control. IEEE, 1990. http://dx.doi.org/10.1109/cdc.1990.203417.
Pełny tekst źródłaLourenco, J. M., i J. M. Lemos. "On-line model bank enlargement for multiple model adaptive control". W European Control Conference 2007 (ECC). IEEE, 2007. http://dx.doi.org/10.23919/ecc.2007.7068734.
Pełny tekst źródłaFisher, K. A., i P. S. Maybeck. "Multiple model adaptive estimation with filter spawning". W Proceedings of 2000 American Control Conference (ACC 2000). IEEE, 2000. http://dx.doi.org/10.1109/acc.2000.878595.
Pełny tekst źródłaRaporty organizacyjne na temat "Multiple model adaptive control"
Baum, C. C., K. L. Buescher, V. Hanagandi, R. Jones i K. Lee. Adaptive model predictive control using neural networks. Office of Scientific and Technical Information (OSTI), wrzesień 1994. http://dx.doi.org/10.2172/10178912.
Pełny tekst źródłaCandy, J. Model Reference Adaptive Control (MRAC) for Additive Manufacturing. Office of Scientific and Technical Information (OSTI), czerwiec 2021. http://dx.doi.org/10.2172/1798434.
Pełny tekst źródłaDurling, Mike. Direct Model Reference Adaptive Control for a Magnetic Bearing. Office of Scientific and Technical Information (OSTI), listopad 1999. http://dx.doi.org/10.2172/767405.
Pełny tekst źródłaMorris, Nancy M., William B. Rouse i Paul R. Frey. Adaptive Aiding for Symbiotic Human-Computer Control: Conceptual Model and Experimental Approach. Fort Belvoir, VA: Defense Technical Information Center, luty 1985. http://dx.doi.org/10.21236/ada153870.
Pełny tekst źródłaEguchi, Hiroaki, Takanori Fukao i Koichi Osuka. Design Method of Reference Model for Active Steering Based on Nonlinear Adaptive D* Control. Warrendale, PA: SAE International, wrzesień 2005. http://dx.doi.org/10.4271/2005-08-0423.
Pełny tekst źródłaHardt, D. E., E. Papadpoulos i A. Suzuki. Study of reduced order model reference adaptive control systems for improved process control. Final report, May 1, 1982-January 31, 1986. Office of Scientific and Technical Information (OSTI), luty 1986. http://dx.doi.org/10.2172/6114568.
Pełny tekst źródłaHeinz, Kevin, Itamar Glazer, Moshe Coll, Amanda Chau i Andrew Chow. Use of multiple biological control agents for control of western flower thrips. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7613875.bard.
Pełny tekst źródłaHuang, Hui-Min. Outline of a multiple dimensional reference model architecture and a knowledge engineering methodology for intelligent systems control. Gaithersburg, MD: National Institute of Standards and Technology, 1995. http://dx.doi.org/10.6028/nist.ir.5643.
Pełny tekst źródłaWegner, Michael D. Physician Provider Profiling in Brooke Army Medical Center's Internal Medicine Clinic: A Multiple Regression and Process Control Model. Fort Belvoir, VA: Defense Technical Information Center, grudzień 1999. http://dx.doi.org/10.21236/ada420371.
Pełny tekst źródłaPruitt, Bruce, K. Killgore, William Slack i Ramune Matuliauskaite. Formulation of a multi-scale watershed ecological model using a statistical approach. Engineer Research and Development Center (U.S.), listopad 2020. http://dx.doi.org/10.21079/11681/38862.
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