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Artykuły w czasopismach na temat "Sampled-data models"
Goodwin, Graham C., Juan I. Yuz i Juan C. Agüero. "Relative Error Issues in Sampled Data Models". IFAC Proceedings Volumes 41, nr 2 (2008): 5047–52. http://dx.doi.org/10.3182/20080706-5-kr-1001.00848.
Pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. "SAMPLED-DATA MODELS FOR STOCHASTIC NONLINEAR SYSTEMS". IFAC Proceedings Volumes 39, nr 1 (2006): 434–39. http://dx.doi.org/10.3182/20060329-3-au-2901.00065.
Pełny tekst źródłaYiin, Lih-Huah, i H. Vincent Poor. "Linear interpolation models for rapidly-sampled data". Communications in Statistics - Theory and Methods 14, nr 4 (1998): 867–82. http://dx.doi.org/10.1080/03610929808828953.
Pełny tekst źródłaYuz, J. I., i G. C. Goodwin. "On sampled-data models for nonlinear systems". IEEE Transactions on Automatic Control 50, nr 10 (październik 2005): 1477–89. http://dx.doi.org/10.1109/tac.2005.856640.
Pełny tekst źródłaYiin, Lih-Huah, i H. Vincent Poor. "Linear interpolation models for rapidly-sampled data". Communications in Statistics. Stochastic Models 14, nr 4 (styczeń 1998): 867–82. http://dx.doi.org/10.1080/15326349808807505.
Pełny tekst źródłaRadchenko, Peter, Xinghao Qiao i Gareth M. James. "Index Models for Sparsely Sampled Functional Data". Journal of the American Statistical Association 110, nr 510 (3.04.2015): 824–36. http://dx.doi.org/10.1080/01621459.2014.931859.
Pełny tekst źródłaYucra, Eduardo A., i Juan I. Yuz. "Frequency domain accuracy of approximate sampled-data models". IFAC Proceedings Volumes 44, nr 1 (styczeń 2011): 8711–17. http://dx.doi.org/10.3182/20110828-6-it-1002.02257.
Pełny tekst źródłaMoheimani, S. O. Reza. "Model Correction for Sampled-Data Models of Structures". Journal of Guidance, Control, and Dynamics 24, nr 3 (maj 2001): 634–37. http://dx.doi.org/10.2514/2.4760.
Pełny tekst źródłaRabbath, C. A., N. Hori i N. Lechevin. "Convergence of Sampled-Data Models in Digital Redesign". IEEE Transactions on Automatic Control 49, nr 5 (maj 2004): 850–55. http://dx.doi.org/10.1109/tac.2004.828312.
Pełny tekst źródłaWang, Jiandong, Tongwen Chen i Biao Huang. "Multirate sampled-data systems: computing fast-rate models". Journal of Process Control 14, nr 1 (luty 2004): 79–88. http://dx.doi.org/10.1016/s0959-1524(03)00033-7.
Pełny tekst źródłaRozprawy doktorskie na temat "Sampled-data models"
Findeisen, Rolf. "Nonlinear model predictive control a sampled data feedback perspective /". [S.l. : s.n.], 2004.
Znajdź pełny tekst źródłaChen, Fengwei. "Contributions à l'identification de modèles à temps continu à partir de données échantillonnées à pas variable". Thesis, Université de Lorraine, 2014. http://www.theses.fr/2014LORR0149/document.
Pełny tekst źródłaThe output of a system is always corrupted by additive noise, therefore it is more practical to develop estimation algorithms that are capable of handling noisy data. The effect of white additive noise has been widely studied, while a colored additive noise attracts less attention, especially for a continuous-time (CT) noise. Sampling issues of CT stochastic processes are reviewed in this thesis, several sampling schemes are presented. Estimation of a CT stochastic process is studied. An expectation-maximization-based (EM) method to CT autoregressive/autoregressive moving average model is developed, which gives accurate estimation over a large range of sampling interval. Estimation of CT Box-Jenkins models is also considered in this thesis, in which the noise part is modeled to improve the performance of plant model estimation. The proposed method for CT Box-Jenkins model identification is in a two-step and iterative framework. Two-step means the plant and noise models are estimated in a separate and alternate way, where in estimating each of them, the other is assumed to be fixed. More specifically, the plant is estimated by refined instrumental variable (RIV) method while the noise is estimated by EM algorithm. Iterative means that the proposed method repeats the estimation procedure several times until a optimal estimate is found. Many practical systems have inherent time-delay. The problem of identifying delayed systems are of great importance for analysis, prediction or control design. The presence of a unknown time-delay greatly complicates the parameter estimation problem, essentially because the model are not linear with respect to the time-delay. An approach to continuous-time model identification of time-delay systems, combining a numerical search algorithm for the delay with the RIV method for the dynamic has been developed in this thesis. In the proposed algorithm, the system parameters and time-delay are estimated reciprocally in a bootstrap manner. The time-delay is estimated by an adaptive gradient-based method, whereas the system parameters are estimated by the RIV method. Since numerical method is used in this algorithm, the bootstrap method is likely to converge to local optima, therefore a low-pass filter has been used to enlarge the convergence region for the time-delay. The performance of the proposed algorithms are evaluated by numerical examples
Yuz, Eissmann Juan Ignacio. "Sampled-data models for linear and nonlinear systems". Thesis, 2006. http://hdl.handle.net/1959.13/24852.
Pełny tekst źródłaPhD Doctorate
Yuz, Eissmann Juan Ignacio. "Sampled-data models for linear and nonlinear systems". 2006. http://hdl.handle.net/1959.13/24852.
Pełny tekst źródłaPhD Doctorate
Ramroop, Shaun. "An approach to estimating the variance components to unbalanced cluster sampled survey data and simulated data". Diss., 2002. http://hdl.handle.net/10500/762.
Pełny tekst źródła"Modelling irregularly sampled time series : an application on Hong Kong water pollution data". Chinese University of Hong Kong, 1986. http://library.cuhk.edu.hk/record=b5885655.
Pełny tekst źródłaCHEN, CHENG-LIANG, i 陳誠亮. "Identification of continuous-time models for linar multivariable dynamic systems via sampled data". Thesis, 1987. http://ndltd.ncl.edu.tw/handle/91097850936882099575.
Pełny tekst źródła"Linear averaged and sampled data models for large signal control of high power factor Ac-DC converters". Massachusetts Institute of Technology, Laboratory for Information and Decision Systems], 1990. http://hdl.handle.net/1721.1/3198.
Pełny tekst źródłaCover title.
Includes bibliographical references (leaf 9).
Work partially supported by DEC. Work partially supported by the Air Force Office of Scientific Research. AFOSR-88-0032 Work partially supported by the MIT/Industry Power Electronics Collegium.
Carrasco, Yanez Diego S. "Uncertainty issues in deterministic and stochastic nonlinear systems". Thesis, 2014. http://hdl.handle.net/1959.13/1049172.
Pełny tekst źródłaRobustness issues arise in every real world control problem. The objective of any robust control strategy is to preserve closed-loop stability in situations where the real plant differs from the model used to design the controller, i.e. the real system is, in some sense, unknown. There are different ways to quantify, or describe, the uncertainty of a model. It is the amount of uncertainty, or lack of confidence in the model, that ultimately determines, and constrains, what the closed-loop can achieve. In this thesis we address particular issues concerned with how to quantify and reduce the impact of uncertainty. To this end, the present thesis is divided in two parts: The first part is aimed at linear systems. We propose two ideas on how to improve closed-loop performance in the face of general uncertainty, namely, (i) augmenting the control architecture with a feedforward component and (ii) augmenting the observer architecture by using the more general class of unbiased observers. We then illustrate the first strategy applied to an Artificial Pancreas problem. The second part is aimed at nonlinear systems. A common source of uncertainty in this area is the use of approximate sampled-data models of continuous time systems, be it for control design or system identifcation. This is due to the fact that, contrary to the linear case, exact discretisations are not generally possible in the nonlinear case. In particular, we deal with the sampled-data scenario in both deterministic and stochastic cases and focus our attention on accuracy and related properties of sampled-data models. We first study the accuracy properties, or error dynamics, of a particular deterministic sampled data model, and show that it possesses an improved order of accuracy when compared to the usual Euler approximation. We then demonstrate the usefulness of having such a quantification via several applications, namely, (i) obtaining better bias-variance tradeoffs in the parameter estimation of continuous-time systems from sampled-data, (ii) obtaining a sampled-data model that depends only on input-output data that retains the improved order of accuracy, and (iii) obtaining better performance in high-gain sampled-data feedback control of nonlinear systems, via feedback lineraisation. In addition, we extend the analysis to stochastic sampled-data nonlinear systems. In this case, we show that the error dynamics are tightly intertwined with other system properties that arise due to the sampling process. In particular, we show the existence of stochastic sampling zero dynamics that are closely related to the sampling zero dynamics associated with the deterministic case.
Findeisen, Rolf [Verfasser]. "Nonlinear model predictive control: a sampled-data feedback perspective / vorgelegt von Rolf Findeisen". 2005. http://d-nb.info/979741750/34.
Pełny tekst źródłaKsiążki na temat "Sampled-data models"
Hugues, Garnier, i Wang Liuping, red. Identification of continuous-time models from sampled data. London: Springer, 2008.
Znajdź pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. Sampled-Data Models for Linear and Nonlinear Systems. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1.
Pełny tekst źródłaGarnier, Hugues, i Liuping Wang, red. Identification of Continuous-time Models from Sampled Data. London: Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-161-9.
Pełny tekst źródłaGhysels, Eric. Predicitng volatility: Getting the most out of return data sampled at different frequencies. Cambridge, MA: National Bureau of Economic Research, 2004.
Znajdź pełny tekst źródłaGhysels, Eric. Predicting volatility: Getting the most out of return data sampled at different frequencies. Cambridge, Mass: National Bureau of Economic Research, 2004.
Znajdź pełny tekst źródłaTsang, K. M. Reconstruction of linear and nonlinear continuous time models from discrete time sampled-data systems. Sheffield: University of Sheffield, Dept. of Control Engineering, 1990.
Znajdź pełny tekst źródłaByun, Jae-Woong. Estimation of discrete dynamic models from endogenously-sampled company panel data: An analysis of direct investmentby Korean firms in the European Union. Leicester: University of Leicester, Department of Economics, 1994.
Znajdź pełny tekst źródłaYuz, Juan, i Graham C. Goodwin. Sampled-Data Models for Linear and Nonlinear Systems. Springer London, Limited, 2016.
Znajdź pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. Sampled-Data Models for Linear and Nonlinear Systems. Springer London, Limited, 2013.
Znajdź pełny tekst źródłaWang, Liuping, i Hugues Garnier. Identification of Continuous-Time Models from Sampled Data. Springer London, Limited, 2010.
Znajdź pełny tekst źródłaCzęści książek na temat "Sampled-data models"
Yuz, Juan I., i Graham C. Goodwin. "Incremental Sampled-Data Models". W Communications and Control Engineering, 39–45. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1_4.
Pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. "Incremental Stochastic Sampled-Data Models". W Communications and Control Engineering, 157–67. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1_13.
Pełny tekst źródłaMurray-Smith, D. J. "Sampled-Data Models and Operator Methods". W Continuous System Simulation, 67–84. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-2504-2_5.
Pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. "Sampled-Data Models for Linear Stochastic Systems". W Communications and Control Engineering, 149–56. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1_12.
Pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. "Applications of Approximate Stochastic Sampled-Data Models". W Communications and Control Engineering, 233–50. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1_19.
Pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. "Sampled-Data Models for Linear Deterministic Systems". W Communications and Control Engineering, 21–38. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1_3.
Pełny tekst źródłaSouthard, David A. "Piecewise Planar Surface Models from Sampled Data". W Scientific Visualization of Physical Phenomena, 667–80. Tokyo: Springer Japan, 1991. http://dx.doi.org/10.1007/978-4-431-68159-5_37.
Pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. "Approximate Sampled-Data Models for Linear Stochastic Systems". W Communications and Control Engineering, 195–207. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1_16.
Pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. "Approximate Sampled-Data Models for Nonlinear Stochastic Systems". W Communications and Control Engineering, 221–31. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1_18.
Pełny tekst źródłaYuz, Juan I., i Graham C. Goodwin. "Approximate Sampled-Data Models for Fractional Order Systems". W Communications and Control Engineering, 271–86. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5562-1_22.
Pełny tekst źródłaStreszczenia konferencji na temat "Sampled-data models"
Goodwin, G. C., J. I. Yuz, J. C. Aguero i M. Cea. "Sampling and sampled-data models". W 2010 American Control Conference (ACC 2010). IEEE, 2010. http://dx.doi.org/10.1109/acc.2010.5531562.
Pełny tekst źródłaSilva, Cesar A., i Juan I. Yuz. "On sampled-data models for model predictive control". W IECON 2010 - 36th Annual Conference of IEEE Industrial Electronics. IEEE, 2010. http://dx.doi.org/10.1109/iecon.2010.5674939.
Pełny tekst źródłaLi Chai i Xiaodong Zhao. "Sampled Data Model Predictive Control for Step Response Models". W 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1714305.
Pełny tekst źródłaNishi, Masatoshi, Mitsuaki Ishitobi i Sadaaki Kunimatsu. "Nonlinear sampled-data models and zero dynamics". W 2009 International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2009. http://dx.doi.org/10.1109/icnsc.2009.4919304.
Pełny tekst źródłaRomano, Rodrigo A., Felipe Pait i P. Lopes dos Santos. "Obtaining multivariable continuous-time models from sampled data". W 2017 American Control Conference (ACC). IEEE, 2017. http://dx.doi.org/10.23919/acc.2017.7962944.
Pełny tekst źródłaKarafyllis, Iasson, Michael Malisoff i Miroslav Krstic. "Sampled-data feedback stabilization of age-structured chemostat models". W 2015 American Control Conference (ACC). IEEE, 2015. http://dx.doi.org/10.1109/acc.2015.7172045.
Pełny tekst źródłaIshitobi, Mitsuaki, i Masatoshi Nishi. "Zero dynamics of sampled-data models for nonlinear systems". W 2008 American Control Conference (ACC '08). IEEE, 2008. http://dx.doi.org/10.1109/acc.2008.4586653.
Pełny tekst źródłaIshitobi, Mitsuaki, i Sadaaki Kunimatsu. "Zeros of sampled-data models for time delay MIMO systems". W TENCON 2016 - 2016 IEEE Region 10 Conference. IEEE, 2016. http://dx.doi.org/10.1109/tencon.2016.7848687.
Pełny tekst źródłaAvila, F., J. I. Yuz, A. Donaire i J. C. Aguero. "Constrained maximum likelihood estimation for state space sampled-data models". W 2018 22nd International Conference on System Theory, Control and Computing (ICSTCC). IEEE, 2018. http://dx.doi.org/10.1109/icstcc.2018.8540710.
Pełny tekst źródłaNagy, Szabolcs. "Exact reconstruction of HOSVD based TP models from sampled data". W 2009 5th International Symposium on Applied Computational Intelligence and Informatics (SACI). IEEE, 2009. http://dx.doi.org/10.1109/saci.2009.5136214.
Pełny tekst źródłaRaporty organizacyjne na temat "Sampled-data models"
Hart, Carl R., D. Keith Wilson, Chris L. Pettit i Edward T. Nykaza. Machine-Learning of Long-Range Sound Propagation Through Simulated Atmospheric Turbulence. U.S. Army Engineer Research and Development Center, lipiec 2021. http://dx.doi.org/10.21079/11681/41182.
Pełny tekst źródłaDutra, Lauren M., Matthew C. Farrelly, Brian Bradfield, Jamie Ridenhour i Jamie Guillory. Modeling the Probability of Fraud in Social Media in a National Cannabis Survey. RTI Press, wrzesień 2021. http://dx.doi.org/10.3768/rtipress.2021.mr.0046.2109.
Pełny tekst źródłaSwanson, David, i Celia Hampton-Miller. Drained lakes in Bering Land Bridge National Preserve: Vegetation succession and impacts on loon habitat. National Park Service, styczeń 2023. http://dx.doi.org/10.36967/2296593.
Pełny tekst źródłaWeissinger, Rebecca. Trends in water quality at Bryce Canyon National Park, water years 2006–2021. Redaktor Alice Wondrak Biel. National Park Service, listopad 2022. http://dx.doi.org/10.36967/2294946.
Pełny tekst źródłaGalili, Naftali, Roger P. Rohrbach, Itzhak Shmulevich, Yoram Fuchs i Giora Zauberman. Non-Destructive Quality Sensing of High-Value Agricultural Commodities Through Response Analysis. United States Department of Agriculture, październik 1994. http://dx.doi.org/10.32747/1994.7570549.bard.
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