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Libros sobre el tema "Nonlinear dynamic system modeling and control"

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Autor: Grafiati
Publicado: 16 de julio de 2024

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1

Goebel, Rafal. Hybrid dynamical systems: Modeling, stability, and robustness. Princeton, N.J: Princeton University Press, 2012.

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2

Magnus, Nørgaard, ed. Neural networks for modelling and control of dynamic systems: A practitioner's handbook. Berlin: Springer, 2000.

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3

Erik, Mosekilde y Mouritsen Ole G, eds. Modelling the dynamics of biological systems: Nonlinear phenomena and pattern formation. Berlin: Springer, 1995.

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4

International Conference "Dynamical Systems - Theory and Applications" (9th 2007 Łódź, Poland). Modeling, simulation and control of nonlinear engineering dynamical systems: State-of-the-art, perspectives and applications. Editado por Awrejcewicz J. [S.l.]: Springer, 2009.

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5

International Conference "Dynamical Systems - Theory and Applications" (9th 2007 Łódź, Poland). Modeling, simulation and control of nonlinear engineering dynamical systems: State-of-the-art, perspectives and applications. Editado por Awrejcewicz J. [S.l.]: Springer, 2009.

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6

Awrejcewicz, Jan, ed. Modeling, Simulation and Control of Nonlinear Engineering Dynamical Systems. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-8778-3.

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7

Rong, Hai-Jun y Zhao-Xu Yang. Sequential Intelligent Dynamic System Modeling and Control. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1541-1.

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8

International, Conference "Dynamical Systems Theory and Applications" (9th 2007 Łódź Poland). Modeling, simulation and control of nonlinear engineering dynamical systems: State-of-the-art, perspectives and applications. [S.l.]: Springer, 2009.

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9

Shearer, J. Lowen. Dynamic modeling and control of engineering systems. 2a ed. Upper Saddle River, N.J: Prentice Hall, 1997.

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10

Shearer, J. Lowen. Dynamic modeling and control of engineering systems. New York: Macmillan, 1990.

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11

Palm, William J. Modeling, analysis, and control of dynamic systems. 2a ed. New York: Wiley, 1998.

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12

Palm, William J. Modeling, analysis, and control of dynamic systems. 2a ed. New York: Wiley, 1999.

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13

Palm, William J. Modeling, analysis, and control of dynamic systems. 2a ed. New York: Wiley, 1998.

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14

Liu, Yu, Fengjiao Liu, Yanfang Mei, Xiangqian Yao y Wei Zhao. Dynamic Modeling and Boundary Control of Flexible Axially Moving System. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6941-6.

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15

H, Daugherty Robert, Martinson Veloria J y Langley Research Center, eds. Modeling and validation of a Navy A6-Intruder actively controlled landing gear system. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1999.

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16

H, Daugherty Robert, Martinson Veloria J y Langley Research Center, eds. Modeling and validation of a Navy A6-Intruder actively controlled landing gear system. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1999.

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17

Melin, Patricia. Modelling, simulation and control of non-linear dynamical systems: An intelligent approach using soft computing and fractal theory. London: Taylor & Francis, 2002.

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18

Zhang, Huaguang. Adaptive Dynamic Programming for Control: Algorithms and Stability. London: Springer London, 2013.

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19

McEwen, Matthew D. Dynamic system identification and modeling of a rotary wing UAV for stability and control analysis. Monterey, Calif: Naval Postgraduate School, 1998.

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20

Laliberte, Matthieu. Dynamic modeling and control of a multi-robot system during assembly of flexible payloads with kinematic uncertainty. Ottawa: National Library of Canada, 1996.

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21

Chang-Hee, Won, Schrader Cheryl B, Michel Anthony N y Sain Michael K, eds. Advances in statistical control, algebraic systems theory, and dynamic systems characteristics: A tribute to Michael K. Sain. Boston, Mass: Birkhäuser, 2008.

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22

Sirbiladze, Gia. Extremal Fuzzy Dynamic Systems: Theory and Applications. New York, NY: Springer New York, 2013.

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23

Zhukova, Galina. Mathematical methods for management decisions. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1084987.

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The purpose of this manual is to help students to master basic concepts and research methods used in the theory of optimal control. The foundations of mathematical modeling. Systematic mathematical methods for managerial decision-making in linear, nonlinear and dynamic problems of optimal socio-economic processes. Each section contains numerous examples of the application of these methods to solve applied problems. Much attention is paid to comparison of the proposed methods, a proper choice of study design problems, case studies and analysis of complex situations that arise in the study of these topics theory of decision-making, methods of optimal control. It is recommended that teachers, students and graduate students studying advanced mathematics.
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24

Kolomyc, Erland. Monitoring the sustainable development of forest ecosystems in a changing climate. ru: INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/2056726.

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The monograph presents a working concept of the theory and methods of terrestrial geosystem monitoring of forests. For the first time, the complete triad of monitoring is considered in its classical definition: "observation (assessment of the state) - control (forecasting) - management (adaptation, feedback, regulation)". The patterns of local and regional response of forests to global climate change are described. The entire array of scientific and methodological developments is systematized in such a way as to reveal the content of geo-ecological monitoring using multidimensional system analysis enriched with empirical and statistical models of basic and predicted states, geo (eco) systems as integral dynamic formations. Forecasts of changes in the biological cycle, including forest productivity, are given. Analytical and cartographic models of functional stability of forest ecosystems are presented. Quantitative forecast estimates of the local and regional regulation of the carbon cycle by forest ecosystems in the context of modern global warming are presented. For students, postgraduates and young scientists studying landscape ecology, environmental modeling and forecasting.
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25

Goebel, Rafal, Andrew R. Teel y Ricardo G. Sanfelice. Hybrid Dynamical Systems: Modeling, Stability, and Robustness. Princeton University Press, 2012.

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26

Goebel, Rafal, Andrew R. Teel y Ricardo G. Sanfelice. Hybrid Dynamical Systems: Modeling, Stability, and Robustness. Princeton University Press, 2012.

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27

Norgaard, M., O. Ravn, N. K. Poulsen y L. K. Hansen. Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook (Advanced Textbooks in Control and Signal Processing). Springer, 2003.

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28

Ivancevic, Vladimir G. y Tijana T. Ivancevic. Geometrical Dynamics of Complex Systems: A Unified Modelling Approach to Physics, Control, Biomechanics, Neurodynamics and Psycho-Socio-Economical Dynamics. Springer, 2006.

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29

Srinivasan, Krishnaswamy y Matthew Detrick. Dynamic System Modeling and Control System Design. Wiley & Sons, Limited, John, 2016.

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30

Srinivasan, Krishnaswamy y Matthew Detrick. Dynamic System Modeling and Control System Design. Wiley & Sons, Incorporated, John, 2018.

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31

Ivancevic, Vladimir G. y Tijana T. Ivancevic. Geometrical Dynamics of Complex Systems: A Unified Modelling Approach to Physics, Control, Biomechanics, Neurodynamics and Psycho-Socio-Economical Dynamics ... and Intelligent Systems Engineering). Springer, 2006.

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32

Mosekilde, Erik. Modelling the Dynamics of Biological Systems: Nonlinear Phenomina and Pattern Formation (Lecture Notes in Artificial Intelligence). Springer, 1995.

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33

Principe, Jose C. y Danilo Comminiello. Adaptive Learning Methods for Nonlinear System Modeling. Butterworth-Heinemann Limited, 2018.

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34

Principe, Jose C. y Danilo Comminiello. Adaptive Learning Methods for Nonlinear System Modeling. Elsevier Science & Technology Books, 2018.

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35

Kluever, Craig A. Dynamic Systems: Modeling, Simulation, and Control. Wiley & Sons, Limited, John, 2019.

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36

Kluever, Craig A. Dynamic Systems: Modeling, Simulation, and Control. Wiley & Sons, Incorporated, John, 2020.

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37

(Editor), Erik Mosekilde y Ole G. Mouritsen (Editor), eds. Modelling the Dynamics of Biological Systems: Nonlinear Phenomena and Pattern Formation (Springer Series in Synergetics, Vol 65). Springer, 1995.

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38

Kluever, Craig A. Dynamic Systems: Modeling, Simulation, and Control. Wiley & Sons, Incorporated, John, 2015.

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39

Kluever, Craig A. Dynamic Systems: Modeling, Simulation, and Control. Wiley & Sons, Incorporated, John, 2015.

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40

Kluever, Craig A. Dynamic Systems: Modeling, Simulation, and Control. Wiley & Sons, Incorporated, John, 2015.

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41

Kluever, Craig A. Dynamic Systems: Modeling, Simulation, and Control. Wiley & Sons, Incorporated, John, 2015.

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42

Awrejcewicz, Jan. Modeling, Simulation and Control of Nonlinear Engineering Dynamical Systems: State-of-the-Art, Perspectives and Applications. Springer Netherlands, 2010.

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43

Awrejcewicz, Jan. Modeling, Simulation and Control of Nonlinear Engineering Dynamical Systems: State-Of-the-Art, Perspectives and Applications. Springer, 2008.

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44

Nonlinear Control of Dynamic Networks Automation and Control Engineering. Taylor & Francis Inc, 2014.

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45

Chen, Qiang y Xuemei Ren. Adaptive Identification and Control of Uncertain Systems with Non-Smooth Dynamics: New Modelling and Control Methods Applied to a Collection of Non-Smooth Systems. Elsevier Science & Technology Books, 2018.

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46

National Aeronautics and Space Administration (NASA) Staff. Orion Active Thermal Control System Dynamic Modeling Using Simulink/MATLAB. Independently Published, 2019.

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47

Liu, Fengjiao, Yanfang Mei, Xiangqian Yao, Yu Liu y Wei Zhao. Dynamic Modeling and Boundary Control of Flexible Axially Moving System. Springer, 2023.

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48

Singla, Puneet y John L. Junkins. Multi-Resolution Methods for Modeling and Control of Dynamical Systems (Applied Mathematics and Nonlinear Science). Chapman & Hall/CRC, 2008.

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49

Jazar, Reza N. y Liming Dai. Nonlinear Approaches in Engineering Applications: Dynamic Systems and Control. Springer, 2014.

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50

Melin, Patricia y Oscar Castillo. Modelling, Simulation and Control of Non-linear Dynamical Systems: An Intelligent Approach Using Soft Computing and Fractal Theory (Numerical Insights, 2). CRC, 2001.

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