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Books on the topic 'Optimal control methods'

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Published: 15 March 2025

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1

Anderson, Brian D. O. Optimal control: Linear quadratic methods. Englewood Cliffs, N.J: Prentice Hall, 1990.

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2

Anderson, Brian D. O. Optimal control: Linear quadratic methods. Englewood Cliffs, NJ: Prentice-Hall, 1989.

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3

Bensoussan, Alain. Perturbation methods in optimal control. Paris: Gauthier-Villars, 1988.

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4

Roland, Bulirsch, ed. Optimal control: Calculus of variations, optimal control theory, and numerical methods. Basel: Birkhäuser Verlagf, 1993.

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5

Wang, Xinwei, Jie Liu, and Haijun Peng. Symplectic Pseudospectral Methods for Optimal Control. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-3438-6.

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6

Falcone, Maurizio, Roberto Ferretti, Lars Grüne, and William M. McEneaney, eds. Numerical Methods for Optimal Control Problems. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01959-4.

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7

Akulenko, Leonid D. Problems and Methods of Optimal Control. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1194-2.

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8

Akulenko, Leonid D. Problems and Methods of Optimal Control. Dordrecht: Springer Netherlands, 1994.

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9

Akulenko, L. D. Problems and methods of optimal control. Dordrecht: Kluwer Academic Publishers, 1994.

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10

1942-, Lee Sung J., and American Mathematical Society Meeting, eds. Operator methods for optimal control problems. New York: M. Dekker, 1987.

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11

Borggaard, Jeff, John Burns, Eugene Cliff, and Scott Schreck, eds. Computational Methods for Optimal Design and Control. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-1780-0.

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12

Urszula, Ledzewicz, and SpringerLink (Online service), eds. Geometric Optimal Control: Theory, Methods and Examples. New York, NY: Springer New York, 2012.

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13

1963-, Hunt K. J., ed. Polynomial methods in optimal control and filtering. London: P. Peregrinus on behalf of the Institution of Electrical Engineers, 1993.

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14

Khazen, Ė. M. Methods of optimal statistical decisions, optimal control, and stochastic differential equations. [LaVergne, TN]: Xlibris Corporation, 2009.

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15

Burl, Jeffrey B. Linear optimal control: H₂ and H[infinity] methods. Menlo Park, Calif: Addison Wesley Longman, 1999.

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16

Chen, Chi-Tsong. Control system design: Conventional, algebraic, and optimal methods. Stony Brook, NY: Pond Woods Press, 1987.

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17

Shlomo, Ta'asan, and Institute for Computer Applications in Science and Engineering., eds. Multigrid one shot methods for optimal control problems, infinite dimensional control. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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18

Belomestny, Denis, and John Schoenmakers. Advanced Simulation-Based Methods for Optimal Stopping and Control. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-137-03351-2.

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19

Pytlak, Radosław. Numerical Methods for Optimal Control Problems with State Constraints. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0097244.

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20

Mordukhovich, Boris S., and Hector J. Sussmann, eds. Nonsmooth Analysis and Geometric Methods in Deterministic Optimal Control. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4613-8489-2.

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21

Leikkonen, Ilkka. Methods for optimal spatial control of pressurized water reactors. Hki: Teknillisten tieteiden akatemia, 1985.

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22

Sh, Mordukhovich B., and Sussmann Hector J. 1946-, eds. Nonsmooth analysis and geometric methods in deterministic optimal control. New York: Springer, 1996.

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23

Kuijper, M. An introduction to robot joint control methods. Amsterdam: National Aerospace Laboratory, 1986.

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24

Institute for Computer Applications in Science and Engineering. and Langley Research Center, eds. "One Shot" methods for optimal control of distributed parameter systems I: Finite dimensional control. Hampton, Va: Institute for Computer Applications in Science and Engineering, 1991.

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25

Uciński, Dariusz. Optimal measurement methods for distributed parameter system identification. Boca Raton, Fla: CRC Press, 2005.

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26

Lagnese, John E., and Günter Leugering. Domain Decomposition Methods in Optimal Control of Partial Differential Equations. Basel: Birkhäuser Basel, 2004. http://dx.doi.org/10.1007/978-3-0348-7885-2.

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27

Betts, John T. Practical methods for optimal control and estimation using nonlinear programming. 2nd ed. Philadelphia: Society for Industrial and Applied Mathematics, 2010.

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28

Betts, John T. Practical methods for optimal control and estimation using nonlinear programming. 2nd ed. Philadelphia: Society for Industrial and Applied Mathematics, 2009.

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29

Tröltzsch, Fredi. Optimal control of partial differential equations: Theory, methods, and applications. Providence, R.I: American Mathematical Society, 2010.

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30

Betts, John T. Practical methods for optimal control and estimation using nonlinear programming. 2nd ed. Philadelphia: Society for Industrial and Applied Mathematics, 2009.

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31

Lagnese, John E. Domain Decomposition Methods in Optimal Control of Partial Differential Equations. Basel: Birkhäuser Basel, 2004.

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32

W, Ioup Juliette, and United States. National Aeronautics and Space Administration., eds. Optimal application of Morrison's iterative noise removal for deconvolution. New Orleans, LA: Dept. of Physics, University of New Orleans, 1987.

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33

Burns, John A. Factorization and reduction methods for optimal control of distributed parameter systems. Hampton, Va: ICASE, 1985.

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34

Gibson, J. S. Computational methods for optimal linear-quadratic compensators for infinite dimensional discrete-time systems. Hampton, Va: ICASE, 1986.

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35

Borggaard, Jeff. Computational Methods for Optimal Design and Control: Proceedings of the AFOSR Workshop on Optimal Design and Control Arlington, Virginia 30 September-3 October, 1997. Boston, MA: Birkhäuser Boston, 1998.

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36

1964-, Borggaard Jeffrey, ed. Computational methods for optimal design and control: Proceedings of the AFOSR Workshop on Optimal Design and Control, Arlington, Va., 30 September-3 October, 1997. Boston, Mass: Birkhauser Boston, 1998.

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37

Buyal'skiy, Vladimir. Wind turbines with optimal control of electricity generation. ru: INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1946200.

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In the monograph, based on the analysis of modern methods of automatic control of wind power installations, a solution is proposed for the correct connection (in theoretical terms) of related problems of dynamic behavior of power units with optimal control of electricity generation. In this direction, principles, structures and algorithms have been obtained to reduce the dynamic loads of the components of modern wind turbines based on timely preparation of the system for external disturbing influences and taking into account the vibration load of the drive under different operating modes of the power unit. It is intended for researchers and specialists in the field of wind energy, automation of technological processes, system analysis, as well as graduate students and students of relevant training areas and specialties of technical universities.

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38

1945-, Park Sung H., and Vining G. Geoffrey 1954-, eds. Statistical process monitoring and optimization. New York: Marcel Dekker, 2000.

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39

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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40

dell’Isola, Francesco. Variational Models and Methods in Solid and Fluid Mechanics. Vienna: Springer Vienna, 2012.

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41

Kogut, Peter I. Optimal control problems for partial differential equations on reticulated domains: Approximation and asymptotic analysis. New York: Birkhäuser, 2011.

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42

Anderson, Brian D. O., and John B. Moore. Optimal Control: Linear Quadratic Methods. Dover Publications, Incorporated, 2014.

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43

Bensoussan. Perturbation Methods in Optimal Control. Dunod, 1993.

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44

Anderson, Brian D. O., and John B. Moore. Optimal Control: Linear Quadratic Methods. Dover Publications, 2013.

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45

Perturbation methods in optimal control. Chichester: Wiley, 1988.

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46

Bulirsch, Miele, Stoer, and Well. Optimal Control: Calculus of Variations, Optimal Control Theory and Numerical Methods. Springer Basel AG, 2013.

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47

Bulirsch, Miele, Stoer, and Well. Optimal Control: Calculus of Variations, Optimal Control Theory and Numerical Methods. Birkhauser Verlag, 2013.

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48

Ferretti, Roberto, William M. McEneaney, Lars Grüne, and Maurizio Falcone. Numerical Methods for Optimal Control Problems. Springer, 2019.

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49

Global Methods in Optimal Control Theory. CRC Press LLC, 1996.

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50

Akulenko, L. D. Problems and Methods of Optimal Control. Springer, 2014.

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