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1

E, Kim, and Ames Research Center, eds. Optimal helicopter trajectory planning for terrain following flight. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1990.

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2

Bless, Robert R. Variational trajectory optimization tool set: Technical description and user's manual. Hampton, Va: Langley Research Center, 1993.

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3

E, Kim, and Ames Research Center, eds. Optimal helicopter trajectory planning for terrain following flight: Final report. Atlanta, Ga: School of Aerospace Engineering, Georgia Institute of Technology, 1990.

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4

J, Calise Anthony, Moerder Daniel D, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Piloted simulation of an algorithm for onboard control of time-optimal intercept. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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5

S, Naidu D. Fuel-optimal trajectories of aeroassisted orbital transfer with plane change. Norfolk, Va: Old Dominion University Research Foundation, Dept. of Electrical and Computer Engineering, College of Engineering and Technology, Old Dominion University, 1989.

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6

S, Naidu D. Fuel-optimal trajectories of aeroassisted orbital transfer with plane change. Norfolk, Va: Old Dominion University Research Foundation, Dept. of Electrical and Computer Engineering, College of Engineering and Technology, Old Dominion University, 1989.

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7

Bless, Robert R. Time-domain finite elements in optimal control with application to launch-vehicle guidance. Hampton, Va: Langley Research Center, 1991.

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8

United States. National Aeronautics and Space Administration., ed. Hybrid motion planning with multiple destinations: Annual technical report : reporting period 06/10/97 through 06/10/98. [Washington, DC: National Aeronautics and Space Administration, 1998.

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9

Markopoulos, Nikos. Analytical investigations in aircraft and spacecraft trajectory optimization and optimal guidance / by Nikos Markopoulos and Anthony J. Calise. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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10

Georgia Institute of Technology. School of Aerospace Engineering. and Dryden Flight Research Facility, eds. A comparison of time-optimal interception trajectories for the F-8 and F-15: Final report. Atlanta, GA: Georgia Institute of Technology, School of Aerospace Engineering, 1990.

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11

Georgia Institute of Technology. School of Aerospace Engineering. and Dryden Flight Research Facility, eds. A comparison of time-optimal interception trajectories for the F-8 and F-15: Final report. Atlanta, GA: Georgia Institute of Technology, School of Aerospace Engineering, 1990.

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12

Ludovic, Faubourg, and Trélat Emmanuel, eds. Mécanique céleste et contrôle des véhicules spatiaux. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006.

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13

United States. National Aeronautics and Space Administration., ed. Guidance of nonlinear nonminimum-phase dynamic systems: Performance report, period: 3/1/97 - 11/14/97, grant number: NAG 2-1042. [Washington, DC: National Aeronautics and Space Administration, 1997.

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14

United States. National Aeronautics and Space Administration., ed. Guidance of nonlinear nonminimum-phase dynamic systems: Performance report; period: 3/1/96 - 2/28/97; grant number: NAG 2-1042. [Washington, DC: National Aeronautics and Space Administration, 1996.

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15

United States. National Aeronautics and Space Administration., ed. Guidance of nonlinear nonminimum-phase dynamic systems: Performance report; period: 3/1/96 - 2/28/97; grant number: NAG 2-1042. [Washington, DC: National Aeronautics and Space Administration, 1996.

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16

United States. National Aeronautics and Space Administration., ed. Guidance of nonlinear nonminimum-phase dynamic systems: Performance report, period: 3/1/97 - 11/14/97, grant number: NAG 2-1042. [Washington, DC: National Aeronautics and Space Administration, 1997.

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17

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

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18

Guillo, Olivier. Méthode de régulation d'une variable écologique par contrôle optimal stochastique, en temps réel, d'activités social-économiques dans le cadre des jeux dynamiques: Application à la qualité de l'eau de la lagune de Thau et à son bassin versant. Grenoble: A.N.R.T, Université Pierre Mendes France (Grenoble II), 2001.

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19

Prussing, John E. Optimal Trajectories. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198811084.003.0005.

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Optimal trajectories are analysed, covering both constant- and variable-specific-impulse cases. Primer vector is defined and illustrated. The first-order necessary conditions for an optimal constant-specific-impulse (CSI) trajectory were first derived by Lawden using classical Calculus of Variations. Variable-specific-impulse rocket engines are discussed with the cost functional for a VSI engine. In the derivation that follows, an Optimal Control Theory formulation is used, but the derivation is similar to that of Lawden. One difference is that the mass is not defined as a state variable, but is kept track of indirectly.
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20

Lober, Jakob. Optimal Trajectory Tracking of Nonlinear Dynamical Systems. Springer, 2016.

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21

Optimal guidance law develpment for an advanced launch system. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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22

Lewis, Frank L., and Vassilis L. Syrmos. Optimal Control. Wiley & Sons, Incorporated, John, 2008.

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23

Lewis, Frank L., Draguna Vrabie, and Vassilis L. Syrmos. Optimal Control. Wiley & Sons, Incorporated, John, 2012.

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24

Lewis, Frank L., Draguna Vrabie, and Vassilis L. Syrmos. Optimal Control. Wiley & Sons, Incorporated, John, 2012.

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25

Lewis, Frank L. Optimal Control. John Wiley & Sons Inc, 2005.

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26

Trajectory optimization and guidance law development for national aerospace plane applications: Final report, July 1, 1987 to November 30, 1988. Atlanta, Ga: School of Aerospace Engineering, Georgia Institute of Technology, 1988.

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27

Optimal Control For Chemical Engineers. CRC Press, 2012.

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28

Upreti, Simant Ranjan. Optimal Control for Chemical Engineers. Taylor & Francis Group, 2017.

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29

Upreti, Simant Ranjan. Optimal Control for Chemical Engineers. Taylor & Francis Group, 2016.

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30

Upreti, Simant Ranjan. Optimal Control for Chemical Engineers. Taylor & Francis Group, 2016.

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31

Upreti, Simant Ranjan. Optimal Control for Chemical Engineers. Taylor & Francis Group, 2016.

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32

Upreti, Simant Ranjan. Optimal Control for Chemical Engineers. Taylor & Francis Group, 2012.

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33

Upreti, Simant Ranjan. Optimal Control for Chemical Engineers. Taylor & Francis Group, 2016.

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34

A comparison of time-optimal interception trajectories for the F-8 and F-15: Final report. Atlanta, GA: Georgia Institute of Technology, School of Aerospace Engineering, 1990.

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35

Optimal Control Theory: An Introduction. Dover Publications, 2004.

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36

Kirk, Donald E. Optimal Control Theory: An Introduction. Dover Publications, 2004.

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37

Optimisation et Contrôle Stochastique Appliqués à la Finance. Springer London, Limited, 2007.

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38

Guidance of nonlinear nonminimum-phase dynamic systems: Performance report, period: 3/1/97 - 11/14/97, grant number: NAG 2-1042. [Washington, DC: National Aeronautics and Space Administration, 1997.

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39

Ribakov, Yuri, Ido Halperin, and Grigory Agranovich. Design of Optimal Feedback for Structural Control. Taylor & Francis Group, 2021.

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40

Design of Optimal Feedback for Structural Control. Taylor & Francis Group, 2023.

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41

Design of Optimal Feedback for Structural Control. Taylor & Francis Group, 2021.

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42

Design of Optimal Feedback for Structural Control. Taylor & Francis Group, 2021.

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43

Boudreau, Joseph F., and Eric S. Swanson. Data modeling. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0016.

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A variety of techniques for extracting information from data are presented, from pedestrian approaches such as the centuries old linear least-squares fit, to elegant binned and unbinned likelihood fits. A treatment of statistical combination of data leads to an introduction to the powerful Kalman filter approach, used to determine optimal estimates of deterministic-stochastic systems. In experimental physics the Kalman filter is used estimate trajectories from data, but it also finds applications in industrial process control, and in the aeronautics and robots industries. These techniques typically rely on either analytic or numerical optimization of an objective function. Orthogonal series density estimation, a Fourier technique, is also discussed.
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44

Contribution à la théorie des solutions de viscosité des équations de Hamilton-Jacobi du premier ordre et applications à des problèmes de contrôle optimal et de perturbations singulières. Grenoble: A.N.R.T, Université Pierre Mendes France (Grenoble II), 1988.

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