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Journal articles on the topic 'Optimal control theory'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

James, M. R. "Optimal Quantum Control Theory." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (2021): 343–67. http://dx.doi.org/10.1146/annurev-control-061520-010444.

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This article explains some fundamental ideas concerning the optimal control of quantum systems through the study of a relatively simple two-level system coupled to optical fields. The model for this system includes both continuous and impulsive dynamics. Topics covered include open- and closed-loop control, impulsive control, open-loop optimal control, quantum filtering, and measurement feedback optimal control.

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2

Werschnik, J., and E. K. U. Gross. "Quantum optimal control theory." Journal of Physics B: Atomic, Molecular and Optical Physics 40, no. 18 (2007): R175—R211. http://dx.doi.org/10.1088/0953-4075/40/18/r01.

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3

Daund, Arvind, Shrihari Mahishi, and Nirnay Berde. "Synchronization of Parallel Dual Inverted Pendulums using Optimal Control Theory." SIJ Transactions on Advances in Space Research & Earth Exploration 2, no. 2 (2014): 7–11. http://dx.doi.org/10.9756/sijasree/v2i2/0202520301.

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4

CHERRUAULT, Y., and J. GALLEGO. "INTRODUCTION TO OPTIMAL CONTROL THEORY." Kybernetes 14, no. 3 (1985): 151–56. http://dx.doi.org/10.1108/eb005712.

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5

Zelikin, M. I., D. D. Kiselev, and L. V. Lokutsievskiy. "Optimal control and Galois theory." Sbornik: Mathematics 204, no. 11 (2013): 1624–38. http://dx.doi.org/10.1070/sm2013v204n11abeh004352.

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6

Martínez, Eduardo. "Reduction in optimal control theory." Reports on Mathematical Physics 53, no. 1 (2004): 79–90. http://dx.doi.org/10.1016/s0034-4877(04)90005-5.

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7

Yong, Jiongmin. "Infinite dimensional optimal control theory." IFAC Proceedings Volumes 32, no. 2 (1999): 2778–89. http://dx.doi.org/10.1016/s1474-6670(17)56473-3.

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8

FUKUSHIMA, Naoto, Syo OTA, Mehmet Selcuk ARSLAN, and Ichiro HAGIWARA. "B10 Energy Optimal Control Theory : An Optimal Control Theory Based on a New Framework of Control Problem." Proceedings of the Symposium on the Motion and Vibration Control 2009.11 (2009): 109–13. http://dx.doi.org/10.1299/jsmemovic.2009.11.109.

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9

Pant, D. K., R. D. Coalson, M. I. Hernandez, and J. Campos-Martinez. "Optimal control theory for the design of optical waveguides." Journal of Lightwave Technology 16, no. 2 (1998): 292–300. http://dx.doi.org/10.1109/50.661023.

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10

Herrmann, Avriel A., and Joseph Z. Ben-Asher. "Flight Control Law Clearance Using Optimal Control Theory." Journal of Aircraft 53, no. 2 (2016): 515–29. http://dx.doi.org/10.2514/1.c033517.

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11

Slavík, Michal. "Contemporary macroeconomics and optimal control theory." Politická ekonomie 52, no. 4 (2004): 551–61. http://dx.doi.org/10.18267/j.polek.475.

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12

Shah, A. "Optimal control theory and fishery model." Journal of Development and Agricultural Economics 5, no. 12 (2013): 476–81. http://dx.doi.org/10.5897/jdae2013.0487.

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13

Renee Fister, K., and Jennifer Hughes Donnelly. "Immunotherapy: An Optimal Control Theory Approach." Mathematical Biosciences and Engineering 2, no. 3 (2005): 499–510. http://dx.doi.org/10.3934/mbe.2005.2.499.

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14

KONDORSKIY, ALEXEY, and HIROKI NAKAMURA. "SEMICLASSICAL FORMULATION OF OPTIMAL CONTROL THEORY." Journal of Theoretical and Computational Chemistry 04, no. 01 (2005): 75–87. http://dx.doi.org/10.1142/s0219633605001416.

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In the present paper, semiclassical formulation of optimal control theory is made by combining the conjugate gradient search method with new approximate semiclassical expressions for correlation function. Two expressions for correlation function are derived. The simpler one requires calculations of coordinates and momenta of classical trajectories only. The second one requires extra calculation of common semiclassical quantities; as a result additional quantum effects can be taken into account. The efficiency of the method is demonstrated by controlling nuclear wave packet motion in a two-dime

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15

Becker, Robert A., Atle Sierstad, Knut Sydsæter, and Knut Sydsaeter. "Optimal Control Theory with Economic Applications." Scandinavian Journal of Economics 91, no. 1 (1989): 175. http://dx.doi.org/10.2307/3440172.

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16

Žampa, Pavel, Jiří Mošna, and Pavel Prautsch. "New Approach to Optimal Control Theory." IFAC Proceedings Volumes 30, no. 21 (1997): 133–38. http://dx.doi.org/10.1016/s1474-6670(17)41428-5.

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17

Buttazzo, G., and E. Cavazzuti. "Limit Problems in Optimal Control Theory." Annales de l'Institut Henri Poincare (C) Non Linear Analysis 6 (November 1989): 151–60. http://dx.doi.org/10.1016/s0294-1449(17)30019-7.

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18

De la Salle, S. "Stochastic optimal control theory and application." Automatica 24, no. 3 (1988): 425–26. http://dx.doi.org/10.1016/0005-1098(88)90086-6.

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19

Zeidan, V., and P. Zezza. "Coupled points in optimal control theory." IEEE Transactions on Automatic Control 36, no. 11 (1991): 1276–81. http://dx.doi.org/10.1109/9.100937.

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20

Fernández, Antonio, and Pedro L. García. "Regular discretizations in optimal control theory." Journal of Geometric Mechanics 5, no. 4 (2013): 415–32. http://dx.doi.org/10.3934/jgm.2013.5.415.

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21

Yiu, K. F. C., K. L. Mak, and K. L. Teo. "Airfoil design via optimal control theory." Journal of Industrial & Management Optimization 1, no. 1 (2005): 133–48. http://dx.doi.org/10.3934/jimo.2005.1.133.

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22

Zhifeng, Kuang, Yang Mingzhu, and Zhu Guangtian. "Optimal control applications in transport theory." Transport Theory and Statistical Physics 27, no. 5-7 (1998): 691–700. http://dx.doi.org/10.1080/00411459808205651.

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23

Handa, V. K., and R. M. Barcia. "Linear Scheduling Using Optimal Control Theory." Journal of Construction Engineering and Management 112, no. 3 (1986): 387–93. http://dx.doi.org/10.1061/(asce)0733-9364(1986)112:3(387).

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24

Arantes, Santina de F., and Jaime E. Muñoz Rivera. "Optimal control theory for ambient pollution." International Journal of Control 83, no. 11 (2010): 2261–75. http://dx.doi.org/10.1080/00207179.2010.513716.

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25

Pukhlikov, A. V. "Hamiltonian structures in optimal control theory." Journal of Dynamical and Control Systems 1, no. 3 (1995): 379–401. http://dx.doi.org/10.1007/bf02269376.

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26

Hartl, Richard F. "Optimal control theory with economic applications." European Journal of Operational Research 35, no. 2 (1988): 292–93. http://dx.doi.org/10.1016/0377-2217(88)90044-6.

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27

Mathis, Mackenzie W., and Steffen Schneider. "Motor control: Neural correlates of optimal feedback control theory." Current Biology 31, no. 7 (2021): R356—R358. http://dx.doi.org/10.1016/j.cub.2021.01.087.

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28

Ahmed, ABOULFTOUH, EL-BAYOUMI Gamal, and MADBOULI Mohamed. "Hover flight control of helicopter using optimal control theory." INCAS BULLETIN 7, no. 3 (2015): 113–24. http://dx.doi.org/10.13111/2066-8201.2015.7.3.2.

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29

Yang, J. N., Z. Li, and S. Vongchavalitkul. "Generalization of Optimal Control Theory: Linear and Nonlinear Control." Journal of Engineering Mechanics 120, no. 2 (1994): 266–83. http://dx.doi.org/10.1061/(asce)0733-9399(1994)120:2(266).

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30

Peskir, Goran. "Maximum process problems in optimal control theory." Journal of Applied Mathematics and Stochastic Analysis 2005, no. 1 (2005): 77–88. http://dx.doi.org/10.1155/jamsa.2005.77.

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Given a standard Brownian motion (Bt)t≥0 and the equation of motion dXt=vtdt+2dBt, we set St=max0≤s≤tXs and consider the optimal control problem supvE(Sτ−Cτ), where c>0 and the supremum is taken over all admissible controls v satisfying vt∈[μ0,μ1] for all t up to τ=inf{t>0|Xt∉(ℓ0,ℓ1)} with μ0<0<μ1 and ℓ0<0<ℓ1 given and fixed. The following control v∗ is proved to be optimal: “pull as hard as possible,” that is, vt∗=μ0 if Xt<g∗(St), and “push as hard as possible,” that is, vt∗=μ1 if Xt>g∗(St), where s↦g∗(s) is a switching curve that is determined explicitly (as the uniqu

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31

Gurman, V. I. "On Certain Problems in Optimal Control Theory." Bulletin of Irkutsk State University 19 (2017): 26–43. http://dx.doi.org/10.26516/1997-7670.2017.19.26.

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32

Pei, Xiaoxuan, Kewen Li, and Yongming Li. "A survey of adaptive optimal control theory." Mathematical Biosciences and Engineering 19, no. 12 (2022): 12058–72. http://dx.doi.org/10.3934/mbe.2022561.

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<abstract><p>This paper makes a survey about the recent development of optimal control based on adaptive dynamic programming (ADP). First of all, based on DP algorithm and reinforcement learning (RL) algorithm, the origin and development of the optimization idea and its application in the control field are introduced. The second part introduces achievements in the optimal control direction, then we classify and summarize the research results of optimization method, constraint problem, structure design in control algorithm and practical engineering process based on optimal control.

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33

Emms, Paul, and Steven Haberman. "Pricing General Insurance Using Optimal Control Theory." ASTIN Bulletin 35, no. 02 (2005): 427–53. http://dx.doi.org/10.2143/ast.35.2.2003461.

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Insurance premiums are calculated using optimal control theory by maximising the terminal wealth of an insurer under a demand law. If the insurer sets a low premium to generate exposure then profits are reduced, whereas a high premium leads to reduced demand. A continuous stochastic model is developed, which generalises the deterministic discrete model of Taylor (1986). An attractive simplification of this model is that existing policyholders should pay the premium rate currently set by the insurer. It is shown that this assumption leads to a bang-bang optimal premium strategy, which cannot be

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34

Lewis, Debra. "Modeling student engagement using optimal control theory." Journal of Geometric Mechanics 14, no. 1 (2022): 131. http://dx.doi.org/10.3934/jgm.2021032.

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<p style='text-indent:20px;'>Student engagement in learning a prescribed body of knowledge can be modeled using optimal control theory, with a scalar state variable representing mastery, or self-perceived mastery, of the material and control representing the instantaneous cognitive effort devoted to the learning task. The relevant costs include emotional and external penalties for incomplete mastery, reduced availability of cognitive resources for other activities, and psychological stresses related to engagement with the learning task. Application of Pontryagin's maximum principle to so

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35

Prussing, John E. "Review of Optimal Control Theory for Applications." Journal of Guidance, Control, and Dynamics 28, no. 1 (2005): 191. http://dx.doi.org/10.2514/1.15003.

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36

Ashokkumar, C. R., and Singiresu S. Rao. "Structural Control Using Inverse H Optimal Theory." AIAA Journal 41, no. 12 (2003): 2478–85. http://dx.doi.org/10.2514/2.6848.

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37

Sharp, R. S., and Huei Peng. "Vehicle dynamics applications of optimal control theory." Vehicle System Dynamics 49, no. 7 (2011): 1073–111. http://dx.doi.org/10.1080/00423114.2011.586707.

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38

Rosa, Marta, Gabriel Gil, Stefano Corni, and Roberto Cammi. "Quantum optimal control theory for solvated systems." Journal of Chemical Physics 151, no. 19 (2019): 194109. http://dx.doi.org/10.1063/1.5125184.

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39

Abougarair, Ahmed J., Mohsen Bakouri, Abdulrahman Alduraywish, et al. "Optimizing cancer treatment using optimal control theory." AIMS Mathematics 9, no. 11 (2024): 31740–69. http://dx.doi.org/10.3934/math.20241526.

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<p>Cancer is a complex group of diseases characterized by uncontrolled cell growth that can spread throughout the body, leading to serious health issues. Traditional treatments mainly include chemotherapy, surgery, and radiotherapy. Although combining different therapies is becoming more common, predicting how these treatments will interact and what side effects they may cause, such as gastrointestinal or neurological problems, can be challenging. This research applies optimal control theory (OCT) to create precise and personalized treatment plans for cancer patients. OCT helps identify

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40

Borkar, Vivek S. "Contributions to the Theory of Optimal Control." Resonance 29, no. 9 (2024): 1309–27. http://dx.doi.org/10.1007/s12045-024-1309-5.

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41

Chawla, Sanjay, and Suzanne M. Lenhart. "Application of optimal control theory to bioremediation." Journal of Computational and Applied Mathematics 114, no. 1 (2000): 81–102. http://dx.doi.org/10.1016/s0377-0427(99)00290-3.

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42

Xu, Ruixue, Jixin Cheng, and Yan. "A Simple Theory of Optimal Coherent Control." Journal of Physical Chemistry A 103, no. 49 (1999): 10611–18. http://dx.doi.org/10.1021/jp991965b.

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43

Shastri, Yogendra, Urmila Diwekar, and Heriberto Cabezas. "Optimal Control Theory for Sustainable Environmental Management." Environmental Science & Technology 42, no. 14 (2008): 5322–28. http://dx.doi.org/10.1021/es8000807.

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44

Emms, Paul, and Steven Haberman. "Pricing General Insurance Using Optimal Control Theory." ASTIN Bulletin 35, no. 2 (2005): 427–53. http://dx.doi.org/10.1017/s051503610001432x.

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Abstract:

Insurance premiums are calculated using optimal control theory by maximising the terminal wealth of an insurer under a demand law. If the insurer sets a low premium to generate exposure then profits are reduced, whereas a high premium leads to reduced demand. A continuous stochastic model is developed, which generalises the deterministic discrete model of Taylor (1986). An attractive simplification of this model is that existing policyholders should pay the premium rate currently set by the insurer. It is shown that this assumption leads to a bang-bang optimal premium strategy, which cannot be

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45

Curtain, Ruth F. "Optimal control theory for infinite dimensional systems." Automatica 33, no. 4 (1997): 750–51. http://dx.doi.org/10.1016/s0005-1098(97)85780-9.

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46

Bisiacco, Mauro. "New results in 2D optimal control theory." Multidimensional Systems and Signal Processing 6, no. 3 (1995): 189–222. http://dx.doi.org/10.1007/bf00981083.

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47

Karamzin, Dmitry Yu, Valeriano A. de Oliveira, Fernando L. Pereira, and Geraldo N. Silva. "On some extension of optimal control theory." European Journal of Control 20, no. 6 (2014): 284–91. http://dx.doi.org/10.1016/j.ejcon.2014.09.003.

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48

Jones, R. W. "Application of optimal control theory in biomedicine." Automatica 23, no. 1 (1987): 130–31. http://dx.doi.org/10.1016/0005-1098(87)90126-9.

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49

Loring, Stephen H. "Applications of optimal control theory in biomedicine." Mathematical Modelling 7, no. 9-12 (1986): 1659–60. http://dx.doi.org/10.1016/0270-0255(86)90105-3.

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50

Frederico, Gastão S. F., and Delfim F. M. Torres. "Fractional conservation laws in optimal control theory." Nonlinear Dynamics 53, no. 3 (2007): 215–22. http://dx.doi.org/10.1007/s11071-007-9309-z.

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