Academic literature on the topic 'Optimal control theory'
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Journal articles on the topic "Optimal control theory"
James, M. R. "Optimal Quantum Control Theory." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (May 3, 2021): 343–67. http://dx.doi.org/10.1146/annurev-control-061520-010444.
Full textWerschnik, J., and E. K. U. Gross. "Quantum optimal control theory." Journal of Physics B: Atomic, Molecular and Optical Physics 40, no. 18 (September 4, 2007): R175—R211. http://dx.doi.org/10.1088/0953-4075/40/18/r01.
Full textDaund, 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 (April 11, 2014): 7–11. http://dx.doi.org/10.9756/sijasree/v2i2/0202520301.
Full textCHERRUAULT, Y., and J. GALLEGO. "INTRODUCTION TO OPTIMAL CONTROL THEORY." Kybernetes 14, no. 3 (March 1985): 151–56. http://dx.doi.org/10.1108/eb005712.
Full textZelikin, M. I., D. D. Kiselev, and L. V. Lokutsievskiy. "Optimal control and Galois theory." Sbornik: Mathematics 204, no. 11 (November 30, 2013): 1624–38. http://dx.doi.org/10.1070/sm2013v204n11abeh004352.
Full textMartínez, Eduardo. "Reduction in optimal control theory." Reports on Mathematical Physics 53, no. 1 (February 2004): 79–90. http://dx.doi.org/10.1016/s0034-4877(04)90005-5.
Full textYong, Jiongmin. "Infinite dimensional optimal control theory." IFAC Proceedings Volumes 32, no. 2 (July 1999): 2778–89. http://dx.doi.org/10.1016/s1474-6670(17)56473-3.
Full textFUKUSHIMA, 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.
Full textPant, 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.
Full textHerrmann, Avriel A., and Joseph Z. Ben-Asher. "Flight Control Law Clearance Using Optimal Control Theory." Journal of Aircraft 53, no. 2 (March 2016): 515–29. http://dx.doi.org/10.2514/1.c033517.
Full textDissertations / Theses on the topic "Optimal control theory"
Bellon, James. "Riccati Equations in Optimal Control Theory." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/math_theses/46.
Full textYiu, Ka Fai Cedric. "Aerodynamic design via optimal control theory." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317867.
Full textZenios, Stefanos A. (Stefanos Andrea). "Health care applications of optimal control theory." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/11042.
Full textSilva, Francisco Jose. "Interior penalty approximation for optimal control problems. Optimality conditions in stochastic optimal control theory." Palaiseau, Ecole polytechnique, 2010. http://pastel.archives-ouvertes.fr/docs/00/54/22/95/PDF/tesisfjsilva.pdf.
Full textRésumé anglais : This thesis is divided in two parts. In the first one we consider deterministic optimal control problems and we study interior approximations for two model problems with non-negativity constraints. The first model is a quadratic optimal control problem governed by a nonautonomous affine ordinary differential equation. We provide a first-order expansion for the penalized state an adjoint state (around the corresponding state and adjoint state of the original problem), for a general class of penalty functions. Our main argument relies on the following fact: if the optimal control satisfies strict complementarity conditions for its Hamiltonian, except for a set of times with null Lebesgue measure, the functional estimates of the penalized optimal control problem can be derived from the estimates of a related finite dimensional problem. Our results provide three types of measure to analyze the penalization technique: error estimates of the control, error estimates of the state and the adjoint state and also error estimates for the value function. The second model we study is the optimal control problem of a semilinear elliptic PDE with a Dirichlet boundary condition, where the control variable is distributed over the domain and is constrained to be non-negative. Following the same approach as in the first model, we consider an associated family of penalized problems, whose solutions define a central path converging to the solution of the original one. In this fashion, we are able to extend the results obtained in the ODE framework to the case of semilinear elliptic PDE constraints. In the second part of the thesis we consider stochastic optimal control problems. We begin withthe study of a stochastic linear quadratic problem with non-negativity control constraints and we extend the error estimates for the approximation by logarithmic penalization. The proof is based is the stochastic Pontryagin's principle and a duality argument. Next, we deal with a general stochastic optimal control problem with convex control constraints. Using the variational approach, we are able to obtain first and second-order expansions for the state and cost function, around a local minimum. This analysis allows us to prove general first order necessary condition and, under a geometrical assumption over the constraint set, second-order necessary conditions are also established
Hunt, K. J. "Stochastic optimal control theory with application in self-tuning control." Thesis, University of Strathclyde, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382399.
Full textShaikh, Mohammad Shahid. "Optimal control of hybrid systems : theory and algorithms." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85095.
Full textIn this thesis we first formulate a class of hybrid optimal control problems (HOCPs) for systems with controlled and autonomous location transitions and then present necessary conditions for hybrid system trajectory optimality. These necessary conditions constitute generalizations of the standard Minimum Principle (MP) and are presented for the cases of open bounded control value sets and compact control value sets. These conditions give information about the behaviour of the Hamiltonian and the adjoint process at both autonomous and controlled switching times.
Such proofs of the necessary conditions for hybrid systems optimality which can be found in the literature are sufficiently complex that they are difficult to verify and use; in contrast, the formulation of the HOCP given in Chapter 2 of this thesis, together with the use of (i) classical variational methods and more recent needle variation techniques, and (ii) a local controllability condition, called the small time tubular fountain (STTF) condition, make the proofs in that chapter comparatively accessible. We note that the STTF condition is used to establish the adjoint and Hamiltonian jump conditions in the autonomous switchings case.
A hybrid Dynamic Programming Principle (HDPP) generalizing the standard dynamic programming principle to hybrid systems is also derived and this leads to hybrid Hamilton-Jacobi-Bellman (HJB) equation which is then used to establish a verification theorem within this framework. (Abstract shortened by UMI.)
Nedeljković, Nikola. "The LORE computational method in optimal control theory." Thesis, Nedeljković, Nikola (1985) The LORE computational method in optimal control theory. PhD thesis, Murdoch University, 1985. https://researchrepository.murdoch.edu.au/id/eprint/51530/.
Full textDal, Bianco Nicola. "Optimal control of road vehicles: theory and applications." Doctoral thesis, Università degli studi di Padova, 2017. http://hdl.handle.net/11577/3424690.
Full textIn this thesis Optimal Control (OC) of road vehicles is studied especially focusing on minimum lap time simulations. The theory underlying the most used optimal control solving techniques is described, including both the Pontryagin Maximum Principle and the reduction to Nonlinear Programming. Direct and indirect methods for optimal control problems are presented and compared against minimum lap time simulations (LTS). Modelling of vehicles for OC-LTSs is studied in order to understand how different design choices can affect simulation outcomes. Novel multibody models of four wheeled vehicles - a GP2 car and a go-kart - for OC-LTSs are developed and validated thorough comparison with experimental data. Particular attention is dedicated to the simulation of tyre load dynamics, that is achieved by a proper modelling of the chassis and suspension motions and of the aerodynamic forces. OC-LTSs are applied to electric vehicles too, specifically to optimise the design of an electric motorbike taking part at the Tourist Trophy Zero competition. A concise yet effective model is proposed in order to perform reliable simulations on a 60km long road in a reasonable amount of time. Experimental data is used to validate the model. A direct full collocation transcription method for OCPs dealing with implicit differential equations and control derivatives is presented, moreover the structure of the resulting NLP problem is accurately described. The relationship between the first order necessary conditions and the Lagrange multipliers of the NLP and OC problems are derived under the adopted discretisation scheme. The presented transcription method is implemented into a software which is currently in use at the University of Padova to solve OC-LTSs.
Seywald, Hans. "Optimal control problems with switching points." Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-07282008-135220/.
Full textGuo, Chaoyang. "Some optimal control problems in mathematical finance." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0022/NQ39269.pdf.
Full textBooks on the topic "Optimal control theory"
Sethi, Suresh P. Optimal Control Theory. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91745-6.
Full textSethi, Suresh P. Optimal Control Theory. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-98237-3.
Full textMa, Zhongjing, and Suli Zou. Optimal Control Theory. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6292-5.
Full textLewis, Frank L. Optimal control. 3rd ed. Hoboken: Wiley, 2012.
Find full text1934-, Tikhomirov V. M., and Fomin S. V, eds. Optimal control. New York: Consultants Bureau, 1987.
Find full textOptimal control. New York: Springer, 2010.
Find full textHull, David G. Optimal Control Theory for Applications. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-1-4757-4180-3.
Full textAgrachev, Andrei A., A. Stephen Morse, Eduardo D. Sontag, Héctor J. Sussmann, and Vadim I. Utkin. Nonlinear and Optimal Control Theory. Edited by Paolo Nistri and Gianna Stefani. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-77653-6.
Full textSpeyer, Jason Lee. Primer on optimal control theory. Philadelphia: Society for Industrial and Applied Mathematics, 2010.
Find full textH, Jacobson David, ed. Primer on optimal control theory. Philadelphia: Society for Industrial and Applied Mathematics, 2010.
Find full textBook chapters on the topic "Optimal control theory"
Ashchepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Extremals Field Theory." In Optimal Control, 185–201. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91029-7_14.
Full textLocatelli, Arturo. "The Hamilton-Jacobi theory." In Optimal Control, 9–19. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8328-3_2.
Full textColonius, Fritz. "Optimization theory." In Optimal Periodic Control, 8–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0077933.
Full textRoy, Priti Kumar. "Optimal Control Theory." In Mathematical Models for Therapeutic Approaches to Control HIV Disease Transmission, 119–53. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-852-6_6.
Full textKythe, Prem K. "Optimal Control Theory." In Elements of Concave Analysis and Applications, 233–50. Boca Raton, Florida : CRC Press, [2018]: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315202259-10.
Full textLonguski, James M., José J. Guzmán, and John E. Prussing. "Optimal Control Theory." In Optimal Control with Aerospace Applications, 19–38. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8945-0_2.
Full textZiemann, Volker. "Optimal Control Theory." In Undergraduate Lecture Notes in Physics, 171–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63643-2_11.
Full textHeij, Christiaan, André C.M. Ran, and Frederik van Schagen. "Optimal Control." In Introduction to Mathematical Systems Theory, 65–80. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-59654-5_5.
Full textBoltyanski, Vladimir G. "Tent Method in Optimal Control Theory." In Optimal Control, 3–20. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_1.
Full textSethi, Suresh P. "Stochastic Optimal Control." In Optimal Control Theory, 365–84. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98237-3_12.
Full textConference papers on the topic "Optimal control theory"
Robert, Grubbström,. "Optimal Lotsizing within Mrp Theory." In Information Control Problems in Manufacturing, edited by Bakhtadze, Natalia, Chair Dolgui, Alexandre and Bakhtadze, Natalia. Elsevier, 2009. http://dx.doi.org/10.3182/20090603-3-ru-2001.00002.
Full text"Optimal Control Theory and its Applications." In 2019 XXI International Conference Complex Systems: Control and Modeling Problems (CSCMP). IEEE, 2019. http://dx.doi.org/10.1109/cscmp45713.2019.8976795.
Full textSpindler, K. "Motion planning via optimal control theory." In Proceedings of 2002 American Control Conference. IEEE, 2002. http://dx.doi.org/10.1109/acc.2002.1023924.
Full textGaur, Deepak, and Mani Shankar Prasad. "Orbit Transfer using Optimal Control Theory." In 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE). IEEE, 2019. http://dx.doi.org/10.1109/rdcape47089.2019.8979056.
Full textZunino, Paolo, and Diego Mastalli. "Optimal control of peritoneal dialysis." In Control Systems: Theory, Numerics and Applications. Trieste, Italy: Sissa Medialab, 2006. http://dx.doi.org/10.22323/1.018.0018.
Full textPiccoli, Benedetto, and Filippo Castiglione. "Optimal control methods for immunotheraphy." In Control Systems: Theory, Numerics and Applications. Trieste, Italy: Sissa Medialab, 2006. http://dx.doi.org/10.22323/1.018.0027.
Full textTaur, Der-Ren, Jeng-Shing Chern, Der-Ren Taur, and Jeng-Shing Chern. "Optimal normalization scheme for computed quaternion using optimal regulator theory." In Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1997. http://dx.doi.org/10.2514/6.1997-3564.
Full textMenon, P. K. A., E. Kim, and V. H. L. Cheng. "Helicopter Trajectory Planning using Optimal Control Theory." In 1988 American Control Conference. IEEE, 1988. http://dx.doi.org/10.23919/acc.1988.4789945.
Full textThompson, David F., and Osita D. I. Nwokah. "Optimal Loop Synthesis in Quantitative Feedback Theory." In 1990 American Control Conference. IEEE, 1990. http://dx.doi.org/10.23919/acc.1990.4790808.
Full textPAN, LIPING, and QIHONG CHEN. "NEAR-OPTIMAL CONTROLS TO INFINITE DIMENSIONAL LINEAR-QUADRATIC OPTIMAL CONTROL PROBLEM." In Control Theory and Related Topics - In Memory of Professor Xunjing Li. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812790552_0022.
Full textReports on the topic "Optimal control theory"
Iyer, R. V., R. Holsapple, and D. Doman. Optimal Control Problems on Parallelizable Riemannian Manifolds: Theory and Applications. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada455175.
Full textYeh, Edmund M. Theory, Design, and Algorithms for Optimal Control of wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada522224.
Full textMoin, Parviz, Jeremy A. Templeton, and Meng Wang. Wall Models for Large-Eddy Simulation Based on Optimal Control Theory. Fort Belvoir, VA: Defense Technical Information Center, June 2006. http://dx.doi.org/10.21236/ada451008.
Full textJin, Dafeng, Peng Li, Yugong Ruo, Rui Chen, and Keqiang Li. The Study for the Regenerative Braking Strategy Based on the Optimal Control Theory. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0407.
Full textGhandehari, Mostafa. An Optimal Control Formulation of the Blaschke-Lebesgue Theorem. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada200939.
Full textAndreasen, Eugenia, Sofía Bauducco, and Evangelina Dardati. Welfare Effects of Capital Controls. Inter-American Development Bank, June 2021. http://dx.doi.org/10.18235/0003307.
Full textKularatne, Dhanushka N., Subhrajit Bhattacharya, and M. Ani Hsieh. Computing Energy Optimal Paths in Time-Varying Flows. Drexel University, 2016. http://dx.doi.org/10.17918/d8b66v.
Full textMwamba, Isaiah C., Mohamadali Morshedi, Suyash Padhye, Amir Davatgari, Soojin Yoon, Samuel Labi, and Makarand Hastak. Synthesis Study of Best Practices for Mapping and Coordinating Detours for Maintenance of Traffic (MOT) and Risk Assessment for Duration of Traffic Control Activities. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317344.
Full textStavenga, Doekele G. Charting the Visual Space of Insect Eyes - Delineating the Guidance, Navigation and Control of Insect Flight by Their Optical Sensor. Fort Belvoir, VA: Defense Technical Information Center, June 2014. http://dx.doi.org/10.21236/ada607192.
Full textMorkun, Volodymyr, Natalia Morkun, Andrii Pikilnyak, Serhii Semerikov, Oleksandra Serdiuk, and Irina Gaponenko. The Cyber-Physical System for Increasing the Efficiency of the Iron Ore Desliming Process. CEUR Workshop Proceedings, April 2021. http://dx.doi.org/10.31812/123456789/4373.
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