Littérature scientifique sur le sujet « Deterministic optimal control »
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Articles de revues sur le sujet "Deterministic optimal control"
Chaplais, F. « Averaging and Deterministic Optimal Control ». SIAM Journal on Control and Optimization 25, no 3 (mai 1987) : 767–80. http://dx.doi.org/10.1137/0325044.
Texte intégralBehncke, Horst. « Optimal control of deterministic epidemics ». Optimal Control Applications and Methods 21, no 6 (novembre 2000) : 269–85. http://dx.doi.org/10.1002/oca.678.
Texte intégralPareigis, Stephan. « Learning optimal control in deterministic systems ». ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik 78, S3 (1998) : 1033–34. http://dx.doi.org/10.1002/zamm.19980781585.
Texte intégralWang, Yuanchang, et Jiongmin Yong. « A deterministic affine-quadratic optimal control problem ». ESAIM : Control, Optimisation and Calculus of Variations 20, no 3 (21 mai 2014) : 633–61. http://dx.doi.org/10.1051/cocv/2013078.
Texte intégralVerms, D. « Optimal control of piecewise deterministic markov process ». Stochastics 14, no 3 (février 1985) : 165–207. http://dx.doi.org/10.1080/17442508508833338.
Texte intégralSoravia, Pierpaolo. « On Aronsson Equation and Deterministic Optimal Control ». Applied Mathematics and Optimization 59, no 2 (28 mai 2008) : 175–201. http://dx.doi.org/10.1007/s00245-008-9048-7.
Texte intégralHaurie, A., A. Leizarowitz et Ch van Delft. « Boundedly optimal control of piecewise deterministic systems ». European Journal of Operational Research 73, no 2 (mars 1994) : 237–51. http://dx.doi.org/10.1016/0377-2217(94)90262-3.
Texte intégralSeierstad, Atle. « Existence of optimal nonanticipating controls in piecewise deterministic control problems ». ESAIM : Control, Optimisation and Calculus of Variations 19, no 1 (18 janvier 2012) : 43–62. http://dx.doi.org/10.1051/cocv/2011197.
Texte intégralMitsos, Alexander, Jaromił Najman et Ioannis G. Kevrekidis. « Optimal deterministic algorithm generation ». Journal of Global Optimization 71, no 4 (13 février 2018) : 891–913. http://dx.doi.org/10.1007/s10898-018-0611-8.
Texte intégralYu, Juanyi, Jr-Shin Li et Tzyh-Jong Tarn. « Optimal Control of Gene Mutation in DNA Replication ». Journal of Biomedicine and Biotechnology 2012 (2012) : 1–26. http://dx.doi.org/10.1155/2012/743172.
Texte intégralThèses sur le sujet "Deterministic optimal control"
Ribeiro, do Val Joao Bosco. « Stochastic optimal control for piecewise deterministic Markov processes ». Thesis, Imperial College London, 1986. http://hdl.handle.net/10044/1/38142.
Texte intégralJohnson, Miles J. « Inverse optimal control for deterministic continuous-time nonlinear systems ». Thesis, University of Illinois at Urbana-Champaign, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3632073.
Texte intégralInverse optimal control is the problem of computing a cost function with respect to which observed state input trajectories are optimal. We present a new method of inverse optimal control based on minimizing the extent to which observed trajectories violate first-order necessary conditions for optimality. We consider continuous-time deterministic optimal control systems with a cost function that is a linear combination of known basis functions. We compare our approach with three prior methods of inverse optimal control. We demonstrate the performance of these methods by performing simulation experiments using a collection of nominal system models. We compare the robustness of these methods by analyzing how they perform under perturbations to the system. We consider two scenarios: one in which we exactly know the set of basis functions in the cost function, and another in which the true cost function contains an unknown perturbation. Results from simulation experiments show that our new method is computationally efficient relative to prior methods, performs similarly to prior approaches under large perturbations to the system, and better learns the true cost function under small perturbations. We then apply our method to three problems of interest in robotics. First, we apply inverse optimal control to learn the physical properties of an elastic rod. Second, we apply inverse optimal control to learn models of human walking paths. These models of human locomotion enable automation of mobile robots moving in a shared space with humans, and enable motion prediction of walking humans given partial trajectory observations. Finally, we apply inverse optimal control to develop a new method of learning from demonstration for quadrotor dynamic maneuvering. We compare and contrast our method with an existing state-of-the-art solution based on minimum-time optimal control, and show that our method can generalize to novel tasks and reject environmental disturbances.
Laera, Simone. « VWAP OPTIMAL EXECUTION Deterministic and stochastic approaches ». Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018.
Trouver le texte intégralCosta, Oswaldo Luiz de Valle. « Approximations for optimal stopping and impulsive control of piecewise-deterministic processes ». Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/38271.
Texte intégralLange, Dirk Klaus [Verfasser], et N. [Akademischer Betreuer] Bäuerle. « Cost optimal control of Piecewise Deterministic Markov Processes under partial observation / Dirk Klaus Lange ; Betreuer : N. Bäuerle ». Karlsruhe : KIT-Bibliothek, 2017. http://d-nb.info/1132997739/34.
Texte intégralSainvil, Watson. « Contrôle optimal et application aux énergies renouvelables ». Electronic Thesis or Diss., Antilles, 2023. http://www.theses.fr/2023ANTI0894.
Texte intégralToday, electricity is the easiest form of energy to exploit in the world. However, producing it from fossil sources such as oil, coal, natural gas,…, is the main cause of global warming by emitting a massive amount of greenhouse gases into nature. We need an alternative and fast! The almost daily sunshine and the important quantity of wind should favor the development of renewable energies.In this thesis, the main objective is to apply the optimal control theory to renewable energies in order to convince decision makers to switch to them through mathematical studies. First, we develop a deterministic case based on what has already been done in the transition from fossil fuels to renewable energies in which we formulate two case studies. The first one deals with an optimal control probleminvolving the transition from oil to solar energy. The second deals with an optimal control problem involving the transition from oil to solar and wind energies.Then, we develop a stochastic part in which we treat a stochastic control problem whose objective is to take into account the random aspect of the production of solar energy since we cannot guarantee sufficient daily sunshine
Schlosser, Rainer. « Six essays on stochastic and deterministic dynamic pricing and advertising models ». Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2014. http://dx.doi.org/10.18452/16973.
Texte intégralThe cumulative dissertation deals with stochastic and deterministic dynamic sales models for durable as well as perishable products. The models analyzed are characterized by simultaneous dynamic pricing and advertising controls in continuous time and are in line with recent developments in dynamic pricing. They include the modeling of multi-dimensional decisions and take (i) time dependencies, (ii) adoption effects (iii), competitive settings and (iv) risk aversion, explicitly into account. For special cases with isoelastic demand functions as well as with exponential ones explicit solution formulas of the optimal pricing and advertising feedback controls are derived. Moreover, optimally controlled sales processes are analytically described. In particular, the distribution of profits, the expected evolution of prices as well as inventory levels are analyzed in detail and sensitivity results are obtained. Furthermore, we consider the question whether or not monopolistic policies are socially efficient; in special cases, we propose taxation/subsidy mechanisms to establish efficiency. The results are presented in six articles and provide economic insights into a variety of dynamic sales applications of the business world, especially in the area of e-commerce.
Tan, Yang. « Optimal Discrete-in-Time Inventory Control of a Single Deteriorating Product with Partial Backlogging ». Scholar Commons, 2010. http://scholarcommons.usf.edu/etd/3711.
Texte intégralJoubaud, Maud. « Processus de Markov déterministes par morceaux branchants et problème d’arrêt optimal, application à la division cellulaire ». Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS031/document.
Texte intégralPiecewise deterministic Markov processes (PDMP) form a large class of stochastic processes characterized by a deterministic evolution between random jumps. They fall into the class of hybrid processes with a discrete mode and an Euclidean component (called the state variable). Between the jumps, the continuous component evolves deterministically, then a jump occurs and a Markov kernel selects the new value of the discrete and continuous components. In this thesis, we extend the construction of PDMPs to state variables taking values in some measure spaces with infinite dimension. The aim is to model cells populations keeping track of the information about each cell. We study our measured-valued PDMP and we show their Markov property. With thoses processes, we study a optimal stopping problem. The goal of an optimal stopping problem is to find the best admissible stopping time in order to optimize some function of our process. We show that the value fonction can be recursively constructed using dynamic programming equations. We construct some $epsilon$-optimal stopping times for our optimal stopping problem. Then, we study a simple finite-dimension real-valued PDMP, the TCP process. We use Euler scheme to approximate it, and we estimate some types of errors. We illustrate the results with numerical simulations
Geeraert, Alizée. « Contrôle optimal stochastique des processus de Markov déterministes par morceaux et application à l’optimisation de maintenance ». Thesis, Bordeaux, 2017. http://www.theses.fr/2017BORD0602/document.
Texte intégralWe are interested in a discounted impulse control problem with infinite horizon forpiecewise deterministic Markov processes (PDMPs). In the first part, we model the evolutionof an optronic system by PDMPs. To optimize the maintenance of this equipment, we study animpulse control problem where both maintenance costs and the unavailability cost for the clientare considered. We next apply a numerical method for the approximation of the value function associated with the impulse control problem, which relies on quantization of PDMPs. The influence of the parameters on the numerical results is discussed. In the second part, we extendthe theoretical study of the impulse control problem by explicitly building a family of є-optimalstrategies. This approach is based on the iteration of a single-jump-or-intervention operator associatedto the PDMP and relies on the theory for optimal stopping of a piecewise-deterministic Markov process by U.S. Gugerli. In the present situation, the main difficulty consists in approximating the best position after the interventions, which is done by introducing a new operator.The originality of the proposed approach is the construction of є-optimal strategies that areexplicit, since they do not require preliminary resolutions of complex problems
Livres sur le sujet "Deterministic optimal control"
Jadamba, Baasansuren, Akhtar A. Khan, Stanisław Migórski et Miguel Sama. Deterministic and Stochastic Optimal Control and Inverse Problems. Boca Raton : CRC Press, 2021. http://dx.doi.org/10.1201/9781003050575.
Texte intégralCarlson, D. A. Infinite horizon optimal control : Deterministic and stochastic systems. 2e éd. Berlin : Springer-Verlag, 1991.
Trouver le texte intégralCarlson, Dean A. Infinite Horizon Optimal Control : Deterministic and Stochastic Systems. Berlin, Heidelberg : Springer Berlin Heidelberg, 1991.
Trouver le texte intégralMordukhovich, Boris S., et Hector J. Sussmann, dir. 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.
Texte intégralOptimal design of control systems : Stochastic and deterministic problems. New York : M. Dekker, 1999.
Trouver le texte intégralSh, Mordukhovich B., et Sussmann Hector J. 1946-, dir. Nonsmooth analysis and geometric methods in deterministic optimal control. New York : Springer, 1996.
Trouver le texte intégralFleming, Wendell H. Deterministic and Stochastic Optimal Control. Springer, 2012.
Trouver le texte intégralFleming, Wendell H., et Raymond W. Rishel. Deterministic and Stochastic Optimal Control. Springer London, Limited, 2012.
Trouver le texte intégralMoyer, H. Gardner. Deterministic Optimal Control : An Introduction for Scientists. Trafford Publishing, 2006.
Trouver le texte intégralKhan, Akhtar A., Baasansuren Jadamba, Stanislaw Migorski et Miguel Angel Sama Meige. Deterministic and Stochastic Optimal Control and Inverse Problems. Taylor & Francis Group, 2021.
Trouver le texte intégralChapitres de livres sur le sujet "Deterministic optimal control"
Bensoussan, Alain. « Deterministic Optimal Control ». Dans Interdisciplinary Applied Mathematics, 215–47. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75456-7_10.
Texte intégralSeierstad, Atle. « Piecewise Deterministic Optimal Control Problems ». Dans Stochastic Control in Discrete and Continuous Time, 1–70. Boston, MA : Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-76617-1_3.
Texte intégralde Saporta, Benoîte, François Dufour et Huilong Zhang. « Optimal Impulse Control ». Dans Numerical Methods for Simulation and Optimization of Piecewise Deterministic Markov Processes, 231–67. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119145066.ch10.
Texte intégralDontchev, A. L. « Discrete Approximations in Optimal Control ». Dans Nonsmooth Analysis and Geometric Methods in Deterministic Optimal Control, 59–80. New York, NY : Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4613-8489-2_3.
Texte intégralZoppoli, Riccardo, Marcello Sanguineti, Giorgio Gnecco et Thomas Parisini. « Deterministic Optimal Control over a Finite Horizon ». Dans Neural Approximations for Optimal Control and Decision, 255–98. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29693-3_6.
Texte intégralCosta, O. L. V., et F. Dufour. « Optimal Control of Piecewise Deterministic Markov Processes ». Dans Stochastic Analysis, Filtering, and Stochastic Optimization, 53–77. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98519-6_3.
Texte intégralBressan, Alberto. « Impulsive Control Systems ». Dans Nonsmooth Analysis and Geometric Methods in Deterministic Optimal Control, 1–22. New York, NY : Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4613-8489-2_1.
Texte intégralFilatova, Darya. « Optimal Control Strategies for Stochastic/Deterministic Bioeconomic Models ». Dans Mathematics in Industry, 537–43. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25100-9_62.
Texte intégralChen, Lijun, Na Li, Libin Jiang et Steven H. Low. « Optimal Demand Response : Problem Formulation and Deterministic Case ». Dans Control and Optimization Methods for Electric Smart Grids, 63–85. New York, NY : Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-1605-0_3.
Texte intégralZolezzi, Tullio. « Well Posed Optimal Control Problems : A Perturbation Approach ». Dans Nonsmooth Analysis and Geometric Methods in Deterministic Optimal Control, 239–46. New York, NY : Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4613-8489-2_11.
Texte intégralActes de conférences sur le sujet "Deterministic optimal control"
Zamani, Mohammad, Jochen Trumpf et Robert Mahony. « Near-optimal deterministic attitude filtering ». Dans 2010 49th IEEE Conference on Decision and Control (CDC). IEEE, 2010. http://dx.doi.org/10.1109/cdc.2010.5717043.
Texte intégralLi, Yuchao, Karl H. Johansson, Jonas Martensson et Dimitri P. Bertsekas. « Data-driven Rollout for Deterministic Optimal Control ». Dans 2021 60th IEEE Conference on Decision and Control (CDC). IEEE, 2021. http://dx.doi.org/10.1109/cdc45484.2021.9683499.
Texte intégralBarles, G., et B. Perthame. « Discontinuous viscosity solutions of deterministic optimal control problems ». Dans 1986 25th IEEE Conference on Decision and Control. IEEE, 1986. http://dx.doi.org/10.1109/cdc.1986.267221.
Texte intégralCoote, Paul, Jochen Trumpf, Robert Mahony et Jan C. Willems. « Near-optimal deterministic filtering on the unit circle ». Dans 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC). IEEE, 2009. http://dx.doi.org/10.1109/cdc.2009.5399999.
Texte intégralLiao, Y., et S. Lenhart. « Optimal control of piecewise-deterministic processes with discrete control actions ». Dans 1985 24th IEEE Conference on Decision and Control. IEEE, 1985. http://dx.doi.org/10.1109/cdc.1985.268634.
Texte intégralBasin, Michael V., et Irma R. Valadez Guzman. « Optimal controller for integral Volterra systems with deterministic uncertainties ». Dans 2001 European Control Conference (ECC). IEEE, 2001. http://dx.doi.org/10.23919/ecc.2001.7075973.
Texte intégralBasin, Michael, et Dario Calderon-Alvarez. « Optimal controller for uncertain stochastic polynomial systems with deterministic disturbances ». Dans 2009 American Control Conference. IEEE, 2009. http://dx.doi.org/10.1109/acc.2009.5160068.
Texte intégralTsumura, Koji. « Optimal Quantizer for Mixed Probabilistic/Deterministic Parameter Estimation ». Dans Proceedings of the 45th IEEE Conference on Decision and Control. IEEE, 2006. http://dx.doi.org/10.1109/cdc.2006.376940.
Texte intégral« COST-OPTIMAL STRONG PLANNING IN NON-DETERMINISTIC DOMAINS ». Dans 8th International Conference on Informatics in Control, Automation and Robotics. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003448200560066.
Texte intégralSun, Jin-gen, Li-jun Fu, Zhi-gang Huang et Dong-sheng Wu. « The Method of Deterministic Optimal Control with Box Constraints ». Dans 2010 3rd International Conference on Intelligent Networks and Intelligent Systems (ICINIS). IEEE, 2010. http://dx.doi.org/10.1109/icinis.2010.37.
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