An introduction to optimal control theory: the dynamic programming approach
This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering, Operations Research, and Management Science,...
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham, Switzerland
Springer
[2023]
|
| Schriftenreihe: | Texts in applied mathematics
volume 76 |
| Schlagworte: | |
| Zusammenfassung: | This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering, Operations Research, and Management Science, among many others.The main objective is to give a concise, systematic, and reasonably self contained presentation of some key topics in optimal control theory. To this end, most of the analyses are based on the dynamic programming (DP) technique. This technique is applicable to almost all control problems that appear in theory and applications. They include, for instance, finite and infinite horizon control problems in which the underlying dynamic system follows either a deterministic or stochastic difference or differential equation. In the infinite horizon case, it also uses DP to study undiscounted problems, such as the ergodic or long-run average cost. After a general introduction to control problems, the book covers the topic dividing into four parts with different dynamical systems: control of discrete-time deterministic systems, discrete-time stochastic systems, ordinary differential equations, and finally a general continuous-time MCP with applications for stochastic differential equations.The first and second part should be accessible to undergraduate students with some knowledge of elementary calculus, linear algebra, and some concepts from probability theory (random variables, expectations, and so forth). Whereas the third and fourth part would be appropriate for advanced undergraduates or graduate students who have a working knowledge of mathematical analysis (derivatives, integrals,.) and stochastic processes |
| Beschreibung: | Introduction: optimal control problems-. Discrete-time deterministic systems.- Discrete-time stochastic control systems.- Continuous-time deterministic systems.- Continuous-time Markov control processes.- Controlled diffusion processes.- Appendices.- Bibliography.- Index |
| Beschreibung: | xv, 273 Seiten 659 grams |
| ISBN: | 9783031211386 |
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| 520 | |a This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering, Operations Research, and Management Science, among many others.The main objective is to give a concise, systematic, and reasonably self contained presentation of some key topics in optimal control theory. To this end, most of the analyses are based on the dynamic programming (DP) technique. This technique is applicable to almost all control problems that appear in theory and applications. They include, for instance, finite and infinite horizon control problems in which the underlying dynamic system follows either a deterministic or stochastic difference or differential equation. In the infinite horizon case, it also uses DP to study undiscounted problems, such as the ergodic or long-run average cost. After a general introduction to control problems, the book covers the topic dividing into four parts with different dynamical systems: control of discrete-time deterministic systems, discrete-time stochastic systems, ordinary differential equations, and finally a general continuous-time MCP with applications for stochastic differential equations.The first and second part should be accessible to undergraduate students with some knowledge of elementary calculus, linear algebra, and some concepts from probability theory (random variables, expectations, and so forth). Whereas the third and fourth part would be appropriate for advanced undergraduates or graduate students who have a working knowledge of mathematical analysis (derivatives, integrals,.) and stochastic processes | ||
| 650 | 4 | |a Stochastic models | |
| 650 | 4 | |a Stochastic processes | |
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| 700 | 1 | |a Mendoza-Palacios, Saúl |e Verfasser |0 (DE-588)1271986051 |4 aut | |
| 700 | 1 | |a González-Sánchez, David |e Verfasser |0 (DE-588)1043447148 |4 aut | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-034168921 | ||
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| id | DE-604.BV048904618 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T21:51:49Z |
| indexdate | 2024-07-10T09:49:24Z |
| institution | BVB |
| isbn | 9783031211386 |
| language | English |
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| physical | xv, 273 Seiten 659 grams |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Springer |
| record_format | marc |
| series | Texts in applied mathematics |
| series2 | Texts in applied mathematics |
| spelling | Hernández-Lerma, Onésimo 1946- Verfasser (DE-588)111571081 aut An introduction to optimal control theory the dynamic programming approach Onésimo Hernández-Lerma, Leonardo R. Laura-Guarachi, Saul Mendoza-Palacios, David González-Sánchez Cham, Switzerland Springer [2023] xv, 273 Seiten 659 grams txt rdacontent n rdamedia nc rdacarrier Texts in applied mathematics volume 76 Introduction: optimal control problems-. Discrete-time deterministic systems.- Discrete-time stochastic control systems.- Continuous-time deterministic systems.- Continuous-time Markov control processes.- Controlled diffusion processes.- Appendices.- Bibliography.- Index This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering, Operations Research, and Management Science, among many others.The main objective is to give a concise, systematic, and reasonably self contained presentation of some key topics in optimal control theory. To this end, most of the analyses are based on the dynamic programming (DP) technique. This technique is applicable to almost all control problems that appear in theory and applications. They include, for instance, finite and infinite horizon control problems in which the underlying dynamic system follows either a deterministic or stochastic difference or differential equation. In the infinite horizon case, it also uses DP to study undiscounted problems, such as the ergodic or long-run average cost. After a general introduction to control problems, the book covers the topic dividing into four parts with different dynamical systems: control of discrete-time deterministic systems, discrete-time stochastic systems, ordinary differential equations, and finally a general continuous-time MCP with applications for stochastic differential equations.The first and second part should be accessible to undergraduate students with some knowledge of elementary calculus, linear algebra, and some concepts from probability theory (random variables, expectations, and so forth). Whereas the third and fourth part would be appropriate for advanced undergraduates or graduate students who have a working knowledge of mathematical analysis (derivatives, integrals,.) and stochastic processes Stochastic models Stochastic processes Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik Laura-Guarachi, Leonardo R. Verfasser aut Mendoza-Palacios, Saúl Verfasser (DE-588)1271986051 aut González-Sánchez, David Verfasser (DE-588)1043447148 aut Erscheint auch als Online-Ausgabe 978-3-031-21139-3 Texts in applied mathematics volume 76 (DE-604)BV002476038 76 |
| spellingShingle | Hernández-Lerma, Onésimo 1946- Laura-Guarachi, Leonardo R. Mendoza-Palacios, Saúl González-Sánchez, David An introduction to optimal control theory the dynamic programming approach Texts in applied mathematics Stochastic models Stochastic processes |
| title | An introduction to optimal control theory the dynamic programming approach |
| title_auth | An introduction to optimal control theory the dynamic programming approach |
| title_exact_search | An introduction to optimal control theory the dynamic programming approach |
| title_exact_search_txtP | An introduction to optimal control theory the dynamic programming approach |
| title_full | An introduction to optimal control theory the dynamic programming approach Onésimo Hernández-Lerma, Leonardo R. Laura-Guarachi, Saul Mendoza-Palacios, David González-Sánchez |
| title_fullStr | An introduction to optimal control theory the dynamic programming approach Onésimo Hernández-Lerma, Leonardo R. Laura-Guarachi, Saul Mendoza-Palacios, David González-Sánchez |
| title_full_unstemmed | An introduction to optimal control theory the dynamic programming approach Onésimo Hernández-Lerma, Leonardo R. Laura-Guarachi, Saul Mendoza-Palacios, David González-Sánchez |
| title_short | An introduction to optimal control theory |
| title_sort | an introduction to optimal control theory the dynamic programming approach |
| title_sub | the dynamic programming approach |
| topic | Stochastic models Stochastic processes |
| topic_facet | Stochastic models Stochastic processes |
| volume_link | (DE-604)BV002476038 |
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