Both refining and extending previous publications by the authors, the material in this monograph has been class-tested in mathematical institutions throughout the world. Covering some of the key areas of optimal control theory (OCT)―a rapidly expanding field that has developed to analyze the optimal behavior of a constrained process over time―the authors use new methods to set out a version of OCT’s more refined ‘maximum principle’ designed to solve the problem of constructing optimal control strategies for uncertain systems where some parameters are unknown. Known as a ‘min-max’ problem, this type of difficulty occurs frequently when dealing with finite uncertain sets.
The text begins with a standalone section that reviews classical optimal control theory. Moving on to examine the tent method in detail, the book then presents its core material, which is a more robust maximum principle for both deterministic and stochastic systems. The results obtained have applications in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games.
Using powerful new tools in optimal control theory, this book explores material that will be of great interest to post-graduate students, researchers, and practitioners in applied mathematics and engineering, particularly in the area of systems and control.
"synopsis" may belong to another edition of this title.
Both refining and extending previous publications by the authors, the material in this monograph has been class-tested in mathematical institutions throughout the world. Covering some of the key areas of optimal control theory (OCT)―a rapidly expanding field that has developed to analyze the optimal behavior of a constrained process over time―the authors use new methods to set out a version of OCT’s more refined ‘maximum principle’ designed to solve the problem of constructing optimal control strategies for uncertain systems where some parameters are unknown. Referred to as a ‘min-max’ problem, this type of difficulty occurs frequently when dealing with finite uncertain sets.
The text begins with a standalone section that reviews classical optimal control theory, covering the principal topics of the maximum principle and dynamic programming and considering the important sub-problems of linear quadratic optimal control and time optimization. Moving on to examine the tent method in detail, the book then presents its core material, which is a more robust maximum principle for both deterministic and stochastic systems. The results obtained have applications in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games.
Key features and topics include:
* A version of the tent method in Banach spaces
* How to apply the tent method to a generalization of the Kuhn-Tucker Theorem as well as the Lagrange Principle for infinite-dimensional spaces
* A detailed consideration of the min-max linear quadratic (LQ) control problem
* The application of obtained results from dynamic programming derivations to multi-model sliding mode control and multi-model differential games
* Two examples, dealing with production planning and reinsurance-dividend management, that illustrate the use of the robust maximum principle in stochastic systems
Usingpowerful new tools in optimal control theory, The Robust Maximum Principle explores material that will be of great interest to post-graduate students, researchers, and practitioners in applied mathematics and engineering, particularly in the area of systems and control.
"About this title" may belong to another edition of this title.
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Hardcover. Condition: new. Hardcover. Both refining and extending previous publications by the authors, the material in this monograph has been class-tested in mathematical institutions throughout the world. Covering some of the key areas of optimal control theory (OCT)a rapidly expanding field that has developed to analyze the optimal behavior of a constrained process over timethe authors use new methods to set out a version of OCTs more refined maximum principle designed to solve the problem of constructing optimal control strategies for uncertain systems where some parameters are unknown. Known as a min-max problem, this type of difficulty occurs frequently when dealing with finite uncertain sets.The text begins with a standalone section that reviews classical optimal control theory. Moving on to examine the tent method in detail, the book then presents its core material, which is a more robust maximum principle for both deterministic and stochastic systems. The results obtained have applications in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games. Using powerful new tools in optimal control theory, this book explores material that will be of great interest to post-graduate students, researchers, and practitioners in applied mathematics and engineering, particularly in the area of systems and control. Covering key areas of optimal control theory, this book uses new methods to set out a version of OCT's more refined 'maximum principle' aimed at solving the problem of constructing optimal control strategies for uncertain systems with some unknown parameters. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780817681517
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Covering some of the key areas of optimal control theory (OCT), a rapidly expanding field, the authors use new methods to set out a version of OCT's more refined 'maximum principle.' The results obtained have applications in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games. This book explores material that will be of great interest to post-graduate students, researchers, and practitioners in applied mathematics and engineering, particularly in the area of systems and control. 456 pp. Englisch. Seller Inventory # 9780817681517
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