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Deterministic techniques
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ISBN: 1281172103 9786611172107 0080556108 0080446744 9780080556109 9780080446745 Year: 2008 Publisher: Amsterdam : Elsevier,

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This book provides a blend of Matrix and Linear Algebra Theory, Analysis, Differential Equations, Optimization, Optimal and Robust Control. It contains an advanced mathematical tool which serves as a fundamental basis for both instructors and students who study or actively work in Modern Automatic Control or in its applications. It is includes proofs of all theorems and contains many examples with solutions. It is written for researchers, engineers, and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to System and A


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Advanced mathematical tools for automatic control engineers.
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ISBN: 1282309366 9786612309366 0080914039 0080446736 9780080914039 9780080446738 Year: 2009 Publisher: Oxford ; Amsterdam : Elsevier,

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The second volume of this work continues the approach of the first volume, providing mathematical tools for the control engineer and examining such topics as random variables and sequences, iterative logarithmic and large number laws, differential equations, stochastic measurements and optimization, discrete martingales and probability space. It includes proofs of all theorems and contains many examples with solutions.It is written for researchers, engineers and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to


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Classical and analytical mechanics : theory, applied examples, and practice
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ISBN: 0323898890 0323898165 9780323898898 9780323898164 Year: 2021 Publisher: Amsterdam, Netherlands ; Oxford, England ; Cambridge, Massachusetts : Elsevier,

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Advanced mathematical tools for automatic control engineers.
Author:
ISBN: 9780080556109 0080556108 9780080446745 0080446744 Year: 2008 Publisher: Amsterdam Boston Elsevier

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Abstract

This book provides a blend of Matrix and Linear Algebra Theory, Analysis, Differential Equations, Optimization, Optimal and Robust Control. It contains an advanced mathematical tool which serves as a fundamental basis for both instructors and students who study or actively work in Modern Automatic Control or in its applications. It is includes proofs of all theorems and contains many examples with solutions. It is written for researchers, engineers, and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to System and Automatic Control Theories * Provides comprehensive theory of matrices, real, complex and functional analysis * Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications * Contains worked proofs of all theorems and propositions presented.

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Advanced mathematical tools for automatic control engineers. Volume 2 : Stochastic techniques
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ISBN: 9780080914039 0080914039 Year: 2009 Publisher: Boston Elsevier Science

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Abstract

The second volume of this work continues the and approach of the first volume, providing mathematical tools for the control engineer and examining such topics as random variables and sequences, iterative logarithmic and large number laws, differential equations, stochastic measurements and optimization, discrete martingales and probability space. It includes proofs of all theorems and contains many examples with solutions. It is written for researchers, engineers and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to system and automatic control theories. It also has applications to game theory, machine learning and intelligent systems. * Provides comprehensive theory of matrices, real, complex and functional analysis * Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications * Contains worked proofs of all theorems and propositions presented.

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Learning automata : theory and applications
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ISBN: 0080420249 Year: 1994 Publisher: Oxford Pergamon

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The Robust Maximum Principle : Theory and Applications
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ISBN: 0817681515 0817681523 Year: 2012 Publisher: Boston, MA : Birkhäuser Boston : Imprint: Birkhäuser,

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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 Using powerful 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.


Digital
The Robust Maximum Principle : Theory and Applications
Authors: ---
ISBN: 9780817681524 Year: 2012 Publisher: Boston Birkhäuser Boston


Book
Ozonation and biodegradation in environmental engineering
Authors: --- ---
ISBN: 0128128488 012812847X 9780128128480 9780128128473 Year: 2019 Publisher: Amsterdam


Book
The Robust Maximum Principle : Theory and Applications
Authors: --- ---
ISBN: 9780817681524 Year: 2012 Publisher: Boston Birkhäuser Boston

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Abstract

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 Using powerful 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.

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