Stochastic Modeling And Control
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Stochastic Modeling And Control
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Author : Ivan Ivanov
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-11-28
Stochastic Modeling And Control written by Ivan Ivanov and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-28 with Mathematics categories.
Stochastic control plays an important role in many scientific and applied disciplines including communications, engineering, medicine, finance and many others. It is one of the effective methods being used to find optimal decision-making strategies in applications. The book provides a collection of outstanding investigations in various aspects of stochastic systems and their behavior. The book provides a self-contained treatment on practical aspects of stochastic modeling and calculus including applications drawn from engineering, statistics, and computer science. Readers should be familiar with basic probability theory and have a working knowledge of stochastic calculus. PhD students and researchers in stochastic control will find this book useful.
Stochastic Modeling And Control
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Author : Jacek Jakubowski
language : en
Publisher:
Release Date : 2020
Stochastic Modeling And Control written by Jacek Jakubowski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Stochastic Modelling And Control
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Author : Mark Davis
language : en
Publisher: Springer
Release Date : 2012-02-13
Stochastic Modelling And Control written by Mark Davis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-13 with Science categories.
This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory.
Stochastic Modeling Of Manufacturing Systems
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Author : George Liberopoulos
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-12
Stochastic Modeling Of Manufacturing Systems written by George Liberopoulos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-12 with Business & Economics categories.
Manufacturing systems rarely perform exactly as expected and predicted. Unexpected events, such as order changes, equipment failures and product defects, affect the performance of the system and complicate decision-making. This volume is devoted to the development of analytical methods aiming at responding to variability in a way that limits its corrupting effects on system performance. The book includes fifteen novel chapters that mostly focus on the development and analysis of performance evaluation models of manufacturing systems using decomposition-based methods, Markovian and queuing analysis, simulation, and inventory control approaches. They are organized into four distinct sections to reflect their shared viewpoints: factory design, unreliable production lines, queuing network models, production planning and assembly.
Optimal Stochastic Modeling And Control Of Flexible Structures
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Author :
language : en
Publisher:
Release Date : 1988
Optimal Stochastic Modeling And Control Of Flexible Structures written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with categories.
Modeling and control design of large flexible space structures under high uncertainty is considered. Linear stochastic system models with multiplicative and additive noises that are state -, control -, and measurement - dependent are treated extensively. Controllability, observability, and robustness issues are also discussed under various optimality considerations. An optimal stochastic controller is derived under perfect information and a sub- optimal compensator is formulated under partial and noisy information. The intent of the report is to treat the modeling of uncertainties and to develop the appropriate stochastic control that is robust. Aircraft; Jet aircraft; Linear control systems; Stochastic systems; Optimal control; Estimation; Robust control systems; Stochastic discreet time system; Multi-variable control.
Stochastic Modelling And Control
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Author : M. H. A. Davis
language : en
Publisher: Springer
Release Date : 1985-05-16
Stochastic Modelling And Control written by M. H. A. Davis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-05-16 with Juvenile Nonfiction categories.
This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory.
Econometric Decision Models
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Author : Josef Gruber
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Econometric Decision Models written by Josef Gruber and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Business & Economics categories.
This volume contains a refereed selection of revised papers which were originally presented at the Second International Conference on Econometric Decision Models, University of Hagen (FernUni versitat). The conference was held in Haus Nordhelle, a meeting place in the mountainous area " Sauerland" , some 50 kilometers south of Hagen, on August 29 - September 1, 1989. Some details about this conference are given in the first paper, they need not be repeated here. The 40 papers included in this volume are organized in 10 "parts", shown in the table of contents. Included are such "fashionable" topics like "optimal control", "cointegration" and "rational expec tations models". In each part, the papers have been arranged alphabetically by author, unless there were good reasons for a different arrangement. To facilitate the decision making of the readers, all papers (except a few short ones) contain an abstract, a list of keywords and a table of contents. At the end of the proceedings volume, there is a list of authors. More than ten years ago, I began to organize meetings of econometricians, mainly called "seminar" or " colloquium". One major purpose of these meetings has always been to improve international cooperation of econometric model builders (and model users) from "the East" and "the West". Unprecedented changes to the better have taken place recently ("perestroika"). For a large fraction of participants from the Soviet Union, the 1989 conference was the first conference in a Western country.
Ecai 2004
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Author : Ramon López de Mántaras
language : en
Publisher: IOS Press
Release Date : 2004
Ecai 2004 written by Ramon López de Mántaras and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
This is the Golden Age for Artificial Intelligence. The world is becoming increasingly automated and wired together. This also increases the opportunities for AI to help people and commerce. Almost every sub field of AI had now been used in substantial applications. Some of the fields highlighted in this publication are: CBR Technology; Model Based Systems; Data Mining and Natural Language Techniques. Not only does this publication show the activities, capabilities and accomplishments of the sub fields, it also focuses on what is happening across the field as a whole.
Applied Stochastic Models And Control For Finance And Insurance
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Author : Charles S. Tapiero
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Applied Stochastic Models And Control For Finance And Insurance written by Charles S. Tapiero and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
Applied Stochastic Models and Control for Finance and Insurance presents at an introductory level some essential stochastic models applied in economics, finance and insurance. Markov chains, random walks, stochastic differential equations and other stochastic processes are used throughout the book and systematically applied to economic and financial applications. In addition, a dynamic programming framework is used to deal with some basic optimization problems. The book begins by introducing problems of economics, finance and insurance which involve time, uncertainty and risk. A number of cases are treated in detail, spanning risk management, volatility, memory, the time structure of preferences, interest rates and yields, etc. The second and third chapters provide an introduction to stochastic models and their application. Stochastic differential equations and stochastic calculus are presented in an intuitive manner, and numerous applications and exercises are used to facilitate their understanding and their use in Chapter 3. A number of other processes which are increasingly used in finance and insurance are introduced in Chapter 4. In the fifth chapter, ARCH and GARCH models are presented and their application to modeling volatility is emphasized. An outline of decision-making procedures is presented in Chapter 6. Furthermore, we also introduce the essentials of stochastic dynamic programming and control, and provide first steps for the student who seeks to apply these techniques. Finally, in Chapter 7, numerical techniques and approximations to stochastic processes are examined. This book can be used in business, economics, financial engineering and decision sciences schools for second year Master's students, as well as in a number of courses widely given in departments of statistics, systems and decision sciences.
Probabilistic Modeling In System Engineering
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Author : Andrey Kostogryzov
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-09-26
Probabilistic Modeling In System Engineering written by Andrey Kostogryzov and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-26 with Technology & Engineering categories.
This book is intended for systems analysts, designers, developers, users, experts, as well as those involved in quality, risk, safety and security management, and, of course, scientists and students. The various sets of original and traditional probabilistic models and interesting results of their applications to the research of different systems are presented. The models are understandable and applicable for solving system engineering problems: to optimize system requirements, compare different processes, rationale technical decisions, carry out tests, adjust technological parameters, and predict and analyze quality and risks. The engineering decisions, scientifically proven by the proposed models and software tools, can provide purposeful, essential improvement of quality and mitigation of risks, and reduce the expense of operating systems. Models, methods, and software tools can also be used in education for system analysis and mathematical modeling on specializations, for example "systems engineering," "operations research," "enterprise management," "project management," "risk management," "quality of systems," "safety and security," "smart systems," "system of systems," etc.