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Modeling Analysis Design And Control Of Stochastic Systems
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Book Synopsis Modeling, Analysis, Design, and Control of Stochastic Systems by : V. G. Kulkarni
Download or read book Modeling, Analysis, Design, and Control of Stochastic Systems written by V. G. Kulkarni and published by Springer. This book was released on 2014-01-13 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory level text on stochastic modelling, suited for undergraduates or graduates in actuarial science, business management, computer science, engineering, operations research, public policy, statistics, and mathematics. It employs a large number of examples to show how to build stochastic models of physical systems, analyse these models to predict their performance, and use the analysis to design and control them. The book provides a self-contained review of the relevant topics in probability theory: In discrete and continuous time Markov models it covers the transient and long term behaviour, cost models, and first passage times; under generalised Markov models, it covers renewal processes, cumulative processes and semi-Markov processes. All the material is illustrated with many examples, and the book emphasises numerical answers to the problems. A software package called MAXIM, which runs on MATLAB, is available for downloading.
Book Synopsis Introduction to Modeling and Analysis of Stochastic Systems by : V. G. Kulkarni
Download or read book Introduction to Modeling and Analysis of Stochastic Systems written by V. G. Kulkarni and published by Springer. This book was released on 2010-11-03 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a self-contained review of all the relevant topics in probability theory. A software package called MAXIM, which runs on MATLAB, is made available for downloading. Vidyadhar G. Kulkarni is Professor of Operations Research at the University of North Carolina at Chapel Hill.
Book Synopsis Applied Stochastic Processes and Control for Jump-Diffusions by : Floyd B. Hanson
Download or read book Applied Stochastic Processes and Control for Jump-Diffusions written by Floyd B. Hanson and published by SIAM. This book was released on 2007-01-01 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained, practical, entry-level text integrates the basic principles of applied mathematics, applied probability, and computational science for a clear presentation of stochastic processes and control for jump diffusions in continuous time. The author covers the important problem of controlling these systems and, through the use of a jump calculus construction, discusses the strong role of discontinuous and nonsmooth properties versus random properties in stochastic systems.
Book Synopsis Stochastic Modeling by : Barry L. Nelson
Download or read book Stochastic Modeling written by Barry L. Nelson and published by Courier Corporation. This book was released on 2012-10-11 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models, analysis, and interpretation of results. 1995 edition.
Book Synopsis Modeling and Analysis of Stochastic Systems Second Edition - Solutions Manual by : Taylor & Francis Group
Download or read book Modeling and Analysis of Stochastic Systems Second Edition - Solutions Manual written by Taylor & Francis Group and published by . This book was released on 2009-12-11 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical and accessible text enables readers from engineering, business, operations research, public policy and computer science to analyze stochastic systems. Emphasizing the modeling of real-life situations with stochastic elements and analyzing the resulting stochastic model, it presents the major cases of useful stochastic processes-discrete and continuous time Markov chains, renewal processes, regenerative processes, and Markov regenerative processes. The author provides reader-friendly yet rigorous coverage. He follows a set pattern of development for each class of stochastic processes and introduces Markov chains before renewal processes, so that readers can begin modeling systems early. He demonstrates both numerical and analytical solution methods in detail and dedicates a separate chapter to queueing applications. Modeling and Analysis of Stochastic Systems includes numerous worked examples and exercises, conveniently categorized as modeling, computational, or conceptual and making difficult concepts easy to grasp. Taking a practical approach to working with stochastic models, this book helps readers to model and analyze the increasingly complex and interdependent systems made possible by recent advances.
Download or read book Stochastic Systems written by P. R. Kumar and published by SIAM. This book was released on 2015-12-15 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.
Book Synopsis Stochastic Systems for Engineers by : John A. Borrie
Download or read book Stochastic Systems for Engineers written by John A. Borrie and published by . This book was released on 1992 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: A self-contained introduction to stochastic systems and an ordered presentation of techniques for computer modelling, filtering and control of these systems. The subject is developed with definition, formulae and explanations but without detailed mathematical proofs.
Book Synopsis Stochastic Discrete Event Systems by : Armin Zimmermann
Download or read book Stochastic Discrete Event Systems written by Armin Zimmermann and published by Springer Science & Business Media. This book was released on 2008-01-12 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic discrete-event systems (SDES) capture the randomness in choices due to activity delays and the probabilities of decisions. This book delivers a comprehensive overview on modeling with a quantitative evaluation of SDES. It presents an abstract model class for SDES as a pivotal unifying result and details important model classes. The book also includes nontrivial examples to explain real-world applications of SDES.
Book Synopsis Discrete-time Stochastic Systems by : Torsten Söderström
Download or read book Discrete-time Stochastic Systems written by Torsten Söderström and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive introduction to the estimation and control of dynamic stochastic systems provides complete derivations of key results. The second edition includes improved and updated material, and a new presentation of polynomial control and new derivation of linear-quadratic-Gaussian control.
Book Synopsis Stochastic Modeling of Manufacturing Systems by : George Liberopoulos
Download or read book Stochastic Modeling of Manufacturing Systems written by George Liberopoulos and published by Springer Science & Business Media. This book was released on 2005-12-12 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Modeling and Analysis of Stochastic Systems, Third Edition by : Vidyadhar G. Kulkarni
Download or read book Modeling and Analysis of Stochastic Systems, Third Edition written by Vidyadhar G. Kulkarni and published by CRC Press. This book was released on 2016-11-18 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.
Book Synopsis Modeling and Management of Stochastic Systems by : William Taylor
Download or read book Modeling and Management of Stochastic Systems written by William Taylor and published by . This book was released on 2015-01-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic control deals with the uncertainties in data observation playing a crucial role in data evolution. Stochastic control plays a crucial role in a number of scientific and applied disciplines including engineering, finance, communications and medicine. Stochastic modeling is one of the most useful techniques for formulation of optimal decision-making strategies in applications. This book provides a compilation of exceptional investigations in different aspects of stochastic systems and their behavior. It presents a distinct analysis on practical aspects of calculus and stochastic modeling including applications derived from computer science, engineering and statistics. This book will be of great utility to readers with knowledge about stochastic calculus and basic probability theory. It will specifically serve as a useful resource for PhD students and researchers in stochastic control.
Book Synopsis Stochastic Switching Systems by : El-Kébir Boukas
Download or read book Stochastic Switching Systems written by El-Kébir Boukas and published by Springer Science & Business Media. This book was released on 2007-05-24 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory chapter highlights basics concepts and practical models, which are then used to solve more advanced problems throughout the book. Included are many numerical examples and LMI synthesis methods and design approaches.
Book Synopsis Modeling and Analysis of Stochastic Systems by : Vidyadhar G. Kulkarni
Download or read book Modeling and Analysis of Stochastic Systems written by Vidyadhar G. Kulkarni and published by CRC Press. This book was released on 1996-05-15 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical and accessible text enables students in engineering, business, operations research, public policy and computer science to analyze stochastic systems. Emphasizing the modeling of real-life situations with stochastic elements and analyzing the resulting stochastic model, it presents the major cases of useful stochastic processes-discrete and continuous time Markov chains, renewal processes, regenerative processes, and Markov regenerative processes. The author provides user-friendly, yet rigorous coverage. He demonstrates both numerical and analytical solution methods in detail and includes numerous worked examples and exercises.
Book Synopsis Stochastic Modelling and Control by : Mark Davis
Download or read book Stochastic Modelling and Control written by Mark Davis and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis An Introduction to System Modeling and Control by : John Chiasson
Download or read book An Introduction to System Modeling and Control written by John Chiasson and published by John Wiley & Sons. This book was released on 2022-03-22 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical and straightforward exploration of the basic tools for the modeling, analysis, and design of control systems In An Introduction to System Modeling and Control, Dr. Chiasson delivers an accessible and intuitive guide to understanding modeling and control for students in electrical, mechanical, and aerospace/aeronautical engineering. The book begins with an introduction to the need for control by describing how an aircraft flies complete with figures illustrating roll, pitch, and yaw control using its ailerons, elevators, and rudder, respectively. The book moves on to rigid body dynamics about a single axis (gears, cart rolling down an incline) and then to modeling DC motors, DC tachometers, and optical encoders. Using the transfer function representation of these dynamic models, PID controllers are introduced as an effective way to track step inputs and reject constant disturbances. It is further shown how any transfer function model can be stabilized using output pole placement and on how two-degree of freedom controllers can be used to eliminate overshoot in step responses. Bode and Nyquist theory are then presented with an emphasis on how they give a quantitative insight into a control system's robustness and sensitivity. An Introduction to System Modeling and Control closes with chapters on modeling an inverted pendulum and a magnetic levitation system, trajectory tracking control using state feedback, and state estimation. In addition the book offers: A complete set of MATLAB/SIMULINK files for examples and problems included in the book. A set of lecture slides for each chapter. A solutions manual with recommended problems to assign. An analysis of the robustness and sensitivity of four different controller designs for an inverted pendulum (cart-pole). Perfect for electrical, mechanical, and aerospace/aeronautical engineering students, An Introduction to System Modeling and Control will also be an invaluable addition to the libraries of practicing engineers.
Book Synopsis Bounded Dynamic Stochastic Systems by : Hong Wang
Download or read book Bounded Dynamic Stochastic Systems written by Hong Wang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decades, although stochastic system control has been studied intensively within the field of control engineering, all the modelling and control strategies developed so far have concentrated on the performance of one or two output properties of the system. such as minimum variance control and mean value control. The general assumption used in the formulation of modelling and control strategies is that the distribution of the random signals involved is Gaussian. In this book, a set of new approaches for the control of the output probability density function of stochastic dynamic systems (those subjected to any bounded random inputs), has been developed. In this context, the purpose of control system design becomes the selection of a control signal that makes the shape of the system outputs p.d.f. as close as possible to a given distribution. The book contains material on the subjects of: - Control of single-input single-output and multiple-input multiple-output stochastic systems; - Stable adaptive control of stochastic distributions; - Model reference adaptive control; - Control of nonlinear dynamic stochastic systems; - Condition monitoring of bounded stochastic distributions; - Control algorithm design; - Singular stochastic systems. A new representation of dynamic stochastic systems is produced by using B-spline functions to descripe the output p.d.f. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
