stochastic processes estimation and control

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Stochastic Processes Estimation And Control

Author : Jason L. Speyer
ISBN : 9780898716559
Genre : Mathematics
File Size : 40. 13 MB
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The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to stochastic optimal control. The book covers discrete- and continuous-time stochastic dynamic systems leading to the derivation of the Kalman filter, its properties, and its relation to the frequency domain Wiener filter aswell as the dynamic programming derivation of the linear quadratic Gaussian (LQG) and the linear exponential Gaussian (LEG) controllers and their relation to HÝsubscript 2¨ and HÝsubscript Ýinfinity¨¨ controllers and system robustness. This book is suitable for first-year graduate students in electrical, mechanical, chemical, and aerospace engineering specializing in systems and control. Students in computer science, economics, and possibly business will also find it useful.

Stochastic Processes Estimation And Control

Author : George N. Saridis
ISBN : UOM:39015034252653
Genre : Mathematics
File Size : 44. 63 MB
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The first new introduction to stochastic processes in 20 years incorporates a modern, innovative approach to estimation and control theory Stochastic Processes, Estimation, and Control: The Entropy Approach provides a comprehensive, up-to-date introduction to stochastic processes, together with a concise review of probability and system theory. Serving both as a text for graduate courses in control and systems engineering and as a guide for the practicing engineer and researcher, the book applies the most recent advances in stochastic and probabilistic processes to such areas as communications systems and robotics technology. Highlights of this outstanding text: Uses the thermodynamic principle of entropy as a tool with which to measure and analyze uncertainty in systems-a feature unique to this text Covers basic material on stochastic processes, parameter and state estimation and control with a novel approach that does not require advanced mathematics Introduces an original approach to the design of nonlinear stochastic control that converges sequentially to the optimal-a practical method that will be particularly appealing to the practicing engineer Reformulates the stochastic estimation and control problem from a global point of view and introduces entropy as the entity that defines control theory as an energy product-a groundbreaking approach Since the early 18th century, scientists have devised probability measures to help them describe uncertain phenomena and approximate the actual laws of nature. It was not until the advent of the computer, however, that stochastic processes have made it possible to approximate the uncertainty inherent in large complex systems. The miracles of space exploration, modern defense systems, and artificial intelligence are just a few of the dramatic advances that have come about due to the ability of the modern digital computer to perform massive probabilistic calculations. In this, the first introductory book on stochastic processes in twenty years, leading theoretician George Saridis provides a modern innovative approach that applies the most recent advances in probabilistic processes to such areas as communications and robotics technology. Stochastic Processes, Estimation, and Control: The Entropy Approach is designed as a text for graduate courses in dynamic programming and stochastic control, stochastic processes, or applied probability in the engineering or mathematical/computational science departments, and as a guide for the practicing engineer and researcher. It offers a lucid discussion of parameter estimation based on least square techniques, an in-depth investigation of the estimation of the states of a stochastic linear and nonlinear dynamic system, and a modified derivation of the linear-quadratic Gaussian optimal control problem. Professor Saridis's presentation of estimation and control theory is thorough, but avoids the use of advanced mathematics. A new theory of approximation of the optimal solution for nonlinear stochastic systems is presented as a general engineering tool, and the whole area of stochastic processes, estimation, and control is recast using entropy as a measure. Stochastic Processes, Estimation, and Control: The Entropy Approach is the first book to apply the thermodynamic principle of entropy to the measurement and analysis of uncertainty in systems. Its new reformulation takes an important first step toward a unified approach to the theory of intelligent machines, where artificial intelligence and system theory come together.

Stochastic Models Estimation And Control

Author : Maybeck
ISBN : 9780080956510
Genre : Mathematics
File Size : 53. 74 MB
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Stochastic Models: Estimation and Control: v. 2

Linear Estimation And Stochastic Control

Author : M. H. A. Davis
ISBN : UOM:39076005944918
Genre : Mathematics
File Size : 38. 1 MB
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Finite-dimensional linear estimation; Stochastic processes and linear estimation; Orthogonal increments processes; Estimation in dynamical systems; Linear stochastic control; An outline of further developments.

Stochastic Processes

Author : Kaddour Najim
ISBN : 008051779X
Genre : Mathematics
File Size : 31. 15 MB
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A ‘stochastic’ process is a ‘random’ or ‘conjectural’ process, and this book is concerned with applied probability and statistics. Whilst maintaining the mathematical rigour this subject requires, it addresses topics of interest to engineers, such as problems in modelling, control, reliability maintenance, data analysis and engineering involvement with insurance. This book deals with the tools and techniques used in the stochastic process – estimation, optimisation and recursive logarithms – in a form accessible to engineers and which can also be applied to Matlab. Amongst the themes covered in the chapters are mathematical expectation arising from increasing information patterns, the estimation of probability distribution, the treatment of distribution of real random phenomena (in engineering, economics, biology and medicine etc), and expectation maximisation. The latter part of the book considers optimization algorithms, which can be used, for example, to help in the better utilization of resources, and stochastic approximation algorithms, which can provide prototype models in many practical applications. * An engineering approach to applied probabilities and statistics * Presents examples related to practical engineering applications, such as reliability, randomness and use of resources * Readers with varying interests and mathematical backgrounds will find this book accessible

Discrete Time Stochastic Systems

Author : Torsten Söderström
ISBN : 0133096831
Genre : Mathematics
File Size : 33. 40 MB
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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.

Estimation And Control Problems For Stochastic Partial Differential Equations

Author : Pavel S. Knopov
ISBN : 9781461482864
Genre : Mathematics
File Size : 46. 72 MB
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Focusing on research surrounding aspects of insufficiently studied problems of estimation and optimal control of random fields, this book exposes some important aspects of those fields for systems modeled by stochastic partial differential equations. It contains many results of interest to specialists in both the theory of random fields and optimal control theory who use modern mathematical tools for resolving specific applied problems, and presents research that has not previously been covered. More generally, this book is intended for scientists, graduate, and post-graduates specializing in probability theory and mathematical statistics. The models presented describe many processes in turbulence theory, fluid mechanics, hydrology, astronomy, and meteorology, and are widely used in pattern recognition theory and parameter identification of stochastic systems. Therefore, this book may also be useful to applied mathematicians who use probability and statistical methods in the selection of useful signals subject to noise, hypothesis distinguishing, distributed parameter systems optimal control, and more. Material presented in this monograph can be used for education courses on the estimation and control theory of random fields.

Stochastic Optimal Linear Estimation And Control

Author : James S. Meditch
ISBN : UOM:39015006376852
Genre : Science
File Size : 38. 98 MB
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Optimal Control And Stochastic Estimation

Author : Michael J. Grimble
ISBN : 0471912654
Genre : Science
File Size : 33. 14 MB
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Modern Control System Theory

Author : M. Gopal
ISBN : 8122405037
Genre : Automatic control
File Size : 70. 70 MB
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About the book... The book provides an integrated treatment of continuous-time and discrete-time systems for two courses at postgraduate level, or one course at undergraduate and one course at postgraduate level. It covers mainly two areas of modern control theory, namely; system theory, and multivariable and optimal control. The coverage of the former is quite exhaustive while that of latter is adequate with significant provision of the necessary topics that enables a research student to comprehend various technical papers. The stress is on interdisciplinary nature of the subject. Practical control problems from various engineering disciplines have been drawn to illustrate the potential concepts. Most of the theoretical results have been presented in a manner suitable for digital computer programming along with the necessary algorithms for numerical computations.

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