Estimation and Control Problems for Stochastic Partial Differential Equations

Estimation and Control Problems for Stochastic Partial Differential Equations PDF

Author: Pavel S. Knopov

Publisher: Springer Science & Business Media

Published: 2013-09-17

Total Pages: 191

ISBN-13: 1461482860

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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.

Mathematical Control Theory for Stochastic Partial Differential Equations

Mathematical Control Theory for Stochastic Partial Differential Equations PDF

Author: Qi Lü

Publisher: Springer Nature

Published: 2021-10-19

Total Pages: 592

ISBN-13: 3030823318

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This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for this type of system are explained in detail. Interestingly enough, one has to develop new mathematical tools to solve some problems in this field, such as the global Carleman estimate for stochastic partial differential equations and the stochastic transposition method for backward stochastic evolution equations. In a certain sense, the stochastic distributed parameter control system is the most general control system in the context of classical physics. Accordingly, studying this field may also yield valuable insights into quantum control systems. A basic grasp of functional analysis, partial differential equations, and control theory for deterministic systems is the only prerequisite for reading this book.

Deterministic and Stochastic Optimal Control and Inverse Problems

Deterministic and Stochastic Optimal Control and Inverse Problems PDF

Author: Baasansuren Jadamba

Publisher: CRC Press

Published: 2021-12-15

Total Pages: 394

ISBN-13: 1000511723

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Inverse problems of identifying parameters and initial/boundary conditions in deterministic and stochastic partial differential equations constitute a vibrant and emerging research area that has found numerous applications. A related problem of paramount importance is the optimal control problem for stochastic differential equations. This edited volume comprises invited contributions from world-renowned researchers in the subject of control and inverse problems. There are several contributions on optimal control and inverse problems covering different aspects of the theory, numerical methods, and applications. Besides a unified presentation of the most recent and relevant developments, this volume also presents some survey articles to make the material self-contained. To maintain the highest level of scientific quality, all manuscripts have been thoroughly reviewed.

Mathematical Control Theory for Stochastic Partial Differential Equations

Mathematical Control Theory for Stochastic Partial Differential Equations PDF

Author: Qi Lü

Publisher: Springer

Published: 2022-09-18

Total Pages: 0

ISBN-13: 9783030823337

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This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for this type of system are explained in detail. Interestingly enough, one has to develop new mathematical tools to solve some problems in this field, such as the global Carleman estimate for stochastic partial differential equations and the stochastic transposition method for backward stochastic evolution equations. In a certain sense, the stochastic distributed parameter control system is the most general control system in the context of classical physics. Accordingly, studying this field may also yield valuable insights into quantum control systems. A basic grasp of functional analysis, partial differential equations, and control theory for deterministic systems is the only prerequisite for reading this book.

Recursive Estimation and Control for Stochastic Systems

Recursive Estimation and Control for Stochastic Systems PDF

Author: Hanfu Chen

Publisher: John Wiley & Sons

Published: 1985

Total Pages: 400

ISBN-13:

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This self-contained reference for statisticians and engineers in system and control theory, analyzes the effect of convergent recursive estimation algorithms and stochastic approximation on the dependent noise case and the classic independent case. It discusses control and adaptive control problems related to recursive estimation, and introduces the combined probabilistic and differential equation method of data analysis.

Parameter Estimation in Stochastic Differential Equations

Parameter Estimation in Stochastic Differential Equations PDF

Author: Jaya P. N. Bishwal

Publisher: Springer

Published: 2007-09-26

Total Pages: 268

ISBN-13: 3540744487

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Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.

Stochastic Processes, Estimation, and Control

Stochastic Processes, Estimation, and Control PDF

Author: Jason L. Speyer

Publisher: SIAM

Published: 2008-01-01

Total Pages: 392

ISBN-13: 0898718597

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Uncertainty and risk are integral to engineering because real systems have inherent ambiguities that arise naturally or due to our inability to model complex physics. The authors discuss probability theory, stochastic processes, estimation, and stochastic control strategies and show how probability can be used to model uncertainty in control and estimation problems. The material is practical and rich in research opportunities.

Optimization and Control for Partial Differential Equations

Optimization and Control for Partial Differential Equations PDF

Author: Roland Herzog

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2022-03-07

Total Pages: 474

ISBN-13: 3110695987

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This book highlights new developments in the wide and growing field of partial differential equations (PDE)-constrained optimization. Optimization problems where the dynamics evolve according to a system of PDEs arise in science, engineering, and economic applications and they can take the form of inverse problems, optimal control problems or optimal design problems. This book covers new theoretical, computational as well as implementation aspects for PDE-constrained optimization problems under uncertainty, in shape optimization, and in feedback control, and it illustrates the new developments on representative problems from a variety of applications.

Estimation and Control of Dynamical Systems

Estimation and Control of Dynamical Systems PDF

Author: Alain Bensoussan

Publisher: Springer

Published: 2018-05-23

Total Pages: 547

ISBN-13: 3319754564

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This book provides a comprehensive presentation of classical and advanced topics in estimation and control of dynamical systems with an emphasis on stochastic control. Many aspects which are not easily found in a single text are provided, such as connections between control theory and mathematical finance, as well as differential games. The book is self-contained and prioritizes concepts rather than full rigor, targeting scientists who want to use control theory in their research in applied mathematics, engineering, economics, and management science. Examples and exercises are included throughout, which will be useful for PhD courses and graduate courses in general. Dr. Alain Bensoussan is Lars Magnus Ericsson Chair at UT Dallas and Director of the International Center for Decision and Risk Analysis which develops risk management research as it pertains to large-investment industrial projects that involve new technologies, applications and markets. He is also Chair Professor at City University Hong Kong.

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