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Sensitivity Analysis for Optimal Control Problems. Stochastic Optimal Control with a Probability Constraint

Sensitivity Analysis for Optimal Control Problems. Stochastic Optimal Control with a Probability Constraint PDF Author: Laurent Pfeiffer
Publisher:
ISBN:
Category :
Languages : en
Pages : 219

Book Description


Sensitivity Analysis for Optimal Control Problems. Stochastic Optimal Control with a Probability Constraint

Sensitivity Analysis for Optimal Control Problems. Stochastic Optimal Control with a Probability Constraint PDF Author: Laurent Pfeiffer
Publisher:
ISBN:
Category :
Languages : en
Pages : 219

Book Description


Stability and Sensitivity Analysis for Optimal Control Problems with Control-state Constraints

Stability and Sensitivity Analysis for Optimal Control Problems with Control-state Constraints PDF Author: Kazimierz Malanowski
Publisher:
ISBN:
Category : Differential equations, Nonlinear
Languages : en
Pages : 51

Book Description


Stochastic Analysis, Control, Optimization and Applications

Stochastic Analysis, Control, Optimization and Applications PDF Author: William M. McEneaney
Publisher: Springer Science & Business Media
ISBN: 9780817640781
Category : Mathematics
Languages : en
Pages : 892

Book Description
In view of Professor Wendell Fleming's many fundamental contributions, his profound influence on the mathematical and systems theory communi ties, his service to the profession, and his dedication to mathematics, we have invited a number of leading experts in the fields of control, optimiza tion, and stochastic systems to contribute to this volume in his honor on the occasion of his 70th birthday. These papers focus on various aspects of stochastic analysis, control theory and optimization, and applications. They include authoritative expositions and surveys as well as research papers on recent and important issues. The papers are grouped according to the following four major themes: (1) large deviations, risk sensitive and Hoc control, (2) partial differential equations and viscosity solutions, (3) stochastic control, filtering and parameter esti mation, and (4) mathematical finance and other applications. We express our deep gratitude to all of the authors for their invaluable contributions, and to the referees for their careful and timely reviews. We thank Harold Kushner for having graciously agreed to undertake the task of writing the foreword. Particular thanks go to H. Thomas Banks for his help, advice and suggestions during the entire preparation process, as well as for the generous support of the Center for Research in Scientific Computation. The assistance from the Birkhauser professional staff is also greatly appreciated.

Numerical Methods in Sensitivity Analysis and Shape Optimization

Numerical Methods in Sensitivity Analysis and Shape Optimization PDF Author: Emmanuel Laporte
Publisher: Springer Science & Business Media
ISBN: 1461200695
Category : Technology & Engineering
Languages : en
Pages : 202

Book Description
Sensitivity analysis and optimal shape design are key issues in engineering that have been affected by advances in numerical tools currently available. This book, and its supplementary online files, presents basic optimization techniques that can be used to compute the sensitivity of a given design to local change, or to improve its performance by local optimization of these data. The relevance and scope of these techniques have improved dramatically in recent years because of progress in discretization strategies, optimization algorithms, automatic differentiation, software availability, and the power of personal computers. Numerical Methods in Sensitivity Analysis and Shape Optimization will be of interest to graduate students involved in mathematical modeling and simulation, as well as engineers and researchers in applied mathematics looking for an up-to-date introduction to optimization techniques, sensitivity analysis, and optimal design.

Optimal Control

Optimal Control PDF Author: Peter Whittle
Publisher: Wiley
ISBN: 9780471960997
Category : Mathematics
Languages : en
Pages : 474

Book Description
The concept of a system as an entity in its own right has emerged with increasing force in the past few decades in, for example, the areas of electrical and control engineering, economics, ecology, urban structures, automaton theory, operational research and industry. The more definite concept of a large-scale system is implicit in these applications, but is particularly evident in fields such as the study of communication networks, computer networks and neural networks. The Wiley-Interscience Series in Systems and Optimization has been established to serve the needs of researchers in these rapidly developing fields. It is intended for works concerned with developments in quantitative systems theory, applications of such theory in areas of interest, or associated methodology. This is the first book-length treatment of risk-sensitive control, with many new results. The quadratic cost function of the standard LQG (linear/quadratic/Gaussian) treatment is replaced by the exponential of a quadratic, giving the so-called LEQG formulation allowing for a degree of optimism or pessimism on the part of the optimiser. The author is the first to achieve formulation and proof of risk-sensitive versions of the certainty-equivalence and separation principles. Further analysis allows one to formulate the optimization as the extremization of a path integral and to characterize the solution in terms of canonical factorization. It is thus possible to achieve the long-sought goal of an operational stochastic maximum principle, valid for a higher-order model, and in fact only evident when the models are extended to the risk-sensitive class. Additional results include deduction of compact relations between value functions and canonical factors, the exploitation of the equivalence between policy improvement and Newton Raphson methods and the direct relation of LEQG methods to the H??? and minimum-entropy methods. This book will prove essential reading for all graduate students, researchers and practitioners who have an interest in control theory including mathematicians, engineers, economists, physicists and psychologists. 1990 Stochastic Programming Peter Kall, University of Zurich, Switzerland and Stein W. Wallace, University of Trondheim, Norway Stochastic Programming is the first textbook to provide a thorough and self-contained introduction to the subject. Carefully written to cover all necessary background material from both linear and non-linear programming, as well as probability theory, the book draws together the methods and techniques previously described in disparate sources. After introducing the terms and modelling issues when randomness is introduced in a deterministic mathematical programming model, the authors cover decision trees and dynamic programming, recourse problems, probabilistic constraints, preprocessing and network problems. Exercises are provided at the end of each chapter. Throughout, the emphasis is on the appropriate use of the techniques, rather than on the underlying mathematical proofs and theories, making the book ideal for researchers and students in mathematical programming and operations research who wish to develop their skills in stochastic programming. 1994

Linear Stochastic Control Systems

Linear Stochastic Control Systems PDF Author: Goong Chen
Publisher: CRC Press
ISBN: 9780849380754
Category : Business & Economics
Languages : en
Pages : 404

Book Description
Linear Stochastic Control Systems presents a thorough description of the mathematical theory and fundamental principles of linear stochastic control systems. Both continuous-time and discrete-time systems are thoroughly covered. Reviews of the modern probability and random processes theories and the Itô stochastic differential equations are provided. Discrete-time stochastic systems theory, optimal estimation and Kalman filtering, and optimal stochastic control theory are studied in detail. A modern treatment of these same topics for continuous-time stochastic control systems is included. The text is written in an easy-to-understand style, and the reader needs only to have a background of elementary real analysis and linear deterministic systems theory to comprehend the subject matter. This graduate textbook is also suitable for self-study, professional training, and as a handy research reference. Linear Stochastic Control Systems is self-contained and provides a step-by-step development of the theory, with many illustrative examples, exercises, and engineering applications.

Parametric sensitivity analysis for control-constrained optimal control problems governed partial differential equations

Parametric sensitivity analysis for control-constrained optimal control problems governed partial differential equations PDF Author: Roland Griesse
Publisher:
ISBN:
Category :
Languages : en
Pages : 194

Book Description


Perturbations, Approximations, and Sensitivity Analysis of Optimal Control Systems

Perturbations, Approximations, and Sensitivity Analysis of Optimal Control Systems PDF Author: A. L. Dontchev
Publisher: Springer
ISBN:
Category : Science
Languages : en
Pages : 170

Book Description
Devoted to current problems in sensitivity analysis of optimal control. Two topics are considered: well-posedness, i.e. continuation of the solutions; & estimation of variations in solutions of constrained optimal control problems resulting from various changes of the model.

Risk-Sensitive Optimal Control

Risk-Sensitive Optimal Control PDF Author: Peter Whittle
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 266

Book Description
The two major themes of this book are risk-sensitive control and path-integral or Hamiltonian formulation. It covers risk-sensitive certainty-equivalence principles, the consequent extension of the conventional LQG treatment and the path-integral formulation.

Discrete Event Systems

Discrete Event Systems PDF Author: Reuven Y. Rubinstein
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 360

Book Description
A unified and rigorous treatment of the associated stochastic optimization problems is provided and recent advances in perturbation theory encompassed. Throughout the book emphasis is upon concepts rather than mathematical completeness with the advantage that the reader only requires a basic knowledge of probability, statistics and optimization.