9780387901558-0387901558-Deterministic and Stochastic Optimal Control (Stochastic Modelling and Applied Probability, 1)

Deterministic and Stochastic Optimal Control (Stochastic Modelling and Applied Probability, 1)

ISBN-13: 9780387901558
ISBN-10: 0387901558
Edition: 1
Author: Wendell H. Fleming, Raymond W. Rishel
Publication date: 1975
Publisher: Springer
Format: Hardcover 233 pages
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ISBN-13: 9780387901558
ISBN-10: 0387901558
Edition: 1
Author: Wendell H. Fleming, Raymond W. Rishel
Publication date: 1975
Publisher: Springer
Format: Hardcover 233 pages

Summary

Deterministic and Stochastic Optimal Control (Stochastic Modelling and Applied Probability, 1) (ISBN-13: 9780387901558 and ISBN-10: 0387901558), written by authors Wendell H. Fleming, Raymond W. Rishel, was published by Springer in 1975. With an overall rating of 4.1 stars, it's a notable title among other Robotics (Hardware & DIY, Computer Science) books. You can easily purchase or rent Deterministic and Stochastic Optimal Control (Stochastic Modelling and Applied Probability, 1) (Hardcover, Used) from BooksRun, along with many other new and used Robotics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.75.

Description

This book may be regarded as consisting of two parts. In Chapters I-IV we pre sent what we regard as essential topics in an introduction to deterministic optimal control theory. This material has been used by the authors for one semester graduate-level courses at Brown University and the University of Kentucky. The simplest problem in calculus of variations is taken as the point of departure, in Chapter I. Chapters II, III, and IV deal with necessary conditions for an opti mum, existence and regularity theorems for optimal controls, and the method of dynamic programming. The beginning reader may find it useful first to learn the main results, corollaries, and examples. These tend to be found in the earlier parts of each chapter. We have deliberately postponed some difficult technical proofs to later parts of these chapters. In the second part of the book we give an introduction to stochastic optimal control for Markov diffusion processes. Our treatment follows the dynamic pro gramming method, and depends on the intimate relationship between second order partial differential equations of parabolic type and stochastic differential equations. This relationship is reviewed in Chapter V, which may be read inde pendently of Chapters I-IV. Chapter VI is based to a considerable extent on the authors' work in stochastic control since 1961. It also includes two other topics important for applications, namely, the solution to the stochastic linear regulator and the separation principle.

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