Optimal Control: Basics and Beyond / Edition 1

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Optimal Control Basics and Beyond Peter Whittle Statistical Laboratory, University of Cambridge, UK ‘Control theory’ is now understood not merely in the narrow sense of the control of mechanisms but in the wider sense of the control of any dynamic system (e.g. communication, distribution, production, financial, economic), in general stochastic and imperfectly observed. The author takes this wider view and so covers general techniques of optimisation (e.g. dynamic programming and the maximum principle) as well as topics more classically associated with narrow-sense control theory (e.g. stability, feedback, controllability). There is now a great deal of standard material in this area, and it is to this which the ‘basics’ component of the book provides an introduction. However, while the material may be standard, the treatment of the section is shaped considerably by consciousness of the ‘beyond’ component into which it leads. This subsequent section covers risk-sensitive and H- criteria, time-integral methods, optimal stationary policies, near-determinism and large deviation theory. Covering both standard material and recent results, this book will prove to be essential reading for students and researchers with an interest in control theory. Contents Preface Basics Part 1 Deterministic Models Part 2 Stochastic Models Beyond Part 3 Risk-sensitive and H- Criteria Part 4 Time-integral Methods and Optimal Stationary Policies Part 5 Non-determinism and Large Deviation Theory Appendices References Index By the same author Optimization Over Time, Volume 2: Dynamic Programming and Stochastic Control Wiley 1983, ISBN 0 471 10496 5 Risk-Sensitive Optimal Control Wiley 1990, ISBN 0 471 92622 1 Of related interest Probability, Statistics and Optimization: A Tribute to Peter Whittle F.P. Kelly (Editor), Statistical Laboratory, University of Cambridge, UK Wiley 1994, ISBN 0 471 94829 2

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Editorial Reviews

Covers general techniques of optimization, such as dynamic programming and the maximum principle, as well as topics more classically associated with narrow-sense control theory. Section I on basics treats deterministic and stochastic models. Section II examines advanced subjects including risk sensitive and "H"-infinity criteria, time-integral methods, and near-determinism and large deviation theory. While much of the treatment is informal, conclusions are summarized in theorem-proof form. Includes exercises. For students and researchers in control theory. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

Meet the Author

About the author Professor Whittle was born and educated in Wellington, New Zealand. In 1951 he was awarded his PhD at the University of Uppsala, Sweden. He was then employed in the New Zealand DSIR until he took up an appointment as Lecturer in Mathematics at Cambridge University in 1959. After two years he became Professor of Mathematical Statistics at Manchester University, and in 1967 was appointed Churchill Professor of the Mathematics of Operational Research at Cambridge University. Professor Whittle was elected Fellow of the Royal Society in 1978, and an Honorary Fellow of the Royal Society of New Zealand in 1981. He was awarded the Lanchester Prize of the Operations Research Society of America in 1987 for his book Systems in Stochastic Equilibrium and received the Sylvester Prize of the Royal Society in 1994.

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Table of Contents


Deterministic Models.

Stochastic Models.


Risk-Sensitive and H infinity Criteria.

Time-Integral Methods and Optimal Stationary Policies.

Near-Determinism and Large Deviation Theory.




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