"An excellent introduction to optimal control and estimation theory and its relationship with LQG design .... invaluable as a reference for those already familiar with the subject." - Automatica
Chapter 4 of the book presents methods for estimating the dynamic states of a system that is driven by forces and is observed with random measurement error. Chapter 5 discusses the general problem of stochastic optimal control, and the concluding chapter covers linear time-invariant systems.
Robert F. Stengel is Professor Emeritus of Mechanical and Aerospace Engineering at Princeton University. He was a principal designer of the Project Apollo Lunar Module manual attitude control system.
"An excellent teaching book with many examples and worked problems that would be ideal for self study or for use in the classroom .... The book also has a practical orientation and would be of considerable use to people applying these techniques in practice." - Short Book Reviews, Publication of the International Statistical Institute
"An excellent book which guides the reader through most of the important concepts and techniques of the title subject .... A useful book for students (and their teachers) and for those practising engineers who require a comprehensive reference to the subject." - Library Reviews, The Royal Aeronautical SocietyUnabridged, corrected Dover (1994) republication of Stochastic Optimal Control: Theory and Application, published by John Wiley & Sons, New York, 1986. 142 illustrations. Preface to Dover edition. Biography of author. Problems. References. Index. xv + 639 pp. 5-5/8 x 8-1/4. Paperbound. ISBN 0-486-68200-5.
"The book provides an excellent introductory text to the broad field of optimization .... The highly readable text is complemented with both examples and references enabling the reader to research further points of particular interest." - Automatica
"A valuable book which provides an illuminating insight into many aspects of optimal control .... the reader finds the concepts and methodology expounded in a progressive direct manner, marked by clarity of insight and presentation .... This lucidly written book by Stengel can be confidently recommended to anyone desiring to develop a thorough working knowledge of the subject of stochastic optimal control. It should certainly find a place in the reference library." - Robotica
"... describes a body of techniques that is quite useful in determining the best strategy for controlling a system in the presence of uncertainty.... The power of stochastic optimal control becomes apparent, as interpreted by notions drawn from classical control applied to multi-input/multi-output systems .... Although many interesting developments in control system analysis have been made recently, optimality remains the most important unifying criterion for control system synthesis." - IEEE Control Systems Magazine
"This book is a great one for people interested in nonlinear controls and the Kalman filter at a budget cost. The book introduces stochastic optimal control concepts for application to actual problems with sufficient theoretical background to justify their use, but not enough to get bogged down in the math. The book gives the reader with little background in control theory the tools to design practical control systems and the confidence to tackle more advanced literature - something that both the professional who is a little rusty and the student can appreciate.... There are also numerous worked out numerical examples, which is a welcome pleasure in such books that are often very theoretical. Highly recommended." - Anon (2008), Amazon
"Great book, I'm toward the end of my PhD, really wish I had come across this book sooner, very well done, presented in down to earth manner." - Anon (2018), Amazon
"This is a very well written book. A lot of good info in here with interesting examples of how to apply the content. Most of the optimal control books that I have seen are impossible to understand unless you are a mathematician, but this one is different. This is a great book for engineers." - Anon (2015), Amazon