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The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten.
Features:
· self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis;
· development of a novel paradigm for (convex and nonconvex) controller synthesis in the presence of uncertainty and in the context of randomized algorithms;
· comprehensive treatment of multivariate sample generation techniques, including consideration of the difficulties involved in obtaining identically and independently distributed samples;
· applications of randomized algorithms in various endeavours, such as PageRank computation for the Google Web search engine, unmanned aerial vehicle design (both new in the second edition), congestion control of high-speed communications networks and stability of quantized sampled-data systems.
Randomized Algorithms for Analysis and Control of Uncertain Systems (second edition) is certain to interest academic researchers and graduate control students working in probabilistic, robust or optimal control methods and control engineers dealing with system uncertainties.
The present book is a very timely contribution to the literature. I have no hesitation in asserting that it will remain a widely cited reference work for many years.
M. Vidyasagar
Editorial ReviewsReviewFrom the book reviews:“I found this book to be both, an excellent introduction to randomized methods for people unfamiliar with the topic, and a very good refresher for those already familiar with the subject but who have not closely followed its latest development. … the book is suitable for both self-learning or an advanced, graduate level, seminar style course.” (Mario Sznaier, Automatica, Vol. 50 (7), July, 2014)
“The book focuses on the fundamentals of probabilistic and randomized methods for analysis and design of uncertain systems. … The book can be recommended to mathematicians working in pure mathematics or application of mathematics to uncertain systems.” (Eugen Mamontov, zbMATH, Vol. 1280, 2014)
“This book is a significantly updated edition of the 2005 monograph of the same title. … Of particular interest will be the discussion of new applications, including unmanned aerial vehicles, systems biology, and Google PageRank and other Web ranking systems. This book should appeal to readers of the first edition and to graduate students, researchers, and practitioners looking for a self-contained introduction to an active research field.” (IEEE Control Systems Magazine, October, 2013)
From the Back Cover
The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten.
Features:
· self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis;
· development of a novel paradigm for (convex and nonconvex) controller synthesis in the presence of uncertainty and in the context of randomized algorithms;
· comprehensive treatment of multivariate sample generation techniques, including consideration of the difficulties involved in obtaining identically and independently distributed samples;
· applications of randomized algorithms in various endeavours, such as PageRank computation for the Google Web search engine, unmanned aerial vehicle design (both new in the second edition), congestion control of high-speed communications networks and stability of quantized sampled-data systems.
Randomized Algorithms for Analysis and Control of Uncertain Systems (second edition) is certain to interest academic researchers and graduate control students working in probabilistic, robust or optimal control methods and control engineers dealing with system uncertainties.
The present book is a very timely contribution to the literature. I have no hesitation in asserting that it will remain a widely cited reference work for many years.
M. Vidyasagar
The Communications and Control Engineering series reports major technological advances which have potential for great impact in the fields of communication and control. It reflects research in industrial and academic institutions around the world so that the readership can exploit new possibilities as they become available.
Product Details
- Series: Communications and Control Engineering
- Hardcover: 360 pages
- Publisher: Springer; 2nd ed. 2013 edition (October 21, 2012)
- Language: English
- ISBN-10: 1447146093
- ISBN-13: 978-1447146094
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