Randomized Algorithms for Analysis and Control of Uncertain Systems (Communications and Control Engineering) - Softcover

Tempo, Roberto; Calafiore, Giuseppe; Dabbene, Fabrizio

Softcover

ISBN 10: 1849968829 ISBN 13: 9781849968829

Publisher: Springer, 2010

Synopsis

Moving on from earlier stochastic and robust control paradigms, this book introduces the  fundamentals of probabilistic methods in the analysis and design of uncertain systems. The use of randomized algorithms, guarantees a reduction in the computational complexity of classical robust control algorithms and in the conservativeness of methods like H-infinity control.

Features:

• self-contained treatment explaining randomized algorithms from their genesis in the principles of probability theory to their use for robust analysis and controller synthesis;

• comprehensive treatment of sample generation, including consideration of the difficulties involved in obtaining independent and identically distributed samples;

• applications in congestion control of high-speed communications networks and the stability of quantized sampled-data systems.

This monograph will be of interest to theorists concerned with robust and optimal control techniques and to all control engineers dealing with system uncertainties.

About this title

About the Author

Roberto Tempo is one of the next generation of "top brass" in the control research community. He is currently the director of research at the National Research Council of Italy. Like any leading academic, he has the usual "long-as-your-arm" string of publications, both in refereed journals and at conferences. This is his second book, the first being an edited volume Robustness in Identification and Control. He is a regular member of program committees for several IFAC, IEEE, IEE and EUCA (European Union Control Association) conferences including Conference on Decision and Control (of which he will be program chair when the conference joins with ECC in Seville 2005) and is a fellow of the IEEE. He has been Associate Editor of IEEE Transaction on Automatic Control and is at present the Deputy Editor-in-Chief of Automatica the most widely read and respected journal in the field of theoretical control.

Giuseppe Calafiore is an up-and coming academic who has established a reputation on both sides of the Atlantic with frequent periods as a visiting scholar at both Stanford University and UC Berkeley.

From the Back Cover

The presence of uncertainty in a system description has always been a critical issue in control. Moving on from earlier stochastic and robust control paradigms, the main objective of this book is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of uncertain systems. Using so-called "randomized algorithms", this emerging area of research guarantees a reduction in the computational complexity of classical robust control algorithms and in the conservativeness of methods like H-infinity control.

Features:

• self-contained treatment explaining randomized algorithms from their genesis in the principles of probability theory to their use for robust analysis and controller synthesis;

• comprehensive treatment of sample generation, including consideration of the difficulties involved in obtaining independent and identically distributed samples;

• applications of randomized algorithms in congestion control of high-speed communications networks and the stability of quantized sampled-data systems.

Randomized Algorithms for Analysis and Control of Uncertain Systems will be of certain interest to control theorists concerned with robust and optimal control techniques and to all 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

Edition details

• Publisher: Springer
• Publication date: 2010
• Language: English
• ISBN 10: 1849968829
• ISBN 13: 9781849968829
• Binding: Paperback
• Number of pages: 361