Randomized Algorithms for Analysis and Control of Uncertain Systems: With Applications

✍ Scribed by Roberto Tempo, Giuseppe Calafiore, Fabrizio Dabbene (auth.)

• Publisher: Springer-Verlag London
• Year: 2013
• Tongue: English
• Leaves: 362
• Series: Communications and Control Engineering
• Edition: 2
• Category: Library

✦ Synopsis

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

✦ Table of Contents

Front Matter....Pages I-XXIII
Overview....Pages 1-6
Elements of Probability Theory....Pages 7-12
Uncertain Linear Systems....Pages 13-39
Linear Robust Control Design....Pages 41-57
Limits of the Robustness Paradigm....Pages 59-69
Probabilistic Methods for Uncertain Systems....Pages 71-91
Monte Carlo Methods....Pages 93-108
Probability Inequalities....Pages 109-121
Statistical Learning Theory....Pages 123-134
Randomized Algorithms in Systems and Control....Pages 135-146
Sequential Methods for Probabilistic Design....Pages 147-163
Scenario Approach to Probabilistic Design....Pages 165-179
Learning-Based Probabilistic Design....Pages 181-191
Random Number and Variate Generation....Pages 193-215
Statistical Theory of Random Vectors....Pages 217-229
Vector Randomization Methods....Pages 231-242
Statistical Theory of Random Matrices....Pages 243-266
Matrix Randomization Methods....Pages 267-282
Applications of Randomized Algorithms....Pages 283-327
Back Matter....Pages 329-357

✦ Subjects

Control;Systems Theory, Control;Complexity;Algorithms;Communications Engineering, Networks