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

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Feldname	Details
Vorliegende Sprache	eng
ISBN	978-1-4471-4609-4
Name	Tempo, Roberto
Name	Calafiore, Giuseppe
Name ANZEIGE DER KETTE	Calafiore, Giuseppe
Name	Dabbene, Fabrizio
T I T E L	Randomized Algorithms for Analysis and Control of Uncertain Systems
Zusatz zum Titel	With Applications
Auflage	2nd ed. 2013
Verlagsort	London
Verlag	Springer
Erscheinungsjahr	2013
Erscheinungsjahr	2013
Umfang	Online-Ressource (XXI, 357 p. 75 illus., 49 illus. in color, digital)
Reihe	Communications and Control Engineering
Notiz / Fußnoten	Description based upon print version of record
Weiterer Inhalt	Randomized Algorithms for Analysis and Control of Uncertain Systems; Foreword; Foreword to the First Edition; Preface to the Second Edition; Acknowledgements; Acknowledgments to the First Edition; Contents; Chapter 1: Overview; 1.1 Probabilistic and Randomized Methods; 1.2 Structure of the Book; Chapter 2: Elements of Probability Theory; 2.1 Probability, Random Variables and Random Matrices; 2.1.1 Probability Space; 2.1.2 Real and Complex Random Variables; Distribution and Density Functions; 2.1.3 Real and Complex Random Matrices; 2.1.4 Expected Value and Covariance. 2.2 Marginal and Conditional Densities2.3 Univariate and Multivariate Density Functions; Binomial Density; Normal Density; Multivariate Normal Density; Uniform Density; Uniform Density over a Set; Chi-Square Density; Weibull Density; Laplace Density; Gamma Density; Generalized Gamma Density; 2.4 Convergence of Random Variables; Chapter 3: Uncertain Linear Systems; 3.1 Norms, Balls and Volumes; 3.1.1 Vector Norms and Balls; 3.1.2 Matrix Norms and Balls; Hilbert-Schmidt Matrix Norms; Induced Matrix Norms; 3.1.3 Volumes; 3.2 Signals; 3.2.1 Deterministic Signals; 3.2.2 Stochastic Signals. 3.3 Linear Time-Invariant Systems3.4 Linear Matrix Inequalities; 3.5 Computing H2 and Hinfty Norms; 3.6 Modeling Uncertainty of Linear Systems; 3.7 Robust Stability of M-Delta Conﬁguration; 3.7.1 Dynamic Uncertainty and Stability Radii; 3.7.2 Structured Singular Value and µ Analysis; 3.7.3 Computation of Bounds on µ D; 3.7.4 Rank-One µ Problem and Kharitonov Theory; 3.8 Robustness Analysis with Parametric Uncertainty; Chapter 4: Linear Robust Control Design; 4.1 Hinfty Design; 4.1.1 Regular Hinfty Problem; 4.1.2 Alternative LMI Solution for Hinfty Design; 4.1.3 µ Synthesis. D-K Iteration for µ Synthesis4.2 H2 Design; 4.2.1 Linear Quadratic Regulator; 4.2.2 Quadratic Stabilizability and Guaranteed-Cost; 4.3 Robust LMIs; 4.4 Historical Notes and Discussion; Chapter 5: Limits of the Robustness Paradigm; 5.1 Computational Complexity; 5.1.1 Decidable and Undecidable Problems; 5.1.2 Time Complexity; 5.1.3 NP-Completeness and NP-Hardness; 5.1.4 Some NP-Hard Problems in Systems and Control; 5.2 Conservatism of Robustness Margin; 5.3 Discontinuity of Robustness Margin; Chapter 6: Probabilistic Methods for Uncertain Systems. 6.1 Performance Function for Uncertain Systems6.2 Good and Bad Sets; 6.3 Probabilistic Analysis of Uncertain Systems; 6.4 Distribution-Free Robustness; 6.5 Historical Notes on Probabilistic Methods; Chapter 7: Monte Carlo Methods; 7.1 Probability and Expected Value Estimation; 7.2 Monte Carlo Methods for Integration; 7.3 Monte Carlo Methods for Optimization; 7.4 Quasi-Monte Carlo Methods; 7.4.1 Discrepancy and Error Bounds for Integration; 7.4.2 One-Dimensional Low Discrepancy Sequences; 7.4.3 Low Discrepancy Sequences for n>1; 7.4.4 Dispersion and Point Sets for Optimization. Chapter 8: Probability Inequalities. Uncertainty and Robustness -- Probability and Robustness of Uncertain Systems -- Elements of Probability Theory -- Uncertain Linear Systems and Robustness -- Linear Robust Control Design -- Some Limits of the Robustness Paradigm -- Probabilistic Methods for Robustness -- Monte Carlo Methods -- Randomized Algorithms in Systems and Control -- Probability Inequalities -- Statistical Learning Theory and Control Design -- Sequential Algorithms for Probabilistic Robust Design -- Sequential Algorithms for LPV Systems -- Scenario Approach for Probabilistic Robust Design -- Random Number and Variate Generation -- Statistical Theory of Radial Random Vectors -- Vector Randomization Methods -- Statistical Theory of Radial Random Matrices -- Matrix Randomization Methods -- Applications of Randomized Algorithms.
Titelhinweis	Buchausg. u.d.T.ISBN: 978-1-447-14609-4
ISBN	ISBN 978-1-4471-4610-0
Klassifikation	TJFM
	TEC004000
	*93-02
	93E03
	93B35
	93B36
	60B20
	60G35
	62F10
	62H30
	68W20
	629.8
	TJ212-225
Kurzbeschreibung	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. VidyasagarThe 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.
SWB-Titel-Idn	375375694
Signatur	Springer E-Book
Bemerkungen	Elektronischer Volltext - Campuslizenz
Elektronische Adresse	$uhttp://dx.doi.org/10.1007/978-1-4471-4610-0
Internetseite / Link	Volltext
Siehe auch	Volltext
Siehe auch	Cover
Siehe auch	Inhaltstext

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