Probabilistic and Randomized Methods for Design under Uncertainty / Edition 1

by Giuseppe Calafiore, Fabrizio Dabbene

Overview

Probabilistic and Randomized Methods for Design under Uncertainty is a collection of contributions from the world’s leading experts in a fast-emerging branch of control engineering and operations research. The book will be bought by university researchers and lecturers along with graduate students in control engineering and operational research.

Product Details

ISBN-13:	9781846280948
Publisher:	Springer London
Publication date:	01/13/2006
Edition description:	2006
Pages:	458
Product dimensions:	6.10(w) x 9.25(h) x 0.04(d)

About the Author

Drs. Giuseppe Calafiore and Fabrizio Dabbene work at the Politecnico di Torino, Italy, where Dr. Calafiore is an associate professor and Dr. Dabbene is a research fellow. Dr. Calafiore is an associate editor of IEEE Transactions on Systems, Man and Cybernetics and Dr. Dabbene is an associate editor of the conference editorial board of the IEEE Control Systems Society. Dr. Calafiore has published 60+ journal papers and both editors are co-authors of Randomized Algorithms for Analysis and Control of Uncertain Systems (Tempo, Calafiore and Dabbene, Springer-Verlag London, 2004).

In this edited work, Calafiore and Dabbene have brought together contributions from the world's leading experts in randomised methods as applied to robust design from both control and optimisation angles. The selection of authors is fully international and includes 15 from the United States.

Table of Contents

Part I Chance-Constrained and Shastic Optimization Scenario Approximations of Chance Constraints Optimization Models with Probabilistic Constraints Theoretical Framework for Comparing Several Shastic Optimization Approaches Optimization of Risk Measures Part II Robust Optimization and Random Sampling Sampled Convex Programs and Probabilistically Robust Design Tetris: A Study of Randomized Constraint Sampling Near Optimal Solutions to Least-Squares Problems with Shastic Uncertainty The Randomized Ellipsoid Algorithm for Constrained Robust Least Squares Problems Randomized Algorithms for Semi-Infnite Programming Problems Part III Probabilistic Methods in Identifcation and Control A Learning Theory Approach to System Identifcation and Shastic Adaptive Control Probabilistic Design of a Robust Controller Using a Parameter-Dependent Lyapunov Function Probabilistic Robust Controller Design: Probable Near Minimax Value and Randomized Algorithms Sampling Random Transfer Functions Nonlinear Systems Stability via Random and Quasi-Random Methods Probabilistic Control of Nonlinear Uncertain Systems Fast Randomized Algorithms for Probabilistic Robustness Analysis References