Homogeneous polynomial forms for robustness analysis of uncertain systems

Cover of: Homogeneous polynomial forms for robustness analysis of uncertain systems |

Published by Springer in New York .

Written in English

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Subjects:

  • Robust control

Edition Notes

Includes bibliographical references (p. [183]-190) and index.

Book details

StatementGraziano Chesi ... [et al.].
SeriesLecture notes in control and information sciences -- 390
ContributionsChesi, Graziano.
Classifications
LC ClassificationsTJ217.2 .H66 2009
The Physical Object
Paginationxvi, 197 p. :
Number of Pages197
ID Numbers
Open LibraryOL24109465M
ISBN 109781848827806
LC Control Number2009933685

Download Homogeneous polynomial forms for robustness analysis of uncertain systems

Request PDF | Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems | Positive Forms.- Positivity Gap.- Robustness with Time-varying Uncertainty.

"This book presents a number of techniques for robustness analysis of uncertain systems. The theoretical basis for their development is derived from the application of convex optimization tools to problems involving positivity of homogeneous polynomial forms.

Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems. Authors: Chesi, G., Garulli, A., Tesi, A., Vicino, A. Free Preview. About this book Keywords Control Engineering Hilbert’s 17th Problem Robust Analysis Robust Control SOS Polynomials Time-invariant Uncertainty Time-varying Uncertainty Uncertain Systems algorithms optimization.

Homogeneous polynomial forms for robustness analysis of uncertain systems. Responsibility Graziano Chesi [and others]. Imprint Robustness with Time-varying Uncertainty.- Robustness with Time-invariant Uncertainty.- Robustness with Bounded-rate Time-varying Uncertainty.- Distance Problems with Applications to Robust Control.

Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems. several robustness problems are presented by exploiting classical results and providing new insights on the theory of homogeneous polynomial forms.

In particular, a general framework is introduced for dealing with positivity of forms via the solution of linear Author: G Chesi. A review of the book \Homogeneous polynomial forms for robustness analysis of uncertain systems" by Graziano Chesi, Andrea Garulli, Alberto Tesi and Antonio Vicino.

Lecture Notes in Control and Information Sciences, vol. Springer, Berlin, The book describes convex optimization techniques to deal with stability and performance eval. Chesi G., Garulli A., Tesi A., Vicino A.

() Positive Forms. In: Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems. Lecture Notes in Control and Information Sciences, vol Kup książkę Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems (Graziano Chesi, Andrea Garulli, Alberto Tesi, Antonio Vicino) za jedyne zł u sprzedawcy godnego zaufania.

Zajrzyj do środka, czytaj recenzje innych czytelników, pozwól nam polecić Ci podobne tytuły z naszej ponad milionowej kolekcji. Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems.

Springer, Other Series: Lecture Notes in Control and Information Sciences Volume: Pages: ISBN: Abstract This book presents a number of techniques for robustness analysis of uncertain systems. In this note, the use of homogeneous polynomial Lyapunov functions (HPLFs) for robust stability analysis of linear systems subject to time-varying parametric uncertainty, affecting rationally the.

Abstract. This book presents a number of techniques for robustness analysis of uncertain systems. The theoretical basis for their development is derived from the application of convex optimization tools to problems involving positivity of homogeneous polynomial : G.

CHESI, A. GARULLI, A. TESI and A. VICINO. He is the Founder and Chair of the Technical Committee on Systems with Uncertainty of the IEEE Control Systems Society.

He is the author of the book “Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems” (Springer, ) and editor of the book “Visual Servoing via Advanced Numerical Methods” (Springer, ).Cited by: I co-authored the book: Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems by Graziano Chesi, Alberto Tesi, Andrea Garulli and Antonio Vicino Springer, Lecture Notes in Control and Information Sciences, Vol.ISBN: I co-authored the toolbox: LFR_RAI: Robustness Analysis of LFR models.

The problem addressed in this paper is the construction of homogeneous polynomial Lyapunov functions (HPLFs) for linear systems with time-varying structured uncertainties. A sufficient condition for the existence of an HPLF of given degree is formulated in terms of a linear matrix inequalities (LMI) feasibility by: He is the Founder and Chair of the Technical Committee on Systems with Uncertainty of the IEEE Control Systems Society.

He is author of the book "Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems" (Springer, ) and editor of the book "Visual Servoing via Advanced Numerical Methods" (Springer, ).Brand: Springer-Verlag London.

Download Robustness in Identification and Control by Andrea Garulli Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems ISBN Robustness Analysis and Synthesis for Nonlinear Uncertain Systems Wei-Min Lu, Member, IEEE, and John C.

Doyle Abstract— A state-space characterization of robustness analysis and synthesis for nonlinear uncertain systems is proposed. The robustness of a class of nonlinear systems subject to L 2-boundedCited by: Home Resume Publications: Books and Special Issues [B4] A.

Losi, P. Mancarella and A. Vicino, Editors, Integration of Demand Response into the Electricity Chain: Challenges, Opportunities and Smart Grid Solutions, Iste-Wiley, Electrical Engineering Series, [B3] G.

Chesi, A. Garulli, A. Tesi and A. Vicino, Homogeneous Polynomial Forms for Robustness Analysis of Uncertain. Chesi is the Founder and the Chair of the Technical Committee on Systems with Uncertainty of the IEEE Control Systems Society.

He is author of the book "Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems" (Springer, ), editor of the book "Visual Servoing via Advanced Numerical Methods" (Springer, ), and author of. He is co-author of more than technical publications in journals and conference proceedings, and of the book "Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems", Springer Keywords: Uncertain HMP, M-matrices, Polya’s theorem, dynamic polytopic systems.

Introduction Stability analysis of linear systems subjected to structured real parametric uncertainty, belonging to a compact vector set, has been recognised as a key issue in the analysis of control systems.

Usually, a quadratic in the state candidate for a. He is co-author of more than technical publications in journals and conference proceedings, and of the book "Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems", Springer His present research interests include system identification, robust estimation and filtering, optimization techniques for robust control.

In this paper, robust stability for linear systems with several uncertain (complex and/or real) scalar parameters is studied. A countable family of conditions sufficient for robust stability is given, in terms of solvability of some simple linear matrix inequalities (LMIs).

These conditions are of increasing precision, and it is shown conversely that robust stability implies solvability of Cited by: Advanced Topics in Control and Estimation of State-Multiplicative Noisy Systems begins with an introduction and extensive literature survey.

The text proceeds to cover the field of H time-delay linear systems where the issues of stability and L2 gain are presented and solved for nominal and uncertain stochastic systems, via the input-output approach. ROBUSTNESS ANALYSIS OF UNCERTAIN LINEAR SYSTEMS AND ROBUST STABILIZATION OF UNCERTAIN DELAYED SYSTEMS By VARADHARAJAN R.

BASKER May Chairman: Major Department: Dr. Oscar D. Crisalle Chemical Engineering This dissertation focuses on two main aspects. One, developing new tools for the robustness analysis of uncertain linear systems. Review of the book "Homogeneous polynomial forms for robustness analysis of uncertain systems" by Graziano Chesi, Andrea Garulli, Alberto Tesi, Antonio Vicino, Springer, AMS Math Reviews MR (g), January () Homogeneous Polynomial Forms for Simultaneous Stabilizability of Families of Linear Control Systems: A Tensor Product Approach.

IEEE Transactions on Automatic Control() A direct/functional redundancy scheme for Cited by: The stability of an equilibrium point of a nonlinear dynamical system is typically determined using Lyapunov theory.

This requires the construction of an energy-like function, termed a Lyapunov function, which satisfies certain positivity conditions. Unlike linear dynamical systems, there is no algorithmic method for constructing Lyapunov functions for general nonlinear by: G.

Chesi, A. Garulli, A. Tesi and A. Vicino, "Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems,", Lecture Notes in Control Cited by: Robust Optimal Control using Polynomial Chaos and Adjoints for Systems with Uncertain Inputs Sriram∗ General Electric Research Center, Niskayuna, NY,U.S.A.

Antony Jameson† Stanford University, Stanford, CA,U.S.A. The objective of this note is to show how one can combine Polynomial Chaos Expansions. This book presents a number of techniques for robustness analysis of uncertain systems.

In it, convex relaxations for several robustness problems are derived by exploiting and providing new results on the theory of homogenous polynomial forms. Branch and bound algorithm for the robustness analysis of uncertain systems.

Ravanbod D. Noll P. Apkarian Universit e de Toulouse, Institut de Math ematiques, Toulouse, France [email protected], @ ONERA, Toulouse, France [email protected] Robustness Analysis with Real Parametric Uncertainty Motivating Example: DC Electric Motor with Uncertain Parameters For the sake of illustrative purposes, an example of a DC electric motor is formulated and carried out throughout this chapter in various forms.

Consider the system represented in Figure of an. polynomial chaos theory. The polynomial chaos method has been shown to be considerably more efficient than Monte Carlo in the simulation of systems with a small number of uncertain parameters. In the new approach presented in this paper, the maximum likelihood estimates are obtained by minimizing a.

Mathematical Systems Theory I (subtitled "Modelling, State Space Analysis, Stability and Robustness") provides a detailed and rigorous mathematical development of finite-dimensional, time-invariant linear systems. One way to think of this book is to see it as the rigorous mathematical foundation underlying the "linear systems" course common to many.

Abstract: A new methodology for a robust analysis of uncertain nonlinear dynamic systems is presented in this paper. The originality of the method proposed lies in the combination of the centre manifold theory with the polynomial chaos approach. The first one is known to be a powerful tool for model reduction of nonlinear.

Polynomial Chaos-Based Robust Design of Systems with Probabilistic Uncertainties Dongying E. Shen and Richard D. Braatz Dept. of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA DOI /aic Published online J in Wiley Online Library ().

estimates on volumes of homogeneous polynomial spaces 5 In particular, for every homogeneous polynomial f(X)∈ L[X], the restriction of vf to P n (K)is uniformly approximated by formulae with parameters in K, i.e., vf↾Author: Itaï Ben Yaacov.

the study of complex systems, robustness analysis is a method of quantifying the effect of uncertainty at the level of the parameters on the final predictions; in statistics, robust estimators are those unaffected byCited by: 5.

the robust counterpart of the uncertain LP problem (1), and we call a vector x solving (3) a robust solution of the uncertain problem. No underlying stochastic model of the data is assumed to be known (or even to exist), although such knowledge may be of use to obtain reasonable uncertainty sets (see Section 4).4Note also that robustness analysis is used in other areas of science with yet a di erent meaning: e.g, in the study of complex systems, robustness analysis is a method of quantifying the e ect of uncertainty at the level of the parameters on the nal predictions; in statistics, robust estimators are those una ected by outliers in the by: 5.$\begingroup$ A nice reference on this subject is Morris Marden's book The Geometry of the Zeros of a Polynomial in a Complex Variable.

$\endgroup$ – Mariano Suárez-Álvarez Sep 9 '11 at $\begingroup$ I didn't know that book: thanks for the reference, Mariano. $\endgroup$ – Georges Elencwajg Sep 9 '11 at

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