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The complex structured singular value

TLDR
A tutorial introduction to the complex structured singular value (μ) is presented, with an emphasis on the mathematical aspects of μ.
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This article is published in Automatica.The article was published on 1993-01-01 and is currently open access. It has received 1515 citations till now. The article focuses on the topics: Linear system & Linear fractional transformation.

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Citations
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Book

Linear Matrix Inequalities in System and Control Theory

Edwin E. Yaz
TL;DR: In this paper, the authors present a brief history of LMIs in control theory and discuss some of the standard problems involved in LMIs, such as linear matrix inequalities, linear differential inequalities, and matrix problems with analytic solutions.
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Stability of Time-Delay Systems

TL;DR: Preface, Notations 1.Introduction to Time-Delay Systems I.Robust Stability Analysis II.Input-output stability A.LMI and Quadratic Integral Inequalities Bibliography Index
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Essentials of Robust Control

TL;DR: In this article, the authors introduce linear algebraic Riccati Equations and linear systems with Ha spaces and balance model reduction, and Ha Loop Shaping, and Controller Reduction.
Journal ArticleDOI

Robust constrained model predictive control using linear matrix inequalities

TL;DR: This paper presents a new approach for robust MPC synthesis that allows explicit incorporation of the description of plant uncertainty in the problem formulation, and shows that the feasible receding horizon state-feedback control design robustly stabilizes the set of uncertain plants.
DissertationDOI

Structured semidefinite programs and semialgebraic geometry methods in robustness and optimization

TL;DR: In this paper, the authors introduce a specific class of linear matrix inequalities (LMI) whose optimal solution can be characterized exactly, i.e., the optimal value equals the spectral radius of the operator.
References
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Optimization by Vector Space Methods

TL;DR: This book shows engineers how to use optimization theory to solve complex problems with a minimum of mathematics and unifies the large field of optimization with a few geometric principles.
Journal ArticleDOI

State-space solutions to standard H/sub 2/ and H/sub infinity / control problems

TL;DR: In this article, simple state-space formulas are derived for all controllers solving the following standard H/sub infinity / problem: for a given number gamma > 0, find all controllers such that the H/ sub infinity / norm of the closed-loop transfer function is (strictly) less than gamma.
Book

Feedback Systems: Input-output Properties

TL;DR: In this paper, the Bellman-Gronwall Lemma has been applied to the small gain theorem in the context of linear systems and convolutional neural networks, and it has been shown that it can be applied to linear systems.
Journal ArticleDOI

Multivariable feedback design: Concepts for a classical/modern synthesis

TL;DR: This paper presents a practical design perspective on multivariable feedback control problems and generalizes known single-input, single-output (SISO) statements and constraints of the design problem to multiinput, multioutput (MIMO) cases.

Analysis of feedback systems with structured uncertainties

TL;DR: In this article, a general approach for analysing linear systems with structured uncertainty based on a new generalised spectral theory for matrices is introduced, which naturally extend techniques based on singular values and eliminate their most serious difficulties.
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A tutorial introduction to the complex structured singular value ( μ ) is presented, with an emphasis on the mathematical aspects of μ. Several tests for robust stability and performance with computable bounds for transfer functions and their state-space realizations are compared, and a simple synthesis problem is studied. Subtitle: A tutorial introduction to the complex structured singular value ( μ ) is presented, with an emphasis on computable bounds and robust stability and performance tests for transfer functions and their state-space realizations. 

when verifying convergence of the algorithm, it is necessary to begin checking the convergence of the vectors only after the β̃k and β̂k values are nearly equal. 

The closed-loop system is said to be:• well-posed if det (I − P11(∞)∆1) 6= 0. This is the necessary and sufficient condition that all closed-loop transfer functions in Figure 5.1 be proper.• stable if all closed-loop transfer functions in Figure 5.1 are analytic in the closed righthalf-plane. 

Choose α > 0 small enough so that the three conditionsI − αZ > 0 Σ22 − σ21I + αL < 0σ21 (V ∗ZV − U∗ZU)− αT (Σ22 − σ21I + αL )−1 T ∗ < 0are satisfied. 

The authors have shown that quadratic stability with respect to such a parameter can be ascertained by determining if the convex set{X =[P 0 0 D2] : P ∈ Cn×n, D2 ∈ Cm×m, X = X∗ > 0,M∗XM −X < 0 }is nonempty. 

The algorithm resembles a mixture of power methods for eigenvalues and singular values, which is not surprising, since the structured singular value can be viewed as a generalization of both. 

6= 0. This is the necessary and sufficient condition that all closed-loop transfer functions in Figure 5.1 be proper.• stable if all closed-loop transfer functions in Figure 5.1 are analytic in the closed righthalf-plane. 

Motivated by connections with stability of systems, which will be explored in detail in the sequel, the authors call this constant matrix feedback system “unstable”.