This paper is concerned with a robust observer design for linear time-delay systems via linear matrix inequality approach. The proposed method not only guarantees the stability of the proposed observer, but also reduces the effects of different unstructured uncertainties on the estimated error.

In this paper, we propose a design method of a static anti-windup compensator that guarantees closed-loop stability and optimizes performance criterion proposed by Teel and Kapoor. Further, we extend the method to the robust performance problem. We provide design procedures based on linear matrix inequality (LMI) representation.

Based on linear matrix inequality (LMI) technique. a sliding mode control approach is presented for a class of uncertain time-delay systems in the delayindependent and delay-dependent case. The corresponding sufficient conditions for the existence of sliding mode are proposed. Different from the reported results. the conclusion presented in this paper is only relating to the original system par...

A linear matrix inequality (LMI) is a condition stating that a symmetric matrix whose entries are affine-linear combinations of variable,; is positive semidefinite. :dotiv11ted by the fact that diagonal LMIs define polyhedra, the solution set of an LMI is called a spectrahedron. Linear images of spectrahedra are called semidefinitely representable sets. Part of the interest in spectrahedra and ...

for $a,bin m_{nm},$ we say that $a$ is left matrix majorized (resp. left matrix submajorized) by $b$ and write $aprec_{ell}b$ (resp. $aprec_{ell s}b$), if $a=rb$ for some $ntimes n$ row stochastic (resp. row substochastic) matrix $r.$ moreover, we define the relation $sim_{ell s} $ on $m_{nm}$ as follows: $asim_{ell s} b$ if $aprec_{ell s} bprec_{ell s} a.$ this paper characterizes all linear p...

for vectors x, y ∈ rn, it is said that x is left matrix majorizedby y if for some row stochastic matrix r; x = ry. the relationx ∼` y, is defined as follows: x ∼` y if and only if x is leftmatrix majorized by y and y is left matrix majorized by x. alinear operator t : rp → rn is said to be a linear preserver ofa given relation ≺ if x ≺ y on rp implies that t x ≺ ty onrn. the linear preservers o...

Abstract A basic framework for exploiting sparsity via positive semidefinite matrix completion is presented for an optimization problem with linear and nonlinear matrix inequalities. The sparsity, characterized with a chordal graph structure, can be detected in the variable matrix or in a linear or nonlinear matrix-inequality constraint of the problem. We classify the sparsity in two types, the...

Even taking into account the sobering lessons learned from the recession, affordable homeownership remains the most important wealth-building opportunity for most LMI families.1 A major long-term macroeconomic benefit will be achieved if our mortgage finance system effectively opens access to those populations that will make up the largest portion of the growth of the mortgage market in the com...

Schoute (1911) introduced the permutahedron on an n-element set N= { 1, . . . , n} as follows. With any permutation n of N we associate an incidence vector x(71) = (n(I), *.., n(n)) E IR”. The permutahedron is the polytope Perm(N) = conv{x(rr): rr is a permutation of N}. Independently, several authors (cf., e.g., Rado [4], Balas [l], Gaiha and Gupta [2], Young [6]) studied the permutahedron and...