Eigenvalue and eigenvector derivatives with respect to system design variables and their
applications have been and continue to be one of the core issues in the design, control and …

Many questions of robust control analysis and synthesis fundamentally involve nonsmooth
sets and functions, and their variational properties. Central examples include distances to …

This work concerns the global minimization of a prescribed eigenvalue or a weighted sum of
prescribed eigenvalues of a Hermitian matrix-valued function depending on its parameters …

In this thesis, we consider polynomial eigenvalue problems. We extend results on
eigenvalue and eigenvector condition numbers of matrix polynomials to condition numbers …

This study presents an optimal control framework that designs an optimal trajectory while
additionally accounting for the stability of a path-deviation error controller that is dependent …

We consider the distance from a (square or rectangular) matrix pencil to the nearest matrix
pencil in 2-norm that has a set of specified eigenvalues. We derive a singular value …

Let A be a matrix with distinct eigenvalues and let w (A) be the distance from A to the set of
defective matrices (using either the 2-norm or the Frobenius norm). Define Λϵ, the ϵ …

We develop a general framework for perturbation analysis of matrix polynomials. More
specifically, we show that the normed linear space Lm (Cn× n) of n-by-n matrix polynomials …

In the first part of this paper (Sections 2–4), the main concern is with the boundary of the
pseudospectrum of a matrix polynomial and, particularly, with smoothness properties of the …

The Wilkinson distance of a matrix A is the two-norm of the smallest perturbation E so that A+
E has a multiple eigenvalue. Malyshev derived a singular value optimization …