This paper develops a new framework to analyze and design iterative optimization
algorithms built on the notion of integral quadratic constraints (IQCs) from robust control …

We study the optimal design of graph filters (GFs) to implement arbitrary linear
transformations between graph signals. GFs can be represented by matrix polynomials of …

Convex optimization problems arise frequently in many different fields. This book provides a
comprehensive introduction to the subject, and shows in detail how such problems can be …

The basic topic of this book is solving problems from system and control theory using convex
optimization. We show that a wide variety of problems arising in system and control theory …

In semidefinite programming, one minimizes a linear function subject to the constraint that
an affine combination of symmetric matrices is positive semidefinite. Such a constraint is …

The LMI control toolbox Page 1 PKu"gsofths33rd Conferem on Deddon and control Lake
&remvi. FL- December 1894 TP-1 5:20 Tlie LMI Coiitrol Toolbox Puscal Guhiriet t Arkudii …

The continuous‐and discrete‐time H∞ control problems are solved via elementary
manipulations on linear matrix inequalities (LMI). Two interesting new features emerge …

We consider the problem of finding a linear iteration that yields distributed averaging
consensus over a network, ie, that asymptotically computes the average of some initial …

The primary disadvantage of current design techniques for model predictive control (MPC) is
their inability to deal explicitly with plant model uncertainty. In this paper, we present a new …

This paper addresses the design of state-or output-feedback H/sub/spl infin//controllers that
satisfy additional constraints on the closed-loop pole location. Sufficient conditions for …