In [1], a novel best-mean approach to robust analysis and control over uncertain-parameters boxes was presented. This paper extends the results of [1] to convex uncertainty polytopes of arbitrary shape and arbitrary number of vertices, without an underlying parameters model. The paper addresses robust, polytopic, probabilistic H∞ analysis of linear systems and focuses on the performance distrib...

We present in this paper a general decomposition framework to solve exactly adjustable robust linear optimization problems subject to polytope uncertainty. Our approach is based on replacing the polytope by the set of its extreme points and generating the extreme points on the fly within row generation or column-and-row generation algorithms. The novelty of our approach lies in formulating the ...

In this work we present the uncertainty transformation and its properties and apply these in a frequently encountered problem in computer vision: the alignment problem. A convex polytope is used to captivate the uncertainty of transformations that arises when the position of image points is not exactly known. The uncertainty polytope is used to compute the correspondences between points on the ...

This paper addresses a linear finite-horizon robust optimal H∞ analysis problem, where the system matrices and the system initial conditions (ICs, x0) are concurrently uncertain, both in a polytopic manner. Current finite-horizon H∞ analysis practice assumes x0 ∈R ; that is, allows infinite ICs uncertainty. This assumption is unrealistically conservative, and incompatible with the prevalent rob...

Control systems with digital communication between sensors, controllers and actuators are called as Networked Control Systems (NCSs). In general, NCSs encounter with some problems such as packet dropouts and network induced delays. When plant uncertainty is added to the aforementioned problems, the design of the robust controller that is able to guarantee the stability, becomes more complex. In...

In this paper‎, ‎a synthesis method based on robust model predictive control is developed for compensation of uncertain time-delays in networked control systems with bounded disturbance‎. ‎The proposed method uses linear matrix inequalities and uncertainty polytope to model uncertain time-delays and system disturbances‎. ‎The continuous system with time-delay is discretized using uncertainty po...

We solve a linear robust problem with mixed-integer first-stage variables and continuous second stage variables. We consider column wise uncertainty. We first focus on a problem with right hand-side uncertainty which satisfies a "full recourse property" and a specific definition of the uncertainty. We propose a solution based on a generation constraint algorithm. Then we give several generaliza...

Many applications in image processing require the fitting of transformation models to sets of points. We propose a technique that optimizes the model fitting process by employing parametric consistency as an additional constraint. The technique is used to find affine transformations between data points. The uncertainty about the exact location of a data point is modelled by defining a convex un...

We survey the problem of deciding the stability or stabilizability of uncertain linear systems whose region of uncertainty is a polytope. This natural setting has applications in many fields of applied science, from Control Theory to Systems Engineering to Biology. We focus on the algorithmic decidability of this property when one is given a particular polytope. This setting gives rise to sever...