This paper presents a parametrization of a feed-forward control based on structures of subspaces for a non-interacting regulation. With advances in technological development, robotics is increasingly being used in many industrial sectors, including medical applications (e. g., micromanipulation of internal tissues or laparoscopy). Typical problems in robotics and general mechanisms may be mathe...

The version R14SP1 of function hinfsyn (full-order H∞ optimal controller synthesis) of the Robust Control System Toolbox for Matlab is benchmarked on the extensive set of linear models of the COMPleib database. The main conclusion is that sometimes the achieved numerical results are surprising, if not disappointing. This illustrates the difficulty of designing efficient and numerically reliable...

Abstract: The robust control problem for linear systems with parameter uncertainties and time-varying delays is examined. By using an appropriate uncertainty description, a linear state feedback control law is found ensuring the closed-loop system’s stability and a performance measure, in terms of the guaranteed cost. An LMI objective minimization approach allows to determine the ”optimal” choi...

The discretization of control functions by piecewise constant and piecewise linear functions is considered for linear-quadratic elliptic optimal control problems. Error estimates are derived for the optimal controls. Special emphasis is laid on the case of boundary control and convex polygonal domains.

The work examines the problem of model predictive control for uncertain linear dynamic systems with intervally assigned parameters and multiplicative noise inputs. We use the model predictive control techniques based on linear matrix inequalities to get an optimal robust control strategy that provides the system with stability in the mean-square sense. The results are illustrated by an numerica...

In this paper we consider a linear system represented by a coupling graph between subsystems and propose a distributed control scheme capable to guarantee asymptotic stability and satisfaction of constraints on system inputs and states. Most importantly, as in [1, 2] our design procedure enables plug-and-play (PnP) operations, meaning that (i) the addition or removal of subsystems triggers the ...

In this paper, we introduce a robust state feedback controller design using Linear Matrix Inequalities (LMIs) and guaranteed cost approach for Takagi-Sugeno fuzzy systems. The purpose on this work is to establish a systematic method to design controllers for a class of uncertain linear and non linear systems. Our approach utilizes a certain type of fuzzy systems that are based on Takagi-Sugeno ...