Robust control to parametric uncertainties in smart structures using linear matrix inequalities

Finite Horizon Robust Model Predictive Control Using Linear Matrix Inequalities

In this paper, we develop a finite horizon model predictive control algorithm which is robust to model uncertainties. A moving average system matrix is constructed to capture model uncertainties and facilitate future output predictions. The paper is focused on step tracking control. Using linear matrix inequality techniques, the design is converted into a semi-definite optimization problem. Clo...

Robust constrained model predictive control using linear matrix inequalities,

The primary disadvantage of current design techriiques for xriodel predictive control (MPC) is their inability to deal explicitly with plant model uncertainty. In this paper, we present a new approacli for robust MPC synthesis which allows explicit irlcorporation of the description of pla,nt uricertainty in the problem formulation. The uncertainty is expressed both in the time domain and the fr...

Linear Matrix Inequalities in Robust Control A Brief Survey

Control system models must often explicitly incorporate in them “uncertainties”, which model a number of factors, including: dynamics that are neglected to make the model tractable, as with large scale structures; nonlinearities that are either hard to model or too complicated; and parameters that are not known exactly, either because they are hard to measure or because of varying manufacturing...

Robust Constrained Model Predictive Control by Linear Matrix Inequalities

Further Results on “Robust MPC Using Linear Matrix Inequalities”

This paper presents a novel method for designing the terminal cost and the auxiliary control law (ACL) for robust MPC of uncertain linear systems, such that ISS is a priori guaranteed for the closed-loop system. The method is based on the solution of a set of LMIs. An explicit relation is established between the proposed method and H∞ control design. This relation shows that the LMI-based optim...