relation: http://eprints.imtlucca.it/439/
title: Model predictive control tuning by controller matching
creator: Di Cairano, Stefano
creator: Bemporad, Alberto
subject: QA75 Electronic computers. Computer science
description: The effectiveness of model predictive control (MPC) in dealing with input and state constraints during transient operations is well known. However, in contrast with several linear control techniques, closed-loop frequency-domain properties such as sensitivities and robustness to small perturbations are usually not taken into account in the MPC design. This technical note considers the problem of tuning an MPC controller that behaves as a given linear controller when the constraints are not active (e.g., for perturbations around the equilibrium that remain within the given input and state bounds), therefore inheriting the small-signal properties of the linear control design, and that still optimally deals with constraints during transients. We provide two methods for selecting the MPC weight matrices so that the resulting MPC controller behaves as the given linear controller, therefore solving the posed inverse problem of controller matching, and is globally asymptotically stable.
publisher: IEEE 
date: 2010
type: Article
type: PeerReviewed
identifier:   Di Cairano, Stefano and Bemporad, Alberto  Model predictive control tuning by controller matching.  IEEE Transactions on Automatic Control , 55 (1).  pp. 185-190.  ISSN 0018-9286      (2010)  
relation: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5342457&isnumber=5379206
relation: 10.1109/TAC.2009.2033838