@incollection{eprints537,
           pages = {1575--1680},
         journal = {American Control Conference},
       publisher = {IEEE},
         address = {14th-16th June 2006 },
            year = {2006},
       booktitle = {American Control Conference},
           title = {Feedback min-max model predictive control based on a quadratic cost function},
          author = {David Mu{\~n}oz de la Pe{\~n}a and Teodoro Alamo and Alberto Bemporad and Eduardo F. Camacho},
        keywords = {computational complexity; feedback min-max model predictive control; linear systems; optimization algorithms; cost function; quadruple-tank process; recourse horizon; robust control; feedback; linear systems; minimax techniques; predictive control; robust control},
        abstract = {Feedback min-max model predictive control based on a quadratic cost function is addressed in this paper. The main contribution is an algorithm for solving the min-max quadratic MPC problem with an arbitrary degree of approximation. The paper also introduces the "recourse horizon", which allows one to obtain a trade-off between computational complexity and performance of the control law. The results are illustrated by means of a simulation of a quadruple-tank process},
             url = {http://eprints.imtlucca.it/537/}
}