%0 Book Section
%A Rubagotti, Matteo
%A Patrinos, Panagiotis
%A Bemporad, Alberto
%B Proceedings of European Control Conference 
%D 2013
%F eprints:2176
%I IEEE
%K Closed loop systems, Optimal control, Optimization, Real-time systems, Stability analysis, Standards, Vectors
%P 3065-3070
%T Stabilizing embedded MPC with computational complexity guarantees
%U http://eprints.imtlucca.it/2176/
%X This paper describes a model predictive control (MPC) approach for discrete-time linear systems with hard constraints on control and state variables. The finite-horizon optimal control problem is formulated as a quadratic program (QP), and solved using a recently proposed dual fast gradient-projection method. More precisely, in a finite number of iterations of the mentioned optimization algorithm, a solution with bounded levels of infeasibility and suboptimality is determined for an alternative problem. This solution is shown to be a feasible suboptimal solution for the original problem, leading to exponential stability of the closed-loop system. The proposed strategy is particularly useful in embedded control applications, for which real-time constraints and limited computing resources can impose tight bounds on the possible number of iterations that can be performed within the scheduled sampling time.
%Z 2013 European Control Conference (ECC)  July 17-19, 2013, Zürich, Switzerland.