TY - CHAP SN - 978-3-033-03962-9 PB - IEEE EP - 3070 Y1 - 2013/07// SP - 3065 T2 - Proceedings of European Control Conference A1 - Rubagotti, Matteo A1 - Patrinos, Panagiotis A1 - Bemporad, Alberto AV - none ID - eprints2176 TI - Stabilizing embedded MPC with computational complexity guarantees UR - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6669435&isnumber=6669080 N1 - 2013 European Control Conference (ECC) July 17-19, 2013, Zürich, Switzerland. N2 - 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. KW - Closed loop systems KW - Optimal control KW - Optimization KW - Real-time systems KW - Stability analysis KW - Standards KW - Vectors ER -