%P 14-20
%T Simple and Certifiable Quadratic Programming Algorithms for Embedded Linear Model Predictive Control
%R 10.3182/20120823-5-NL-3013.00009
%L eprints1486
%X In this paper we review a dual fast gradient-projection approach to solving quadratic programming (QP) problems recently proposed in [Patrinos and Bemporad, 2012] that is particularly useful for embedded model predictive control (MPC) of linear systems subject to linear constraints on inputs and states. We show that the method has a computational effort aligned with several other existing QP solvers typically used in MPC, and in addition it is extremely easy to code, requires only basic and easily parallelizable arithmetic operations, and a number of iterations to reach a given accuracy in terms of optimality and feasibility of the primal solution that can be estimated quite tightly by solving an off-line mixed-integer linear programming problem. This research was largely motivated by ongoing research activities on embedded MPC for aerospace systems carried out in collaboration with the European Space Agency.
%I IFAC
%K Dedicated Optimization Solvers for Model Predictive Control; Real-Time Implementation of Model Predictive Control
%A Alberto Bemporad
%A Panagiotis Patrinos
%D 2012
%B 4th IFAC Nonlinear Model Predictive Control Conference
%O 4th IFAC Conference on Nonlinear Model Predictive Control 2012 (NMPC'12), Netherlands, August 23 - 27, 2012
%V 4