Logo eprints

Simple and Certifiable Quadratic Programming Algorithms for Embedded Linear Model Predictive Control

Bemporad, Alberto and Patrinos, Panagiotis Simple and Certifiable Quadratic Programming Algorithms for Embedded Linear Model Predictive Control. In: 4th IFAC Nonlinear Model Predictive Control Conference. IFAC, pp. 14-20. ISBN 978-3-902823-07-6 (2012)

Full text not available from this repository.

Abstract

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.

Item Type: Book Section
Identification Number: https://doi.org/10.3182/20120823-5-NL-3013.00009
Additional Information: 4th IFAC Conference on Nonlinear Model Predictive Control 2012 (NMPC'12), Netherlands, August 23 - 27, 2012
Uncontrolled Keywords: Dedicated Optimization Solvers for Model Predictive Control; Real-Time Implementation of Model Predictive Control
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TJ Mechanical engineering and machinery
Research Area: Computer Science and Applications
Depositing User: Ms T. Iannizzi
Date Deposited: 20 Feb 2013 10:41
Last Modified: 20 Feb 2013 10:41
URI: http://eprints.imtlucca.it/id/eprint/1486

Actions (login required)

Edit Item Edit Item