An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control

By Panagiotis Patrinos, Alberto Bemporad. IEEE Transactions on Automatic Control, 2014

296 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

ECOS: An SOCP solver for embedded systems (2013, unknown): “[16], [17]), all existing implementations are limited to QPs, including efficient primal-barrier methods for model predictive control [18], primal-dual interior-point methods by C code-generation for small QPs with micro to millisecond solution times (CVXGEN, [13]) and active set strategies with goo”
Distributed dual gradient methods and error bound conditions (2014, methodology): “For the special case of QPs problems, dual gradient algorithm were also analyzed in [5, 19, 20].”
Reference and command governors for systems with constraints: A survey on theory and applications (2017, methodology): “Among these, in [196] a dual fast gradient method has been proposed.”
From linear to nonlinear MPC: bridging the gap via the real-time iteration (2020, unknown): “…sped up computational times, allowing for the deployment of MPC at outstanding speeds (Domahidi, Zgraggen, Zeilinger, Morari, & Jones, 2012; Ferreau, Kirches, Potschka, Bock, & Diehl, 2014; Frasch, Sager, & Diehl, 2015; Frison, Sorensen, Dammann, & Jorgensen, 2014; Patrinos & Bemporad, 2014).”