eprintid: 2328
rev_number: 12
eprint_status: archive
userid: 6
dir: disk0/00/00/23/28
datestamp: 2014-10-22 07:55:49
lastmod: 2015-04-07 14:04:19
status_changed: 2014-10-22 07:55:49
type: book_section
metadata_visibility: show
creators_name: Guiggiani, Alberto
creators_name: Patrinos, Panagiotis
creators_name: Bemporad, Alberto
creators_id: alberto.guiggiani@imtlucca.it
creators_id: panagiotis.patrinos@imtlucca.it
creators_id: alberto.bemporad@imtlucca.it
title: Fixed-point implementation of a proximal Newton method for embedded model predictive control (I)
ispublished: pub
subjects: TL
divisions: CSA
full_text_status: public
pres_type: paper
keywords: Identification and control methods; Cyber-Physical Systems
note: 19th IFAC World Congress, August 24-29, 2014, Cape Town, South Africa
abstract: Extending the success of model predictive control (MPC) technologies in embedded applications heavily depends on the capability of improving quadratic programming (QP) solvers. Improvements can be done in two directions: better algorithms that reduce the number of arithmetic operations required to compute a solution, and more efficient architectures in terms of speed, power consumption, memory occupancy and cost. This paper proposes a fixed point implementation of a proximal Newton method to solve optimization problems arising in input-constrained MPC. The main advantages of the algorithm are its fast asymptotic convergence rate and its relatively low computational cost per iteration since it the solution of a small linear system is required. A detailed analysis on the effects of quantization errors is presented, showing the robustness of the algorithm with respect to finite-precision computations. A hardware implementation with specific optimizations to minimize computation times and memory footprint is also described, demonstrating the viability of low-cost, low-power controllers for high-bandwidth MPC applications. The algorithm is shown to be very effective for embedded MPC applications through a number of simulation experiments. 
date: 2014-08
date_type: published
publisher: IFAC
pagerange: 2921-2926
id_number: 10.3182/20140824-6-ZA-1003.00992
refereed: TRUE
isbn: 978-3-902823-62-5
book_title: Proceedings of the 19th IFAC World Congress
official_url: http://www.ifac-papersonline.net/Detailed/66145.html
citation:   Guiggiani, Alberto and Patrinos, Panagiotis and Bemporad, Alberto  Fixed-point implementation of a proximal Newton method for embedded model predictive control (I).   In:  Proceedings of the 19th IFAC World Congress.   IFAC, pp. 2921-2926.  ISBN 978-3-902823-62-5      (2014)  
document_url: http://eprints.imtlucca.it/2328/1/Patrinos_Guggiani_Bemporad_IFAC14.pdf