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Real-time proximal gradient method for embedded linear MPC

Tijdschriftbijdrage - Tijdschriftartikel

© 2019 This paper presents and experimentally validates an embedded linear model predictive control (MPC) approach that is particularly useful for implementation on resource-constrained embedded hardware. The MPC scheme is based on a real-time implementation of the proximal gradient method (PGM) and generates input signals with guaranteed constraint satisfaction. Given standard linear MPC assumptions, asymptotic stability of the resulting closed loop is proven. Applied to linear systems with simple input constraints, the real-time PGM results in very simple arithmetics that are rapidly executed on resource-constrained hardware. As a proof on concept, the algorithm is demonstrated on two experimental setups in which it is implemented on a micro-controller. These experimental validations and related simulations demonstrate how the proposed real-time PGM allows fast control rates, especially compared to state-of-the-art linear MPC approaches, and this while preserving good closed-loop performance.
Tijdschrift: Mechatronics
ISSN: 0957-4158
Volume: 59
Pagina's: 1 - 9
Jaar van publicatie:2019
BOF-keylabel:ja
IOF-keylabel:ja
BOF-publication weight:1
CSS-citation score:1
Authors from:Government, Higher Education
Toegankelijkheid:Open