Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89779
Title: Banded null basis and ADMM for embedded MPC
Authors: Dang, Thuy V
Ling, Keck Voon
Maciejowski, Jan
Keywords: DRNTU::Engineering::Electrical and electronic engineering
ADMM
Banded Null Basis
Issue Date: 2017
Source: Dang, T. V., Ling, K. V., & Maciejowski, J. (2017). Banded null basis and ADMM for embedded MPC. IFAC-PapersOnLine, 50(1), 13170-13175. doi: 10.1016/j.ifacol.2017.08.2172
Series/Report no.: IFAC-PapersOnLine
Abstract: In this paper, we propose an improved QP solver for embedded implementations of MPC controllers. We adopt a “reduced Hessian” approach for handling the equality constraints that arise in the well-known “banded” formulation of MPC (in which the predicted states are not eliminated). Our key observation is that a banded basis exists for the null space of the banded equality-constraint matrix, and that this leads to a QP of the same size as the “condensed” formulation of MPC problems, which is considerably smaller than the “banded” formulation. We use the Alternating Direction Method of Multipliers (ADMM) - which is known to be particularly suitable for embedded implementations - to solve this smaller QP problem. Our C implementation results for a particular MPC example (a 9-state, 3-input quadrotor) show that our proposed algorithm is about 4 times faster than an existing well-performing ADMM variant (“indirect indicator” ADMM or “iiADMM”) and 3 times faster than the well-known QP solver CVXGEN. The convergence rate and code size of the proposed ADMM variant is also comparable with iiADMM.
URI: https://hdl.handle.net/10356/89779
http://hdl.handle.net/10220/47137
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2017.08.2172
Rights: © IFAC 2018. This work is posted here by permission of IFAC for your personal use. Not for distribution. The original version was published in ifac-papersonline.net, DOI: 10.1016/j.ifacol.2017.08.2172.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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