@article{Jerez:2014:10.1109/TAC.2014.2351991,
author = {Jerez, J and Goulart, P and Richter, S and Constantinides, GA and Kerrigan, EC and Morari, M},
doi = {10.1109/TAC.2014.2351991},
journal = {IEEE Transactions on Automatic Control},
pages = {3238--3251},
title = {Embedded online optimization for model predictive control at megahertz rates},
url = {http://dx.doi.org/10.1109/TAC.2014.2351991},
volume = {59},
year = {2014}
}

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TY  - JOUR
AB  - Faster, cheaper, and more power efficient optimization solvers than those currently possible using general-purpose techniques are required for extending the use of model predictive control (MPC) to resource-constrained embedded platforms. We propose several custom computational architectures for different first-order optimization methods that can handle linear-quadratic MPC problems with input, input-rate, and soft state constraints. We provide analysis ensuring the reliable operation of the resulting controller under reduced precision fixed-point arithmetic. Implementation of the proposed architectures in FPGAs shows that satisfactory control performance at a sample rate beyond 1 MHz is achievable even on low-end devices, opening up new possibilities for the application of MPC on embedded systems.
AU  - Jerez,J
AU  - Goulart,P
AU  - Richter,S
AU  - Constantinides,GA
AU  - Kerrigan,EC
AU  - Morari,M
DO  - 10.1109/TAC.2014.2351991
EP  - 3251
PY  - 2014///
SN  - 0018-9286
SP  - 3238
TI  - Embedded online optimization for model predictive control at megahertz rates
T2  - IEEE Transactions on Automatic Control
UR  - http://dx.doi.org/10.1109/TAC.2014.2351991
UR  - https://ieeexplore.ieee.org/document/6882832
VL  - 59
ER  - 

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