Embedded Online Optimization for Model Predictive Control at Megahertz Rates
| Author(s): J.L. Jerez, P.J. Goulart, Stefan Richter, G. Constantinides, E.C. Kerrigan, M. Morari |
Conference/Journal: IEEE Transactions on Automatic Control, vol. 59, no. 12, pp. 3238-3251 |
| Abstract: 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. | Year: 2014 |
| Type of Publication: (01)Article | |
| Supervisor: M. Morari | |
% Autogenerated BibTeX entry
@Article { JerEtal:2014:IFA_4866,
author={J.L. Jerez and P.J. Goulart and Stefan Richter and G.
Constantinides and E.C. Kerrigan and M. Morari},
title={{Embedded Online Optimization for Model Predictive Control
at Megahertz Rates}},
journal={IEEE Transactions on Automatic Control},
year={2014},
volume={59},
number={12},
pages={3238--3251},
month=dec,
url={https://old.control.ee.ethz.ch/index.cgi?page=publications;action=details;id=4866}
} | |