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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

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% 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={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=4866}
}
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