@article{7cf3fb4a1669469baa7fd1592fb209a8,
title = "Application of interior-point methods to model predictive control",
abstract = "We present a structured interior-point method for the efficient solution of the optimal control problem in model predictive control. The cost of this approach is linear in the horizon length, compared with cubic growth for a naive approach. We use a discrete-time Riccati recursion to solve the linear equations efficiently at each iteration of the interior-point method, and show that this recursion is numerically stable. We demonstrate the effectiveness of the approach by applying it to three process control problems.",
keywords = "Model predictive control, Riccati equation, interior-point methods",
author = "Rao, {C. V.} and Wright, {S. J.} and Rawlings, {J. B.}",
note = "Funding Information: 1This work was supported by the Mathematical, Information, and Computational Sciences Division subprogram of the Office of Computational and Technology Research, U.S. Department of Energy, under Contract W-31-l09-Eng-38, and a grant from Aspen Technology. We acknowledge the support of the industrial members of the Texas-Wisconsin Modeling and Control Consortium. We are grateful to three referees of the original version of this paper, whose insightful comments improved the paper considerably. 2Research Assistant, Department of Chemical Engineering, University of Wisconsin, Madison, Wisconsin. 3Computer Scientist, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois. 4Professor, Department of Chemical Engineering, University of Wisconsin, Madison, Wisconsin.",
year = "1998",
month = dec,
doi = "10.1023/A:1021711402723",
language = "English (US)",
volume = "99",
pages = "723--757",
journal = "Journal of Optimization Theory and Applications",
issn = "0022-3239",
publisher = "Springer",
number = "3",
}