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Application of Interior-Point Methods to Model Predictive Control

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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.

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Authors and Affiliations

  1. Department of Chemical Engineering, University of Wisconsin, Madison, Wisconsin

    C. V. Rao (Research Assistant)

  2. Mathematics and Computer Science Division, Argonne National Laboratory, [Argonne, Illinois

    S. J. Wright (Computer Scientist)

  3. Department of Chemical Engineering, University of Wisconsin, Wisconsin

    J. B. Rawlings (Professor)

Authors
  1. C. V. Rao
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  2. S. J. Wright
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  3. J. B. Rawlings
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Rao, C.V., Wright, S.J. & Rawlings, J.B. Application of Interior-Point Methods to Model Predictive Control. Journal of Optimization Theory and Applications 99, 723–757 (1998). https://doi.org/10.1023/A:1021711402723

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  • DOI: https://doi.org/10.1023/A:1021711402723

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