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Version 2: LASSO MPC with Stabilising Terminal Cost

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Lasso-MPC – Predictive Control with ℓ1-Regularised Least Squares

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Abstract

This chapter presents a modified version of \(\ell _{asso}\)-MPC that guarantees closed-loop asymptotic stability for arbitrary 1-norm input penalties. The approach is based on a new terminal cost and terminal constraint. Appropriate scalings are computed to adjust the proposed former according to the stage cost matrices. In particular, two strategies are presented to compute the required ingredients. The first one makes use of norm inequalities and linear matrix inequalities.

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Notes

  1. 1.

    Under this assumption, it can be easily shown that problems (3.2.1) and (3.2.2) are still an \(\ell _1\)-regularised LS problem.

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Authors and Affiliations

  1. Analytics, McLaren Applied Technologies, Woking, UK

    Marco Gallieri

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  1. Marco Gallieri
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Correspondence to Marco Gallieri .

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Gallieri, M. (2016). Version 2: LASSO MPC with Stabilising Terminal Cost. In: Lasso-MPC – Predictive Control with ℓ1-Regularised Least Squares. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-27963-3_5

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  • DOI: https://doi.org/10.1007/978-3-319-27963-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27961-9

  • Online ISBN: 978-3-319-27963-3

  • eBook Packages: EngineeringEngineering (R0)

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