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Explicit Use of Probability Distributions in SMPC

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Model Predictive Control

Part of the book series: Advanced Textbooks in Control and Signal Processing ((C&SP))

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Abstract

The previous chapter introduced the use of tubes with ellipsoidal or polytopic cross sections in stochastic MPC. However the probabilistic constraints on predicted states and control inputs were handled using confidence regions for stochastic model parameters, namely sets determined offline that contain the uncertain parameters of the model with a specified probability.

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Authors and Affiliations

  1. University of Oxford, Oxford, UK

    Basil Kouvaritakis & Mark Cannon

Authors
  1. Basil Kouvaritakis
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  2. Mark Cannon
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Correspondence to Basil Kouvaritakis .

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Kouvaritakis, B., Cannon, M. (2016). Explicit Use of Probability Distributions in SMPC. In: Model Predictive Control. Advanced Textbooks in Control and Signal Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-24853-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-24853-0_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24851-6

  • Online ISBN: 978-3-319-24853-0

  • eBook Packages: EngineeringEngineering (R0)

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