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Privacy in Dynamical Systems pp 231–265Cite as

Encrypted Model Predictive Control in the Cloud

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Abstract

In this chapter, we focus on encrypted model predictive control (MPC) implemented in a single cloud. In general, encrypted control enables confidential controller evaluations in networked control systems. Technically, an encrypted controller is a modified control algorithm that is capable of computing encrypted control actions based on encrypted system states without intermediate decryptions. Encrypted control can, for example, be realized using homomorphic encryption that allows simple mathematical operations to be carried out on encrypted data. However, encrypting optimization-based control schemes such as MPC is non-trivial. Against this background, the contribution of the chapter is twofold. First, we summarize and unify two existing encrypted MPCs using the additively homomorphic Paillier cryptosystem. Second, we present a novel encrypted MPC based on real-time iterations of the alternating direction method of multipliers (ADMM). We theoretically and experimentally compare the three approaches and highlight unique features of the new scheme.

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Acknowledgements

Support by the German Research Foundation (DFG) under the grant SCHU 2940/4-1 is gratefully acknowledged.

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Authors and Affiliations

  1. Automatic Control Group, Department of Electrical Engineering and Information Technology, Universität Paderborn, Paderborn, Germany

    Moritz Schulze Darup

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  1. Moritz Schulze Darup
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Correspondence to Moritz Schulze Darup .

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Editors and Affiliations

  1. Department of Electrical and Electronic Engineering, The University of Melbourne and CSIRO’s Data61, Melbourne, VIC, Australia

    Farhad Farokhi

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Schulze Darup, M. (2020). Encrypted Model Predictive Control in the Cloud. In: Farokhi, F. (eds) Privacy in Dynamical Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0493-8_11

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