Towards Encrypted MPC for Linear Constrained Systems

2017135 citationsJournal Article

Authors

Moritz Schulze Darup · Paderborn University

Iman Shames · The University of Melbourne

Farhad Farokhi · The University of Melbourne

Daniel E. Quevedo · Paderborn University

Abstract

We present an encrypted model predictive control (MPC) scheme for linear constrained systems. More precisely, we show that homomorphic encryption can be used to realize a secure and private cloud-based evaluation of an MPC if the corresponding piecewise affine control law is explicitly given.

Topics & Keywords

Advanced Control Systems Optimization Advanced Data Storage Technologies Optimization and Search Problems

UN Sustainable Development Goals

Peace, Justice and strong institutions

Publication Details

Published in: IEEE Control Systems Letters

Volume 2, Issue 2, pp. 195-200

DOI: 10.1109/lcsys.2017.2779473

Field-Weighted Citation Impact: 9.57