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A multirate variational approach to nonlinear MPC

Abstract:
A multirate nonlinear model predictive control (NMPC) strategy is proposed for systems with dynamics and control inputs evolving on different timescales. The proposed multirate formulation of the system model and receding horizon optimal control problem allows larger time steps in the prediction horizon compared to single-rate schemes, providing computational savings while ensuring recursive feasibility. A multirate variational model is used with a tube-based successive linearization NMPC strategy. This allows either Jacobian linearization or linearization using quadratic and linear Taylor series approximations of the Lagrangian and generalized forces respectively, providing alternative means for computing linearization error bounds. The two approaches are shown to be equivalent for a specific choice of approximation points and their structure-preserving properties are investigated. Numerical examples are provided to illustrate the multirate approach, its conservation properties and computational savings.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.23919/ECC55457.2022.9838240

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Publisher:
IEEE
Host title:
Proceedings of the 20th European Control Conference (ECC 2022)
Pages:
729-735
Publication date:
2022-08-05
Acceptance date:
2022-03-30
Event title:
20th European Control Conference (ECC 2022)
Event location:
London, UK
Event website:
https://ecc22.euca-ecc.org/
Event start date:
2022-07-12
Event end date:
2022-07-15
DOI:
EISBN:
978-3-9071-4407-7
ISBN:
978-1-6654-9733-6


Language:
English
Keywords:
Pubs id:
1262909
Local pid:
pubs:1262909
Deposit date:
2022-06-10

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