Time-certified Input-constrained NMPC via Koopman Operator

Liang Wu; Krystian Ganko; Richard D. Braatz

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arXiv · 2401.04653

Time-certified Input-constrained NMPC via Koopman Operator

Liang Wu·Krystian Ganko·Richard D. Braatz

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Abstract

Determining solving-time certificates of nonlinear model predictive control (NMPC) implementations is a pressing requirement when deploying NMPC in production environments. Such a certificate guarantees that the NMPC controller returns a solution before the next sampling time. However, NMPC formulations produce nonlinear programs (NLPs) for which it is very difficult to derive their solving-time certificates. Our previous work, Wu and Braatz (2023), challenged this limitation with a proposed input-constrained MPC algorithm having exact iteration complexity but was restricted to linear MPC formulations. This work extends the algorithm to solve input-constrained NMPC problems, by using the Koopman operator and a condensing MPC technique. We illustrate the algorithm performance on a high-dimensional, nonlinear partial differential equation (PDE) control case study, in which we theoretically and numerically certify the solving time to be less than the sampling time.

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BibTeX RIS

Liang Wu, Krystian Ganko, Richard D. Braatz. 2024-01-09. Time-certified Input-constrained NMPC via Koopman Operator. https://arxiv.org/abs/2401.04653

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