Adaptive Economic Model Predictive Control: Performance Guarantees for Nonlinear Systems

Fuente: arXiv
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Hauptverfasser: Degner, Maximilian, Soloperto, Raffaele, Zeilinger, Melanie N., Lygeros, John, Köhler, Johannes
Format: Preprint
Veröffentlicht: 2024
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author Degner, Maximilian
Soloperto, Raffaele
Zeilinger, Melanie N.
Lygeros, John
Köhler, Johannes
author_facet Degner, Maximilian
Soloperto, Raffaele
Zeilinger, Melanie N.
Lygeros, John
Köhler, Johannes
contents We consider the problem of optimizing the economic performance of nonlinear constrained systems subject to uncertain time-varying parameters and bounded disturbances. In particular, we propose an adaptive economic model predictive control (MPC) framework that: (i) directly minimizes transient economic costs, (ii) addresses parametric uncertainty through online model adaptation, (iii) determines optimal setpoints online, and (iv) ensures robustness by using a tube-based approach. The proposed design ensures recursive feasibility, robust constraint satisfaction, and a transient performance bound. In case the disturbances have a finite energy and the parameter variations have a finite path length, the asymptotic average performance is (approximately) not worse than the performance obtained when operating at the best reachable steady-state. We highlight performance benefits in a numerical example involving a chemical reactor with unknown time-invariant and time-varying parameters.
format Preprint
id arxiv_https___arxiv_org_abs_2412_13046
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Adaptive Economic Model Predictive Control: Performance Guarantees for Nonlinear Systems
Degner, Maximilian
Soloperto, Raffaele
Zeilinger, Melanie N.
Lygeros, John
Köhler, Johannes
Systems and Control
Optimization and Control
We consider the problem of optimizing the economic performance of nonlinear constrained systems subject to uncertain time-varying parameters and bounded disturbances. In particular, we propose an adaptive economic model predictive control (MPC) framework that: (i) directly minimizes transient economic costs, (ii) addresses parametric uncertainty through online model adaptation, (iii) determines optimal setpoints online, and (iv) ensures robustness by using a tube-based approach. The proposed design ensures recursive feasibility, robust constraint satisfaction, and a transient performance bound. In case the disturbances have a finite energy and the parameter variations have a finite path length, the asymptotic average performance is (approximately) not worse than the performance obtained when operating at the best reachable steady-state. We highlight performance benefits in a numerical example involving a chemical reactor with unknown time-invariant and time-varying parameters.
title Adaptive Economic Model Predictive Control: Performance Guarantees for Nonlinear Systems
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2412.13046