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arXiv · 2412.13046

Adaptive Economic Model Predictive Control: Performance Guarantees for Nonlinear Systems

Maximilian Degner·Raffaele Soloperto·Melanie N. Zeilinger·John Lygeros·Johannes Köhler
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Abstract

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.

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Maximilian Degner, Raffaele Soloperto, Melanie N. Zeilinger, John Lygeros, Johannes Köhler. 2024-12-17. Adaptive Economic Model Predictive Control: Performance Guarantees for Nonlinear Systems. https://arxiv.org/abs/2412.13046

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