# Offset-free Nonlinear MPC with Koopman-based Surrogate Models

arXiv: https://arxiv.org/abs/2504.10954 · HTML: https://mlsanity.com/paper/2504.10954/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Apr 2025.

## Built on by (most cited first, 1 of 1)

- [Koopman-Based Nonlinear Identification and Model Predictive Control of a Turbofan Engine](https://mlsanity.com/paper/2604.01730/) (2026)

## Abstract (arXiv)

In this paper, we design offset-free nonlinear Model Predictive Control (MPC) for surrogate models based on Extended Dynamic Mode Decomposition (EDMD). The model used for prediction in MPC is augmented with a disturbance term, that is estimated by an observer. If the full information about the equilibrium of the real system is not available, a reference calculator is introduced in the algorithm to compute the MPC state and input references. The control algorithm guarantees offset-free tracking of the controlled output under the assumption that the modeling errors are asymptotically constant. The effectiveness of the proposed approach is showcased with numerical simulations for two popular benchmark systems: the van-der-Pol oscillator and the four-tanks process.