Adaptive tracking MPC for nonlinear systems via online linear system identification
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866914798479867904 |
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| author | Strelnikova, Tatiana Köhler, Johannes Berberich, Julian |
| author_facet | Strelnikova, Tatiana Köhler, Johannes Berberich, Julian |
| contents | This paper presents an adaptive tracking model predictive control (MPC) scheme to control unknown nonlinear systems based on an adaptively estimated linear model. The model is determined based on linear system identification using a moving window of past measurements, and it serves as a local approximation of the underlying nonlinear dynamics. We prove that the presented scheme ensures practical exponential stability of the (unknown) optimal reachable equilibrium for a given output setpoint. Finally, we apply the proposed scheme in simulation and compare it to an alternative direct data-driven MPC scheme based on the Fundamental Lemma. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_09852 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Adaptive tracking MPC for nonlinear systems via online linear system identification Strelnikova, Tatiana Köhler, Johannes Berberich, Julian Systems and Control Optimization and Control This paper presents an adaptive tracking model predictive control (MPC) scheme to control unknown nonlinear systems based on an adaptively estimated linear model. The model is determined based on linear system identification using a moving window of past measurements, and it serves as a local approximation of the underlying nonlinear dynamics. We prove that the presented scheme ensures practical exponential stability of the (unknown) optimal reachable equilibrium for a given output setpoint. Finally, we apply the proposed scheme in simulation and compare it to an alternative direct data-driven MPC scheme based on the Fundamental Lemma. |
| title | Adaptive tracking MPC for nonlinear systems via online linear system identification |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2405.09852 |