Robust IMMPC: An Offset-free MPC for Rejecting Unknown Disturbances
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866918423089381376 |
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| author | Brändle, Felix Allgöwer, Frank |
| author_facet | Brändle, Felix Allgöwer, Frank |
| contents | Output regulation is the problem of finding a control input to asymptotically track reference trajectories and reject disturbances. This can be addressed by using the internal model principle to embed a model of the disturbance in the controller. In this work, we present a Model Predictive Control scheme to achieve offset-free control. To do so, we extend Internal Model MPC to general bounded disturbances that must not be generated by the disturbance model. We show recursive feasibility, constraint satisfaction, and provide convergence conditions for the optimal reachable output. The proposed controller is validated on a four-tank system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_00564 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Robust IMMPC: An Offset-free MPC for Rejecting Unknown Disturbances Brändle, Felix Allgöwer, Frank Systems and Control Output regulation is the problem of finding a control input to asymptotically track reference trajectories and reject disturbances. This can be addressed by using the internal model principle to embed a model of the disturbance in the controller. In this work, we present a Model Predictive Control scheme to achieve offset-free control. To do so, we extend Internal Model MPC to general bounded disturbances that must not be generated by the disturbance model. We show recursive feasibility, constraint satisfaction, and provide convergence conditions for the optimal reachable output. The proposed controller is validated on a four-tank system. |
| title | Robust IMMPC: An Offset-free MPC for Rejecting Unknown Disturbances |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2604.00564 |