Robust Model Predictive Control Exploiting Monotonicity Properties
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913806199816192 |
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| author | Heinlein, Moritz Subramanian, Sankaranarayanan Lucia, Sergio |
| author_facet | Heinlein, Moritz Subramanian, Sankaranarayanan Lucia, Sergio |
| contents | Robust model predictive control algorithms are essential for addressing unavoidable errors due to the uncertainty in predicting real-world systems. However, the formulation of such algorithms typically results in a trade-off between conservatism and computational complexity. Monotone systems facilitate the efficient computation of reachable sets and thus the straightforward formulation of a robust model predictive control approach optimizing over open-loop predictions. We present an approach based on the division of reachable sets to incorporate feedback in the predictions, resulting in less conservative strategies. The concept of mixed-monotonicity enables an extension of our methodology to non-monotone systems. The potential of the proposed approaches is demonstrated through a nonlinear high-dimensional chemical tank reactor cascade case study. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2408_17348 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Robust Model Predictive Control Exploiting Monotonicity Properties Heinlein, Moritz Subramanian, Sankaranarayanan Lucia, Sergio Systems and Control Optimization and Control Robust model predictive control algorithms are essential for addressing unavoidable errors due to the uncertainty in predicting real-world systems. However, the formulation of such algorithms typically results in a trade-off between conservatism and computational complexity. Monotone systems facilitate the efficient computation of reachable sets and thus the straightforward formulation of a robust model predictive control approach optimizing over open-loop predictions. We present an approach based on the division of reachable sets to incorporate feedback in the predictions, resulting in less conservative strategies. The concept of mixed-monotonicity enables an extension of our methodology to non-monotone systems. The potential of the proposed approaches is demonstrated through a nonlinear high-dimensional chemical tank reactor cascade case study. |
| title | Robust Model Predictive Control Exploiting Monotonicity Properties |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2408.17348 |