Contraction Analysis of Continuation Method for Suboptimal Model Predictive Control
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866916643792224256 |
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| author | Shima, Ryotaro Ito, Yuji Miyano, Tatsuya |
| author_facet | Shima, Ryotaro Ito, Yuji Miyano, Tatsuya |
| contents | This letter analyzes the contraction property of the nonlinear systems controlled by suboptimal model predictive control (MPC) using the continuation method. We propose a contraction metric that reflects the hierarchical dynamics inherent in the continuation method. We derive a pair of matrix inequalities that elucidate the impact of suboptimality on the contraction of the optimally controlled closed-loop system. A numerical example is presented to verify our contraction analysis. Our results are applicable to other MPCs than stabilization, including economic MPC. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_10970 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Contraction Analysis of Continuation Method for Suboptimal Model Predictive Control Shima, Ryotaro Ito, Yuji Miyano, Tatsuya Optimization and Control This letter analyzes the contraction property of the nonlinear systems controlled by suboptimal model predictive control (MPC) using the continuation method. We propose a contraction metric that reflects the hierarchical dynamics inherent in the continuation method. We derive a pair of matrix inequalities that elucidate the impact of suboptimality on the contraction of the optimally controlled closed-loop system. A numerical example is presented to verify our contraction analysis. Our results are applicable to other MPCs than stabilization, including economic MPC. |
| title | Contraction Analysis of Continuation Method for Suboptimal Model Predictive Control |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2409.10970 |