Interior Point Methods in Optimal Control
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866913393771806720 |
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| author | Malisani, Paul |
| author_facet | Malisani, Paul |
| contents | This paper deals with Interior Point Methods (IPMs) for Optimal Control Problems (OCPs) with pure state and mixed constraints. This paper establishes a complete proof of convergence of IPMs for a general class of OCPs. Convergence results are proved for primal variables, namely state and control variables, and for dual variables, namely, the adjoint state, and the constraints multipliers. In addition, the presented convergence result does not rely on a strong convexity assumption. Finally, this paper provides two IPM-based solving algorithms: a primal solving algorithm and a primal-dual solving algorithm. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_01425 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Interior Point Methods in Optimal Control Malisani, Paul Optimization and Control This paper deals with Interior Point Methods (IPMs) for Optimal Control Problems (OCPs) with pure state and mixed constraints. This paper establishes a complete proof of convergence of IPMs for a general class of OCPs. Convergence results are proved for primal variables, namely state and control variables, and for dual variables, namely, the adjoint state, and the constraints multipliers. In addition, the presented convergence result does not rely on a strong convexity assumption. Finally, this paper provides two IPM-based solving algorithms: a primal solving algorithm and a primal-dual solving algorithm. |
| title | Interior Point Methods in Optimal Control |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2309.01425 |