Dual-Regularized Riccati Recursions for Interior-Point Optimal Control
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915815059619840 |
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| author | Sousa-Pinto, João Orban, Dominique |
| author_facet | Sousa-Pinto, João Orban, Dominique |
| contents | We derive closed-form extensions of Riccati's recursions (both sequential and parallel) for solving dual-regularized LQR problems. We show how these methods can be used to solve general constrained, non-convex, discrete-time optimal control problems via a regularized interior point method, while guaranteeing that each primal step is a descent direction of an Augmented Barrier-Lagrangian merit function. We provide MIT-licensed implementations of our methods in C++ and JAX. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_16370 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Dual-Regularized Riccati Recursions for Interior-Point Optimal Control Sousa-Pinto, João Orban, Dominique Optimization and Control Mathematical Software Robotics Systems and Control 49M37, 90C51, 93B45 G.1.6 We derive closed-form extensions of Riccati's recursions (both sequential and parallel) for solving dual-regularized LQR problems. We show how these methods can be used to solve general constrained, non-convex, discrete-time optimal control problems via a regularized interior point method, while guaranteeing that each primal step is a descent direction of an Augmented Barrier-Lagrangian merit function. We provide MIT-licensed implementations of our methods in C++ and JAX. |
| title | Dual-Regularized Riccati Recursions for Interior-Point Optimal Control |
| topic | Optimization and Control Mathematical Software Robotics Systems and Control 49M37, 90C51, 93B45 G.1.6 |
| url | https://arxiv.org/abs/2509.16370 |