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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.07436 |
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| _version_ | 1866914642028134400 |
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| author | Burachik, Regina S. Caldwell, Bethany I. Kaya, C. Yalçın |
| author_facet | Burachik, Regina S. Caldwell, Bethany I. Kaya, C. Yalçın |
| contents | We consider the application of the Douglas-Rachford (DR) algorithm to solve linear-quadratic (LQ) control problems with box constraints on the state and control variables. We split the constraints of the optimal control problem into two sets: one involving the ODE with boundary conditions, which is affine, and the other a box. We rewrite the LQ control problems as the minimization of the sum of two convex functions. We find the proximal mappings of these functions which we then employ for the projections in the DR iterations. We propose a numerical algorithm for computing the projection onto the affine set. We present a conjecture for finding the costates and the state constraint multipliers of the optimal control problem, which can in turn be used in verifying the optimality conditions. We carry out numerical experiments with two constrained optimal control problems to illustrate the working and the efficiency of the DR algorithm compared to the traditional approach of direct discretization. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_07436 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Douglas-Rachford Algorithm for Control- and State-constrained Optimal Control Problems Burachik, Regina S. Caldwell, Bethany I. Kaya, C. Yalçın Optimization and Control We consider the application of the Douglas-Rachford (DR) algorithm to solve linear-quadratic (LQ) control problems with box constraints on the state and control variables. We split the constraints of the optimal control problem into two sets: one involving the ODE with boundary conditions, which is affine, and the other a box. We rewrite the LQ control problems as the minimization of the sum of two convex functions. We find the proximal mappings of these functions which we then employ for the projections in the DR iterations. We propose a numerical algorithm for computing the projection onto the affine set. We present a conjecture for finding the costates and the state constraint multipliers of the optimal control problem, which can in turn be used in verifying the optimality conditions. We carry out numerical experiments with two constrained optimal control problems to illustrate the working and the efficiency of the DR algorithm compared to the traditional approach of direct discretization. |
| title | Douglas-Rachford Algorithm for Control- and State-constrained Optimal Control Problems |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2401.07436 |