Feasibility Analysis and Regularity Characterization of Distributionally Robust Safe Stabilizing Controllers
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866911742987075584 |
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| author | Mestres, Pol Long, Kehan Atanasov, Nikolay Cortés, Jorge |
| author_facet | Mestres, Pol Long, Kehan Atanasov, Nikolay Cortés, Jorge |
| contents | This paper studies the well-posedness and regularity of safe stabilizing optimization-based controllers for control-affine systems in the presence of model uncertainty. When the system dynamics contain unknown parameters, a finite set of samples can be used to formulate distributionally robust versions of control barrier function and control Lyapunov function constraints. Control synthesis with such distributionally robust constraints can be achieved by solving a (convex) second-order cone program (SOCP). We provide one necessary and two sufficient conditions to check the feasibility of such optimization problems, characterize their computational complexity and numerically show that they are significantly faster to check than direct use of SOCP solvers. Finally, we also analyze the regularity of the resulting control laws. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_05813 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Feasibility Analysis and Regularity Characterization of Distributionally Robust Safe Stabilizing Controllers Mestres, Pol Long, Kehan Atanasov, Nikolay Cortés, Jorge Optimization and Control Systems and Control This paper studies the well-posedness and regularity of safe stabilizing optimization-based controllers for control-affine systems in the presence of model uncertainty. When the system dynamics contain unknown parameters, a finite set of samples can be used to formulate distributionally robust versions of control barrier function and control Lyapunov function constraints. Control synthesis with such distributionally robust constraints can be achieved by solving a (convex) second-order cone program (SOCP). We provide one necessary and two sufficient conditions to check the feasibility of such optimization problems, characterize their computational complexity and numerically show that they are significantly faster to check than direct use of SOCP solvers. Finally, we also analyze the regularity of the resulting control laws. |
| title | Feasibility Analysis and Regularity Characterization of Distributionally Robust Safe Stabilizing Controllers |
| topic | Optimization and Control Systems and Control |
| url | https://arxiv.org/abs/2311.05813 |