Feasibility Analysis and Regularity Characterization of Distributionally Robust Safe Stabilizing Controllers

Fuente: arXiv
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Main Authors: Mestres, Pol, Long, Kehan, Atanasov, Nikolay, Cortés, Jorge
Format: Preprint
Published: 2023
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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