A Unified Control-Theoretic Framework for Saddle-Point Dynamics in Constrained Optimization

Fuente: arXiv
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Auteurs principaux: Centorrino, Veronica, Hoteit, Rawan, Balta, Efe C., Lygeros, John
Format: Preprint
Publié: 2026
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author Centorrino, Veronica
Hoteit, Rawan
Balta, Efe C.
Lygeros, John
author_facet Centorrino, Veronica
Hoteit, Rawan
Balta, Efe C.
Lygeros, John
contents This paper studies equality-constrained minimization problems through the lens of feedback control. We introduce a unified control-theoretic framework by showing that a PID feedback law acting on the dual variable induces the PID saddle-point flow (PID-SPF), a broad class of saddle-point dynamics associated with the augmented Lagrangian. This framework recovers several classical primal-dual flows as special cases. We prove that the equilibria of the proposed flow coincide with the stationary points of the original problem. Our analysis reveals how the feedback gains affect the optimization: integral action enforces constraint satisfaction, proportional action introduces the augmented Lagrangian structure, and derivative action modifies the geometry of the primal dynamics by inducing a state-dependent Riemannian metric. Moreover, for convex problems with affine constraints, we establish global exponential convergence by leveraging contraction theory for all admissible PID gains, providing in the process explicit bounds on the convergence rate. Finally, we validate our theoretical results on numerical examples including an application to bilevel optimization.
format Preprint
id arxiv_https___arxiv_org_abs_2604_09252
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Unified Control-Theoretic Framework for Saddle-Point Dynamics in Constrained Optimization
Centorrino, Veronica
Hoteit, Rawan
Balta, Efe C.
Lygeros, John
Optimization and Control
Systems and Control
This paper studies equality-constrained minimization problems through the lens of feedback control. We introduce a unified control-theoretic framework by showing that a PID feedback law acting on the dual variable induces the PID saddle-point flow (PID-SPF), a broad class of saddle-point dynamics associated with the augmented Lagrangian. This framework recovers several classical primal-dual flows as special cases. We prove that the equilibria of the proposed flow coincide with the stationary points of the original problem. Our analysis reveals how the feedback gains affect the optimization: integral action enforces constraint satisfaction, proportional action introduces the augmented Lagrangian structure, and derivative action modifies the geometry of the primal dynamics by inducing a state-dependent Riemannian metric. Moreover, for convex problems with affine constraints, we establish global exponential convergence by leveraging contraction theory for all admissible PID gains, providing in the process explicit bounds on the convergence rate. Finally, we validate our theoretical results on numerical examples including an application to bilevel optimization.
title A Unified Control-Theoretic Framework for Saddle-Point Dynamics in Constrained Optimization
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2604.09252