A Fixed-Time Sliding-Mode Framework for Constraint Optimization

Fuente: arXiv
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Auteurs principaux: Diana, Baby, Singh, Priyanka, Kamal, Shyam, Ghosh, Sandip, Bandyopadhyay, Bijnan
Format: Preprint
Publié: 2026
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author Diana, Baby
Singh, Priyanka
Kamal, Shyam
Ghosh, Sandip
Bandyopadhyay, Bijnan
author_facet Diana, Baby
Singh, Priyanka
Kamal, Shyam
Ghosh, Sandip
Bandyopadhyay, Bijnan
contents This paper develops a robust fixed time optimization framework for constrained problems that guarantees exact constraint satisfaction and convergence to KKT points within fixed time , independent of initial conditions. The approach treats the Lagrange multipliers as control inputs, composed of an equivalent control and a switching control, with the system states representing the decision variables. An equivalent control steers the gradient flow to a local KKT point asymptotically for nonconvex objectives and to unique global optimum in fixed time for convex objectives. Constraint enforcement is achieved by embedding the equality constraints directly as a sliding manifold, with a fixed time switching control ensuring rapid and reliable feasibility. The framework further accounts for the matched disturbances, providing robustness guarantees that are theoretically characterized and illustrated using spherical constraints. Numerical studies on a 3-bus AC optimal power flow problem and distributed consensus=based parameter estimation problem demonstrate the effectiveness, scalability and robustness of proposed approach.
format Preprint
id arxiv_https___arxiv_org_abs_2605_26885
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Fixed-Time Sliding-Mode Framework for Constraint Optimization
Diana, Baby
Singh, Priyanka
Kamal, Shyam
Ghosh, Sandip
Bandyopadhyay, Bijnan
Optimization and Control
Systems and Control
This paper develops a robust fixed time optimization framework for constrained problems that guarantees exact constraint satisfaction and convergence to KKT points within fixed time , independent of initial conditions. The approach treats the Lagrange multipliers as control inputs, composed of an equivalent control and a switching control, with the system states representing the decision variables. An equivalent control steers the gradient flow to a local KKT point asymptotically for nonconvex objectives and to unique global optimum in fixed time for convex objectives. Constraint enforcement is achieved by embedding the equality constraints directly as a sliding manifold, with a fixed time switching control ensuring rapid and reliable feasibility. The framework further accounts for the matched disturbances, providing robustness guarantees that are theoretically characterized and illustrated using spherical constraints. Numerical studies on a 3-bus AC optimal power flow problem and distributed consensus=based parameter estimation problem demonstrate the effectiveness, scalability and robustness of proposed approach.
title A Fixed-Time Sliding-Mode Framework for Constraint Optimization
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2605.26885