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20242026
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math.OC2026

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

Veronica Centorrino, Rawan Hoteit, Efe C. Balta +1

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 feedbac…

math.OC2025

Semismooth Newton Methods for Risk-Averse Markov Decision Processes

Matilde Gargiani, Francesco Micheli, Anastasios Tsiamis +1

Inspired by semismooth Newton methods, we propose a general framework for designing solution methods with convergence guarantees for risk-averse Markov decision processes. Our appr…

math.OC2024

Operator Splitting for Convex Constrained Markov Decision Processes

Panagiotis D. Grontas, Anastasios Tsiamis, John Lygeros

We consider finite Markov decision processes (MDPs) with convex constraints and known dynamics. In principle, this problem is amenable to off-the-shelf convex optimization solvers,…

math.OC2024

BP-MPC: Optimizing the Closed-Loop Performance of MPC using BackPropagation

Riccardo Zuliani, Efe C. Balta, John Lygeros

Model predictive control (MPC) is pervasive in research and industry. However, designing the cost function and the constraints of the MPC to maximize closed-loop performance remain…

math.OC2024

Computing Optimal Joint Chance Constrained Control Policies

Niklas Schmid, Marta Fochesato, Sarah H. Q. Li +2

We consider the problem of optimally controlling stochastic, Markovian systems subject to joint chance constraints over a finite-time horizon. For such problems, standard Dynamic P…

math.OC2024

Interconnection of (Q,S,R)-Dissipative Systems in Discrete Time

Andrea Martinelli, Ahmed Aboudonia, John Lygeros

Discrete-time systems cannot be passive unless there is a direct feedthrough from the input to the output. For passivity-based control to be exploited nevertheless, some authors in…