activity
20182021
most citedTimescale Separation in Autonomous Optimization

94 citations · 351 across the 11 of their papers we have counts for

collaborators

12 papers

math.OC2021★ 32 cited

Optimization Algorithms as Robust Feedback Controllers

Adrian Hauswirth, Zhiyu He, Saverio Bolognani +2

Mathematical optimization is one of the cornerstones of modern engineering research and practice. Yet, throughout all application domains, mathematical optimization is, for the mos…

math.OC2020

Limit Behavior and the Role of Augmentation in Projected Saddle Flows for Convex Optimization

Adrian Hauswirth, Lukas Ortmann, Saverio Bolognani +1

In this paper, we study the stability and convergence of continuous-time Lagrangian saddle flows to solutions of a convex constrained optimization problem. Convergence of these flo…

math.OC2020

Quantitative Sensitivity Bounds for Nonlinear Programming and Time-varying Optimization

Irina Subotić, Adrian Hauswirth, Florian Dörfler

Inspired by classical sensitivity results for nonlinear optimization, we derive and discuss new quantitative bounds to characterize the solution map and dual variables of a paramet…

math.OC2020★ 10 cited

On the Differentiability of Projected Trajectories and the Robust Convergence of Non-convex Anti-Windup Gradient Flows

Adrian Hauswirth, Florian Dörfler, Andrew Teel

This paper concerns a new class of discontinuous dynamical systems for constrained optimization. These dynamics are particularly suited to solve nonlinear, non-convex problems in c…

eess.SY2020★ 48 cited

Non-convex Feedback Optimization with Input and Output Constraints

Verena Häberle, Adrian Hauswirth, Lukas Ortmann +2

In this paper, we present a novel control scheme for feedback optimization. That is, we propose a discrete-time controller that can steer the steady state of a physical plant to th…

math.OC2020★ 10 cited

Anti-Windup Approximations of Oblique Projected Dynamics for Feedback-based Optimization

Adrian Hauswirth, Florian Dörfler, Andrew Teel

In this paper we study how high-gain anti-windup schemes can be used to implement projected dynamical systems in control loops that are subject to saturation on a (possibly unknown…

eess.SY2019★ 67 cited

Experimental Validation of Feedback Optimization in Power Distribution Grids

Lukas Ortmann, Adrian Hauswirth, Ivo Caduff +2

We consider the problem of controlling the voltage of a distribution feeder using the reactive power capabilities of inverters. On a real distribution grid, we compare the local Vo…

math.OC2019★ 94 cited

Timescale Separation in Autonomous Optimization

Adrian Hauswirth, Saverio Bolognani, Gabriela Hug +1

Autonomous optimization refers to the design of feedback controllers that steer a physical system to a steady state that solves a predefined, possibly constrained, optimization pro…

math.OC2018★ 36 cited

Stability of Dynamic Feedback Optimization with Applications to Power Systems

Sandeep Menta, Adrian Hauswirth, Saverio Bolognani +2

We consider the problem of optimizing the steady state of a dynamical system in closed loop. Conventionally, the design of feedback optimization control laws assumes that the syste…

math.OC2018★ 25 cited

Time-varying Projected Dynamical Systems with Applications to Feedback Optimization of Power Systems

Adrian Hauswirth, Irina Subotić, Saverio Bolognani +2

This paper is concerned with the study of continuous-time, non-smooth dynamical systems which arise in the context of time-varying non-convex optimization problems, as for example…

math.OC2018★ 7 cited

Projected Dynamical Systems on Irregular, Non-Euclidean Domains for Nonlinear Optimization

Adrian Hauswirth, Saverio Bolognani, Florian Dörfler

Continuous-time projected dynamical systems are an elementary class of discontinuous dynamical systems with trajectories that remain in a feasible domain by means of projecting out…

math.OC2018★ 22 cited

Generic Existence of Unique Lagrange Multipliers in AC Optimal Power Flow

Adrian Hauswirth, Saverio Bolognani, Gabriela Hug +1

Solutions to nonlinear, nonconvex optimization problems can fail to satisfy the KKT optimality conditions even when they are optimal. This is due to the fact that unless constraint…