activity
20112024
most citedOn a class of generating vector fields for the extremum seeking problem: Lie bracket approximation and stability properties

108 citations · 185 across the 22 of their papers we have counts for

collaborators

31 papers

math.OC2024

Inferring Global Exponential Stability Properties using Lie-bracket Approximations

Marc Weber, Bahman Gharesifard, Christian Ebenbauer

In the present paper, a novel result for inferring uniform global, not semi-global, exponential stability in the sense of Lyapunov with respect to input-affine systems from global…

math.OC2024

Flexible-step MPC for Switched Linear Systems with No Quadratic Common Lyapunov Function

Annika Fürnsinn, Christian Ebenbauer, Bahman Gharesifard

In this paper, we develop a systematic method for constructing a generalized discrete-time control Lyapunov function for the flexible-step Model Predictive Control (MPC) scheme, re…

math.OC2023

Synthesis of constrained robust feedback policies and model predictive control

Dennis Gramlich, Carsten W. Scherer, Hannah Häring +1

In this work, we develop a method based on robust control techniques to synthesize robust time-varying state-feedback policies for finite, infinite, and receding horizon control pr…

math.OC2023

Optimization Algorithm Synthesis based on Integral Quadratic Constraints: A Tutorial

Carsten W. Scherer, Christian Ebenbauer, Tobias Holicki

We expose in a tutorial fashion the mechanisms which underlie the synthesis of optimization algorithms based on dynamic integral quadratic constraints. We reveal how these tools fr…

math.OC2023

A structure exploiting SDP solver for robust controller synthesis

Dennis Gramlich, Tobias Holicki, Carsten W. Scherer +1

In this paper, we revisit structure exploiting SDP solvers dedicated to the solution of Kalman-Yakubovic-Popov semi-definite programs (KYP-SDPs). These SDPs inherit their name from…

math.OC2023

Convolutional Neural Networks as 2-D systems

Dennis Gramlich, Patricia Pauli, Carsten W. Scherer +2

This paper introduces a novel representation of convolutional Neural Networks (CNNs) in terms of 2-D dynamical systems. To this end, the usual description of convolutional layers w…