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20152022
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10 papers · 1 filter

math.OC2022

Robust Differential Dynamic Programming

Dennis Gramlich, Carsten W. Scherer, Christian Ebenbauer

Differential Dynamic Programming is an optimal control technique often used for trajectory generation. Many variations of this algorithm have been developed in the literature, incl…

math.OC2022

Extremum Seeking with Intermittent Measurements: A Lie-brackets Approach

Christophe Labar, Christian Ebenbauer, Lorenzo Marconi

Extremum seeking systems are powerful methods able to steer the input of a (dynamical) cost function towards an optimizer, without any prior knowledge of the cost function. To achi…

math.OC2021

A Note on Nussbaum-type Control and Lie-bracket Approximation

Marc Weber, Christian Ebenbauer, Bahman Gharesifard

In this paper, we propose an adaptive control law for completely unknown scalar linear systems based on Lie-bracket approximation methods. We investigate stability and convergence…

math.OC2021

Convex Synthesis of Accelerated Gradient Algorithms

Carsten Scherer, Christian Ebenbauer

We present a convex solution for the design of generalized accelerated gradient algorithms for strongly convex objective functions with Lipschitz continuous gradients. We utilize i…

math.OC2020

Convex Synthesis of Accelerated Gradient Algorithms for Optimization and Saddle Point Problems using Lyapunov functions

Dennis Gramlich, Christian Ebenbauer, Carsten W. Scherer

This paper considers the problem of designing accelerated gradient-based algorithms for optimization and saddle-point problems. The class of objective functions is defined by a gen…

math.OC2018

Online learning with stability guarantees: A memory-based real-time model predictive controller

Lukas Schwenkel, Meriem Gharbi, Sebastian Trimpe +1

We propose and analyze a real-time model predictive control (MPC) scheme that utilizes stored data to improve its performance by learning the value function online with stability g…