Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Schwenkel, Lukas"'
In this paper, we investigate discounted economic model predictive control (E-MPC) schemes without terminal conditions in scenarios where the optimal operating behavior is a periodic orbit. For such a setting, it is known that a linearly discounted s
Externí odkaz:
http://arxiv.org/abs/2405.14361
Predictive safety filters enable the integration of potentially unsafe learning-based control approaches and humans into safety-critical systems. In addition to simple constraint satisfaction, many control problems involve additional stability requir
Externí odkaz:
http://arxiv.org/abs/2404.05496
This work provides a framework to compute an upper bound on the robust peak-to-peak gain of discrete-time uncertain linear systems using integral quadratic constraints (IQCs). Such bounds are of particular interest in the computation of reachable set
Externí odkaz:
http://arxiv.org/abs/2211.09434
Publikováno v:
Automatica, Volume 159, 2024, pp. 111393
In this work, we study economic model predictive control (MPC) in situations where the optimal operating behavior is periodic. In such a setting, the performance of a standard economic MPC scheme without terminal conditions can generally be far from
Externí odkaz:
http://arxiv.org/abs/2205.03118
In this work, we propose a tube-based MPC scheme for state- and input-constrained linear systems subject to dynamic uncertainties characterized by dynamic integral quadratic constraints (IQCs). In particular, we extend the framework of $\rho$-hard IQ
Externí odkaz:
http://arxiv.org/abs/2104.05444
Publikováno v:
In Automatica January 2024 159
Publikováno v:
IFAC-PapersOnLine Volume 54, Issue 6, 2021, Pages 28-35
In this paper, we provide non-averaged and transient performance guarantees for recently developed, tube-based robust economic model predictive control (MPC) schemes. In particular, we consider both tube-based MPC schemes with and without terminal co
Externí odkaz:
http://arxiv.org/abs/2102.09404
Autor:
Köhler, Johannes, Schwenkel, Lukas, Koch, Anne, Berberich, Julian, Pauli, Patricia, Allgöwer, Frank
Publikováno v:
Annual Reviews in Control (2020)
We investigate adaptive strategies to robustly and optimally control the COVID-19 pandemic via social distancing measures based on the example of Germany. Our goal is to minimize the number of fatalities over the course of two years without inducing
Externí odkaz:
http://arxiv.org/abs/2005.03580
In this paper, a novel tube-based economic Model Predictive Control (MPC) scheme for uncertain systems that uses neither terminal costs nor terminal constraints is investigated. We show that the results from the undisturbed case can be extended to sy
Externí odkaz:
http://arxiv.org/abs/1911.12235
Publikováno v:
Automatica, Volume 122, 109247, 2020
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 guarantees. For linear and nonlinear systems, a learning method is pres
Externí odkaz:
http://arxiv.org/abs/1812.09582