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pro vyhledávání: '"Nonhoff, Marko"'
This article investigates the problem of controlling linear time-invariant systems subject to time-varying and a priori unknown cost functions, state and input constraints, and exogenous disturbances. We combine the online convex optimization framewo
Externí odkaz:
http://arxiv.org/abs/2401.04487
In this work, we propose a control scheme for linear systems subject to pointwise in time state and input constraints that aims to minimize time-varying and a priori unknown cost functions. The proposed controller is based on online convex optimizati
Externí odkaz:
http://arxiv.org/abs/2211.09088
Autor:
Nonhoff, Marko, Müller, Matthias A.
Publikováno v:
Systems & Control Letters 177 (2023)
In this work, we study the relations between bounded dynamic regret and the classical notion of asymptotic stability for the case of a priori unknown and time-varying cost functions. In particular, we show that bounded dynamic regret implies asymptot
Externí odkaz:
http://arxiv.org/abs/2209.05964
Autor:
Nonhoff, Marko, Müller, Matthias A.
We propose an algorithm based on online convex optimization for controlling discrete-time linear dynamical systems. The algorithm is data-driven, i.e., does not require a model of the system, and is able to handle a priori unknown and time-varying co
Externí odkaz:
http://arxiv.org/abs/2204.13680
Autor:
Nonhoff, Marko, Müller, Matthias A.
We propose a data-driven online convex optimization algorithm for controlling dynamical systems. In particular, the control scheme makes use of an initially measured input-output trajectory and behavioral systems theory which enable it to handle unkn
Externí odkaz:
http://arxiv.org/abs/2103.09127
Autor:
Nonhoff, Marko, Müller, Matthias A.
Publikováno v:
In Proc. American Control Conference (ACC), 2021, pp. 2523-2528
This paper studies the problem of controlling linear dynamical systems subject to point-wise-in-time constraints. We present an algorithm similar to online gradient descent, that can handle time-varying and a priori unknown convex cost functions whil
Externí odkaz:
http://arxiv.org/abs/2005.11308
Autor:
Nonhoff, Marko, Müller, Matthias A.
Publikováno v:
IFAC-PapersOnLine, vol. 53, no. 2, pp. 942-952, 2020
In this paper, online convex optimization is applied to the problem of controlling linear dynamical systems. An algorithm similar to online gradient descent, which can handle time-varying and unknown cost functions, is proposed. Then, performance gua
Externí odkaz:
http://arxiv.org/abs/1912.09311
Publikováno v:
In Proc. IEEE 58th Conference on Decision and Control (CDC), 2019, pp. 8329-8334
In this work, the control of snake robot locomotion via economic model predictive control (MPC) is studied. Only very few examples of applications of MPC to snake robots exist and rigorous proofs for recursive feasibility and convergence are missing.
Externí odkaz:
http://arxiv.org/abs/1909.00795
Autor:
Nonhoff, Marko, Müller, Matthias A.
Publikováno v:
In Systems & Control Letters July 2023 177
Publikováno v:
In IFAC PapersOnLine 2023 56(2):2570-2575