Search Results for author: Martin Horn

Found 13 papers, 1 papers with code

Stochastic Model Predictive Control for Networked Systems with Random Delays and Packet Losses in All Channels

no code implementations4 Sep 2023 Marijan Palmisano, Martin Steinberger, Martin Horn

A stochastic Model Predictive Control strategy for control systems with communication networks between the sensor node and the controller and between the controller and the actuator node is proposed.

Model Predictive Control

Modified Implicit Discretization of the Super-Twisting Controller

no code implementations27 Mar 2023 Benedikt Andritsch, Lars Watermann, Stefan Koch, Markus Reichhartinger, Johann Reger, Martin Horn

The continuous-time super-twisting controller is capable of rejecting any unknown Lipschitz-continuous perturbation and converges in finite time.

Control-oriented modeling of a LiBr/H2O absorption heat pumping device and experimental validation

no code implementations27 Mar 2023 Sandra Staudt, Viktor Unterberger, Markus Gölles, Michael Wernhart, René Rieberer, Martin Horn

The presented new modeling approach is considered suitable to be used as a basis for the design of advanced, model-based control strategies, ultimately aiming to improve the modulation and part load capability of AHPDs.

Model Predictive Control

Switched Lyapunov Function based Controller Synthesis for Networked Control Systems: A Computationally Inexpensive Approach

no code implementations2 Mar 2023 Katarina Stanojevic, Martin Steinberger, Martin Horn

This paper presents a Lyapunov function based control strategy for networked control systems (NCS) affected by variable time delays and data loss.

Computational Efficiency

Unknown Input Observer Design for Linear Time-Invariant Systems -- A Unifying Framework

no code implementations29 Nov 2021 Markus Tranninger, Helmut Niederwieser, Richard Seeber, Martin Horn

This paper presents a new observer design approach for linear time invariant multivariable systems subject to unknown inputs.

Detectability Conditions and State Estimation for Linear Time-Varying and Nonlinear Systems

no code implementations25 Jun 2021 Markus Tranninger, Richard Seeber, Martin Steinberger, Martin Horn, Christian Pötzsche

This work proposes a detectability condition for linear time-varying systems based on the exponential dichotomy spectrum.

A Non-Conservative Stability Criterion for Networked Control Systems with time-varying Packet Delays

no code implementations30 Mar 2021 Martin Steinberger, Martin Horn

A networked output feedback loop subject to packetized transmissions of the output signal is considered.

Strong Detectability and Observers for Linear Time Varying Systems

no code implementations23 Mar 2021 Markus Tranninger, Richard Seeber, Juan G. Rueda-Escobedo, Martin Horn

This work presents a notion of strong detectability for linear time varying systems affected by unknown inputs.

Robust exact differentiators with predefined convergence time

no code implementations25 May 2020 Richard Seeber, Hernan Haimovich, Martin Horn, Leonid Fridman, Hernán De Battista

A class of differentiators is proposed, which converge to the derivative of such a signal within a fixed, i. e., a finite and uniformly bounded convergence time.

Learning a Behavior Model of Hybrid Systems Through Combining Model-Based Testing and Machine Learning (Full Version)

no code implementations10 Jul 2019 Bernhard K. Aichernig, Roderick Bloem, Masoud Ebrahimi, Martin Horn, Franz Pernkopf, Wolfgang Roth, Astrid Rupp, Martin Tappler, Markus Tranninger

Therefore, there is considerable interest in learning such hybrid behavior by means of machine learning which requires sufficient and representative training data covering the behavior of the physical system adequately.

BIG-bench Machine Learning

Safe learning-based optimal motion planning for automated driving

no code implementations25 May 2018 Zlatan Ajanovic, Bakir Lacevic, Georg Stettinger, Daniel Watzenig, Martin Horn

This paper presents preliminary work on learning the search heuristic for the optimal motion planning for automated driving in urban traffic.

BIG-bench Machine Learning Motion Planning +1

A novel model-based heuristic for energy optimal motion planning for automated driving

no code implementations11 Dec 2017 Zlatan Ajanovic, Michael Stolz, Martin Horn

Although planning of an optimal trajectory is done in a systematic way, dynamic programming does not use any knowledge about the considered problem to guide the exploration and therefore explores all possible trajectories.

Motion Planning Optimal Motion Planning

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