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arXiv 2025年

作者： Blath, Jochen Tóbiás, András Goethe-Universität Frankfurt Robert-Mayer-Straße 10 Frankfurt am Main60325 Germany Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary HUN-REN Alfréd Rényi Institute of Mathematics Reáltanoda utca 13–15 BudapestH-1053 Hungary

We study a minimal stochastic individual-based model for a microbial population challenged by a persistent (lytic) virus epidemic. We focus on the situation in which the resident microbial host population and the virus population are in stable coexistence upon arrival of a single new "mutant" host individual. We assume that this mutant is capable of switching to a reversible state of dormancy upon contact with virions as a means of avoiding infection by the virus. At the same time, we assume that this new dormancy trait comes with a cost, namely a reduced individual reproduction rate. We prove that there is a non-trivial range of parameters where the mutants can nevertheless invade the resident population with with strictly positive probability (bounded away from 0) in the large population limit. Given the reduced reproductive rate, such an invasion would be impossible in the absence of either the dormancy trait or the virus epidemic. We explicitly characterize the parameter regime where this emergence of a (costly) host dormancy trait is possible, determine the success probability of a single invader and the typical amount of time it takes the successful mutants to reach a macroscopic population size. We conclude this study by an investigation of the fate of the population after the successful emergence of a dormancy trait. Heuristic arguments and simulations suggest that after successful invasion, either both host types and the virus will reach coexistence, or the mutants will drive the resident hosts to extinction while the virus will stay in the *** Codes 92D25, 60J85, 34D05, 37G15 Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic models

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Gaussian-Process-Based Adaptive Trajectory Tracking control for Autonomous Ground Vehicles

Gaussian-Process-Based Adaptive Trajectory Tracking Control ...

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European control Conference (ECC)

作者： Kristóf Floch Tamás Péni Roland Tóth Systems and Control Lab HUN-REN Inst. for Computer Science and Control Budapest Hungary Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper proposes an adaptive trajectory tracking control algorithm for autonomous ground vehicles. The nonlinear vehicle dynamics are decoupled into two subsystems corresponding to the longitudinal and lateral motions. Each subsystem is augmented with a Gaussian Process to compensate for modeling errors and external disturbances. Based on the augmented subsystems, adaptive control algorithms are synthesized. To give a mathematically correct performance measure, the induced $\mathcal{L}_2$ -gain of the nonlinear closed-loop system is computed. The efficiency of the learning-based control method is demonstrated on a high-fidelity physical simulator using a digital twin model of the 1/10 scale F1TENTH vehicle platform.

关键词： Adaptation models Uncertainty Trajectory tracking Heuristic algorithms Computational modeling Mathematical models Land vehicles

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Cybersecurity and Autonomous Driving: Experiments with LiDAR Sensor Spoofing

Cybersecurity and Autonomous Driving: Experiments with LiDAR...

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Communications, Information, Electronic and Energy Systems (CIEES), International Conference on

作者： Ernő Rigó Péter Árvai Valéria Póser Institute for Computer Science and Control (SZTAKI) Hungarian Research Network (HUN-REN) Budapest Hungary Biomatics and Applied Artificial Intelligence Institute Óbuda University Budapest Hungary

ISBN: (数字)9798350352863

ISBN: (纸本)9798350352870

This research investigates the vulnerability of onboard navigation sensors in autonomous vehicles to cybersecurity attacks. By exploiting the interconnectedness of these systems, adversaries can manipulate sensor data, compromise software, or physically interfere with sensors, potentially leading to serious consequences. This study describes cybersecurity experiments on a hardware-in-the-loop autonomous vehicle testbed, focusing on cyberattacks against LiDAR-based navigation, exploring various attack vectors, including jamming and various methods of spoofing. Experimental results demonstrate the feasibility of these attacks and highlight the need for robust security measures to protect autonomous vehicles from cyber threats. The findings emphasize the importance of ongoing research in developing effective countermeasures to ensure the safety and reliability of autonomous driving systems.

关键词： Laser radar Navigation Sensor systems Vectors Software Sensors Safety Reliability computer crime Autonomous vehicles

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No Tiling of the 70×70 Square with Consecutive Squares 12

No Tiling of the 70×70 Square with Consecutive Squares

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12th International Conference on Fun with Algorithms, FUN 2024

作者： Sgall, Jiří Balogh, János Békési, József Dósa, György Hvattum, Lars Magnus Tuza, Zsolt Computer Science Institute of Charles University Faculty of Mathematics and Physics Prague Czech Republic University of Szeged Hungary University of Pannonia Veszprém Hungary Molde University College Norway HUN-REN Alfréd Rényi Institute of Mathematics Budapest Hungary

ISBN: (纸本)9783959773140

The total area of the 24 squares of sizes 1, 2, . . ., 24 is equal to the area of the 70 × 70 square. Can this equation be demonstrated by a tiling of the 70 × 70 square with the 24 squares of sizes 1, 2, . . ., 24? The answer is "NO", no such tiling exists. This has been demonstrated by computer search. However, until now, no proof without use of computer was given. We fill this gap and give a complete combinatorial proof. © Jiří Sgall, János Balogh, József Békési, György Dósa, Lars Magnus Hvattum, and Zsolt Tuza.

关键词： combinatorial proof Gardner’s problem square packing

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Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear Systems ⁎

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IFAC-PapersOnLine 2024年第15期58卷 265-270页

作者： Patrick J.W. Koelewijn Rajiv Singh Peter Seiler Roland Tóth Sioux Technologies B.V. Eindhoven The Netherlands Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands The MathWorks Inc. Natick USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor USA Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples.

关键词： Reduced-order modeling Neural Networks Linear Parameter-Varying Models

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A general modeling and simulation framework for dynamic vehicle routing

arXiv

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arXiv 2024年

作者： Horváth, Markó Tamási, Tímea HUN-REN Institute for Computer Science and Control Budapest Hungary Department of Operations Research Institute of Mathematics ELTE Eötvös Loránd University Budapest Hungary

In dynamic vehicle routing problems (DVRPs), some part of the information is revealed or changed on the fly, and the decision maker has the opportunity to re-plan the vehicle routes during their execution, reflecting on the changes. Accordingly, the solution to a DVRP is a flexible policy rather than a set of fixed routes. A policy is basically a problem-specific algorithm that is invoked at various decision points in the planning horizon and returns a decision according to the current state. Since DVRPs involve dynamic decision making, a simulator is an essential tool for dynamically testing and evaluating the policies. Despite this, there are few tools available that are specifically designed for this purpose. To fill this gap, we have developed a simulation framework that is suitable for a wide range of dynamic vehicle routing problems and allows to dynamically test different policies for the given problem. In this paper, we present the background of this simulation tool, for which we proposed a general modeling framework suitable for formalizing DVRPs independently of simulation purposes. Our open source simulation tool is already available, easy to use, and easily customizable, making it a useful tool for the research community. © 2024, CC BY.

关键词： Vehicle routing

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Nonparametric control Koopman Operators

arXiv

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arXiv 2024年

作者： Bevanda, Petar Driessen, Bas Iacob, Lucian Cristian Sosnowski, Stefan Tóth, Roland Hirche, Sandra Chair of Information-oriented Control TU München Germany Control Systems Group TU/e Eindhoven Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

This paper presents a novel Koopman (composition) operator representation framework for control systems in reproducing kernel Hilbert spaces (RKHSs) that is free of explicit dictionary or input parametrizations. By establishing fundamental equivalences between different model representations, we are able to close the gap of control system operator learning and infinite-dimensional regression, enabling various empirical estimators and the connection to well-understood learning theory in RKHSs under one unified framework. As a consequence, our proposed framework allows for arbitrary accurate finite-rank approximations in infinite-dimensional spaces and leads to finite-dimensional predictors without apriori restrictions to a finite span of functions or inputs. To enable applications to high-dimensional control systems, we improve the scalability of our proposed control Koopman operator estimates by utilizing sketching techniques. Numerical experiments demonstrate superior prediction accuracy compared to bilinear EDMD, especially in high dimensions. Finally, we show that our learned models are readily interfaced with linear-parameter-varying techniques for model predictive control. Copyright © 2024, The Authors. All rights reserved.

关键词： Predictive control systems

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Decoupling parameter variation from noise: Biquadratic Lyapunov forms in data-driven LPV control

arXiv

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arXiv 2024年

作者： Verhoek, Chris Eising, Jaap Dörfler, Florian Tóth, Roland Control Systems Group Eindhoven University of Technology Netherlands Institut für Automatik ETH Zürich Switzerland Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Hungary

A promising step from linear towards nonlinear data-driven control is via the design of controllers for linear parameter-varying (LPV) systems, which are linear systems whose parameters are varying along a measurable scheduling signal. However, the interplay between uncertainty arising from corrupted data and the parameter-varying nature of these systems impacts the stability analysis and limits the generalization of well-understood data-driven methods available for linear time-invariant systems. In this work, we decouple this interplay using a recently developed variant of the Fundamental Lemma for LPV systems and the concept of data-informativity, in combination with biquadratic Lyapunov forms. Together, these allow us to develop novel linear matrix inequality conditions for the existence of scheduling-dependent Lyapunov functions, incorporating the intrinsic nonlinearity. Appealingly, these results are stated purely in terms of the collected data and bounds on the noise, and they are computationally favorable to check. © 2024, CC BY-NC-SA.

关键词： Lyapunov functions

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Decoupling parameter variation from noise: Biquadratic Lyapunov forms in data-driven LPV control

Decoupling parameter variation from noise: Biquadratic Lyapu...

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IEEE Conference on Decision and control

作者： Chris Verhoek Jaap Eising Florian Dörfler Roland Tóth Control Systems Group Eindhoven University of Technology The Netherlands Institut für Automatik ETH Zürich Switzerland Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Hungary

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

关键词： Linear systems Uncertainty Noise Stability analysis Robustness Trajectory Linear matrix inequalities Noise measurement Output feedback Lyapunov methods

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A Non-Parametric Identification Scheme of SISO-LTI Systems Using Blaschke-Products*

A Non-Parametric Identification Scheme of SISO-LTI Systems U...

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Mediterranean Conference on control and Automation (MED)

作者： Gergő Ungvári Alexandros Soumelidis Tamás Dózsa Department of Numerical Analysis Faculty of Informatics Eötvös Loránd University Budapest Hungary Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

In this manuscript, a novel algorithm is presented for the identification of single input single output linear time invariant (SISO-LTI) systems. The proposed method is able to find poles of the transfer function describing the system without any assumptions on the system order. The results presented in this paper generalize earlier identification schemes based on expansions of the transfer function using generalized rational orthogonal basis functions (GOBFs). These previous methods depended on a convergent sequence constructed from the coefficients of the orthogonal GOBF expansion. The first contribution of this study is showing that a wider family of functions may be used to construct similar pole finding algorithms. The aforementioned previous approaches can be interpreted as special cases of the results presented here. In addition, using this generalization a new pole identification scheme is proposed using finite Blaschke-products. Through experiments, the practical utility of this scheme is verified when compared to earlier variations of the pole finding scheme.

关键词： Automation Transfer functions

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