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2025 International Conference on Mobile and Miniaturized Terahertz systems, ICMMTS 2025

作者： Jorswieck, Eduard A. Soleymani, Mohammad Santamaria, Ignacio Gutierrez, Jesus Tu Braunschweig Institute for Communications Technology Germany University of Paderborn Signal and System Theory Group Germany University of Cantabria Dept. of Communications Engineering Spain Ihp - Leibniz-Institut für Innovative Mikroelektronik Frankfurt (Oder) Germany

ISBN: (纸本)9798350365832

The challenges in dense ultra-reliable low-latency communication networks to deliver the required service to multiple devices are addressed by three main technologies: multiple antennas at the base station (MISO), rate splitting multiple access (RSMA) with private and common message encoding, and simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). Careful resource allocation, encompassing beamforming and RIS optimization, is required to exploit the synergy between the three. We propose an alternating optimization-based algorithm, relying on minorization-maximization. Numerical results show that the achievable second-order max-min rates of the proposed scheme outperform the baselines significantly. MISO, RSMA, and STAR-RIS all contribute to enabling ultra-reliable low-latency communication (URLLC). © 2025 IEEE.

关键词： BD-RIS Interference Management MAC optimization resource allocation RSMA URLLC Wireless Networks

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Path-Complete Barrier Functions for Safety of Switched Linear systems

Path-Complete Barrier Functions for Safety of Switched Linea...

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IEEE Conference on Decision and Control

作者： Mahathi Anand Raphaël Jungers Majid Zamani Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Germany Department of Mathematical Engineering Université catholique de Louvain University of Colorado Boulder USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we address the safety verification problem of switched linear dynamical systems under arbitrary switching via barrier functions. Our approach is based on a notion of path-complete barrier functions, which utilizes a collection of barrier functions associated with a directed labeled graph that can encode all the possible switching sequences. We show that path-complete barrier functions effectively generalize notions of common and multiple barrier functions studied in existing literature, and can potentially provide less conservative conditions for safety verification. We demonstrate that, for switched linear systems, the inequalities imposed via path-complete barrier functions can be easily encoded into simple linear matrix inequalities under some assumptions on the regions of interest and appropriately chosen templates for the barrier functions. We also study the relationship between path-complete barrier functions and common barrier functions, and show that for any path-complete graph with an admissible path-complete barrier function, one can derive a suitable (possibly non-smooth) common barrier function by utilizing the path-complete barrier function. Finally, we utilize several examples to illustrate the effectiveness of our approach, and briefly discuss the challenges that lay foundations for future research.

关键词： Linear systems Switches Control systems Safety Linear matrix inequalities Dynamical systems

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An $\mathcal{L}_{\mathrm{p}}$ -norm framework for event-triggered control

An $\mathcal{L}_{\mathrm{p}}$ -norm framework for event-trig...

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European Control Conference (ECC)

作者： Michael Hertneck Alejandro I. Maass Dragan Nešić Frank Allgöwer University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart Germany Department of Electrical Engineering Pontificia Universidad Catolica de Chile Santiago Chile Department of Electrical and Electronic Engineering The University of Melbourne Parkville Victoria Australia

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper presents a novel event-triggered control (ETC) design framework based on measured $\mathcal{L}_{p}$ norms. We consider a class of systems with finite $\mathcal{L}_{p}$ gain from the network-induced error to a chosen output. The $\mathcal{L}_{p}$ norms of the network-induced error and the chosen output since the last sampling time are used to formulate a class of triggering rules. Based on a small-gain condition, we derive an explicit expression for the $\mathcal{L}_{p}$ gain of the resulting closed-loop systems and present a time-regularization, which can be used to guarantee a lower bound on the inter-sampling times. The proposed framework is based on a different stability- and triggering concept compared to ETC approaches from the literature, and thus may yield new types of dynamical properties for the closed-loop system. However, for specific output choices it can lead to similar triggering rules as “standard” static and dynamic ETC approaches based on input-to-state stability and yields therefore a novel interpretation for some of the existing triggering rules. We illustrate the proposed framework with a numerical example from the literature.

关键词： Europe Closed loop systems Numerical stability Standards

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Lipschitz-Bounded 1D Convolutional Neural Networks using the Cayley Transform and the Controllability Gramian

Lipschitz-Bounded 1D Convolutional Neural Networks using the...

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IEEE Conference on Decision and Control

作者： Patricia Pauli Ruigang Wang Ian R. Manchester Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Australia

We establish a layer-wise parameterization for 1D convolutional neural networks (CNNs) with built-in end-to-end robustness guarantees. In doing so, we use the Lipschitz constant of the input-output mapping characterized by a CNN as a robustness measure. We base our parameterization on the Cayley transform that parameterizes orthogonal matrices and the controllability Gramian of the state space representation of the convolutional layers. The proposed parameterization by design fulfills linear matrix inequalities that are sufficient for Lipschitz continuity of the CNN, which further enables unconstrained training of Lipschitz-bounded 1D CNNs. Finally, we train Lipschitz-bounded 1D CNNs for the classification of heart arrythmia data and show their improved robustness.

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Construction of Solutions to a Boundary Value Problem with Singularity for a Nonlinear Parabolic system

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Journal of Applied and Industrial Mathematics 2021年第4期15卷 616-626页

作者： Kazakov, A.L. Kuznetsov, P.A. Spevak, L.F. Matrosov Institute for System Dynamics and Control Theory Irkutsk664033 Russia Institute of Engineering Science Ekaterinburg620049 Russia Ural State University of Railway Transport Ekaterinburg620034 Russia

Abstract: We consider a system of two nonlinear second-order parabolic equations with *** of this type are applied in chemical kinetics to describe reaction-diffusion processes. Weprove the existence and uniqueness theorem of an analytic solution having the diffusion-wave typeat a given wave front. The proof is constructive, and the solution had the form of a power serieswith recursively calculated coefficients. Moreover, we propose some numerical algorithm based onthe boundary element method whose verification uses the segments of analytic solutions. © 2021, Pleiades Publishing, Ltd.

关键词： Boundary element method

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Lipschitz-bounded 1D convolutional neural networks using the Cayley transform and the controllability Gramian

arXiv

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arXiv 2023年

作者： Pauli, Patricia Wang, Ruigang Manchester, Ian R. Allgöwer, Frank The Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70569 Germany The Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Australia

关键词： State space methods

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On-Board Pedestrian Trajectory Prediction Using Behavioral Features

On-Board Pedestrian Trajectory Prediction Using Behavioral F...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Phillip Czech Markus Braun Ulrich Kreßel Bin Yang Urban Autonomous Driving Department Mercedes-Benz AG Stuttgart Germany Institute of Signal Processing and System Theory University of Stuttgart Stuttgart Germany

This paper presents a novel approach to pedestrian trajectory prediction for on-board camera systems, which utilizes behavioral features of pedestrians that can be inferred from visual observations. Our proposed method, called Behavior-Aware Pedestrian Trajectory Prediction (BA-PTP), processes multiple input modalities, i.e. bounding boxes, body and head orientation of pedestrians as well as their pose, with independent encoding streams. The encodings of each stream are fused using a modality attention mechanism, resulting in a final embedding that is used to predict future bounding boxes in the *** experiments on two datasets for pedestrian behavior prediction, we demonstrate the benefit of using behavioral features for pedestrian trajectory prediction and evaluate the effectiveness of the proposed encoding strategy. Additionally, we investigate the relevance of different behavioral features on the prediction performance based on an ablation study.

关键词： Visualization Head Image coding Machine learning Predictive models Streaming media Encoding

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ExANT: Exploring NLP AI systems for Requirements Development 74

ExANT: Exploring NLP AI Systems for Requirements Development

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74th International Astronautical Congress, IAC 2023

作者： Ehresmann, Manfred Beyer, Julian Fasoulas, Stefanos Schorfmann, Martin Brudna, Timon Schoolmann, Ingo Brüggmann, Jörg Hönle, Alfred Gerlich, Ralf Gerlich, Rainer Institute of Space Systems University of Stuttgart Pfaffenwaldring 29 Stuttgart70569 Germany OHB Digital Services GmbH Konrad-Zuse-Str.8 Bremen28359 Germany OHB System AG Universitätsallee 27-29 Bremen28359 Germany Dr. Rainer Gerlich System and Software Engineering GSSE Auf dem Ruhbuehl 181 ImmenstaadD-88090 Germany

In spacecraft development, initial customer requirements are refined through subsequent engineering phases to meet specific subsystem and operational needs. However, the dynamic nature of requirements, influenced by evolving engineering processes and customer demands, poses challenges. Ensuring requirement quality, interpreting changes, and tracking them can be demanding, especially in larger teams or multi-organization projects. This can lead to prolonged development times, escalated costs, and the risk of incorrect implementations. The ExANT (Extraction of Requirements from Natural Language Texts) project employs natural language processing (NLP) and artificial intelligence (AI) to automate requirement development. The goal is to create an AI system that can automatically analyse requirement texts, assess quality, and suggest enhancements and in the long run enable automated testing of software requirements. This paper updates the project's progress, comparing commercially available tools like IBM Watson with open-source alternatives such as spaCy for processing software requirements. The project focuses on spacecraft-related software requirements, aiming to narrow the domain knowledge needed for NLP AI training. Real-world requirements provided by OHB system, a European large system integrator, and artificially generated requirements using OpenAI's ChatGPT to enrich the dataset are explored. Human annotation is essential for processing software requirement texts, enabling supervised training for named entity recognition (NER). Collaboratively developed entity types and annotation guidelines enables consistent NER training. An AI system, aided by annotated data, becomes skilled at recognizing entities in similar texts. Patterns, quantities, and entity relationships contribute to an assessment pipeline for requirement quality. The ExANT project, involving GSSE, OHB system AG, OHB Digital Services GmbH, and the institute of Space systems at the university of Stuttga

关键词： Artificial Intelligence Natural Language Processing Requirements engineering

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Enhancing Safety of Power Supply systems in Automotive Applications: Integrating Functional Safety (FuSa) and Safety of the Intended Functionality (SOTIF)

Enhancing Safety of Power Supply Systems in Automotive Appli...

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International Conference on system Reliability and Science (ICSRS)

作者： Zhiyi Xu Armin J. Köhler Tobias Christian Traub Martin Dazer Engineering Vehicle Systems (XC-CE/EPP1) Robert Bosch GmbH Stuttgart Germany Engineering System Architecture (XC/EYA3) Robert Bosch GmbH Stuttgart Germany Institute of Machine Components - Reliability Technology University of Stuttgart Stuttgart Germany

ISBN: (数字)9798350354508

ISBN: (纸本)9798350354515

The automotive industry's development towards electrification and automation raises special attention to Safety-Related Availability (SaRA) of onboard power supply systems (powernets). This paper provides insights into the current state of safety development for powernets and highlights the challenges in the safety argumentation for batteries. Our key contributions are twofold: First, we synchronize FuSa and SOTIF safety processes to manage intricate interactions and enhance reusability. We present a case study demonstrating how this integrated process is applied to powernets. Second, we extend the application of SOTIF to low-level complex safety measures, such as battery diagnosis, as a supplement to the high-level functional safety concept. We further discuss the applicability of SOTIF to battery diagnosis and specifically focus on deriving acceptance criteria, identifying functional insufficiencies, defining triggering conditions, and comparing various validation methods. Despite the differences from AD/ADAS, SOTIF's goal to mitigate potential risks resulting from functional insufficiencies remains applicable to battery diagnosis. Finally, we propose a safety validation framework combining sensitivity analysis, probabilistic surrogate models, and importance sampling to provide quantitative safety argumentation. This paper primarily focuses on theoretical analysis and is intended to lay a robust theoretical foundation for power supply safety.

关键词： Monte Carlo methods Power supplies Sensitivity analysis Vehicle safety Electrification Probabilistic logic Safety Batteries Synchronization Reliability

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Deep Open Set Recognition Using Dynamic Intra-class Splitting

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SN Computer Science 2020年第2期1卷 1-12页

作者： Schlachter, Patrick Liao, Yiwen Yang, Bin Institute of Signal Processing and System Theory University of Stuttgart Pfaffenwaldring 47 Stuttgart 70550 Germany

This paper provides a generic deep learning method to solve open set recognition problems. In open set recognition, only samples of a limited number of known classes are given for training. During inference, an open set recognizer must not only correctly classify samples from known classes, but also reject samples from unknown classes. Due to these specific requirements, conventional deep learning models that assume a closed set environment cannot be used. Therefore, special open set approaches were taken, including variants of support vector machines and generation-based state-of-the-art methods which model unknown classes by generated samples. In contrast, our proposed method models unknown classes by atypical subsets of training samples. The subsets are obtained through intra-class splitting (ICS). Based on a recently proposed two-stage algorithm using ICS, we propose a one-stage method based on alternating between ICS and the training of a deep neural network. Finally, several experiments were conducted to compare our proposed method with conventional and other state-of-the-art methods. The proposed method based on dynamic ICS showed a comparable or better performance than all considered existing methods regarding balanced accuracy. © 2020, The Author(s).

关键词： Deep learning Dynamic intra-class splitting End-to-end Open set recognition

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