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This work mainly addresses continuous-time multiagent consensus networks where an adverse attacker affects the convergence performances of said protocol. In particular, we develop a novel secure-by-design approach in which the presence of a…

Systems and Control · Electrical Eng. & Systems 2025-01-30 Marco Fabris , Daniel Zelazo

When designing optimal controllers for any system, it is often the case that the true state of the system is unknown to the controller, for example due to noisy measurements or partially observable states. Incomplete state information must…

Optimization and Control · Mathematics 2014-01-23 Kendra Lesser , Meeko Oishi

This article addresses the problem of average consensus in a multi-agent system when the desired consensus quantity is a time varying signal. Recently, the EDCHO protocol leveraged high order sliding modes to achieve exact consensus under a…

Systems and Control · Electrical Eng. & Systems 2022-05-26 Rodrigo Aldana-López , Rosario Aragüés , Carlos Sagüés

Robust optimization is a young and active research field that has been mainly developed in the last 15 years. Robust optimization is very useful for practice, since it is tailored to the information at hand, and it leads to computationally…

Optimization and Control · Mathematics 2015-08-21 Bram L. Gorissen , Ihsan Yanıkoğlu , Dick den Hertog

Ultra-reliable and low-latency communications (URLLC) is an emerging feature in 5G and beyond wireless systems, which is introduced to support stringent latency and reliability requirements of mission-critical industrial applications. In…

Signal Processing · Electrical Eng. & Systems 2018-07-03 Aamir Mahmood , Muhammad Ikram Ashraf , Mikael Gidlund , Johan Torsner

This paper presents, in a unified fashion, deterministic as well as statistical Lagrangian-verification techniques. They formally quantify the behavioral robustness of any time-continuous process, formulated as a continuous-depth model. To…

Machine Learning · Computer Science 2023-08-24 Sophie A. Neubauer , Radu Grosu

Based on existing ideas in the field of imprecise probabilities, we present a new approach for assessing the reliability of the individual predictions of a generative probabilistic classifier. We call this approach robustness…

Machine Learning · Computer Science 2025-04-11 Adrián Detavernier , Jasper De Bock

In this work, we analyze an efficient sampling-based algorithm for general-purpose reachability analysis, which remains a notoriously challenging problem with applications ranging from neural network verification to safety analysis of…

Systems and Control · Electrical Eng. & Systems 2022-04-15 Thomas Lew , Lucas Janson , Riccardo Bonalli , Marco Pavone

As reinforcement learning (RL) has achieved great success and been even adopted in safety-critical domains such as autonomous vehicles, a range of empirical studies have been conducted to improve its robustness against adversarial attacks.…

Machine Learning · Computer Science 2022-03-17 Fan Wu , Linyi Li , Zijian Huang , Yevgeniy Vorobeychik , Ding Zhao , Bo Li

With the development of mobile communication and industrial internet technologies, the demand for robust absolute time synchronization based on network for diverse scenarios is significantly growing. TAP is a novel network timing method…

Networking and Internet Architecture · Computer Science 2024-02-08 Chenyu Zhang , Xiangming Wen , Wei Zheng , Longdan Yu , Zhaoming Lu , Zhengying Wang

In contrast to electronic computation, chemical computation is noisy and susceptible to a variety of sources of error, which has prevented the construction of robust complex systems. To be effective, chemical algorithms must be designed…

Data Structures and Algorithms · Computer Science 2019-08-19 Dan Alistarh , Bartłomiej Dudek , Adrian Kosowski , David Soloveichik , Przemysław Uznański

Reachability computations that rely on learned or estimated models require calibration in order to uphold confidence about their guarantees. Calibration generally involves sampling scenarios inside the reachable set. However, producing…

Systems and Control · Electrical Eng. & Systems 2026-03-27 Sampada Deglurkar , Ebonye Smith , Jingqi Li , Claire J. Tomlin

Robustness is a critical aspect of machine learning models. Existing robustness evaluation approaches often lack theoretical generality or rely heavily on empirical assessments, limiting insights into the structural factors contributing to…

Machine Learning · Computer Science 2024-11-26 Baiyuan Chen

In real world applications, uncertain parameters are the rule rather than the exception. We present a reachability algorithm for linear systems with uncertain parameters and inputs using set propagation of polynomial zonotopes. In contrast…

Systems and Control · Electrical Eng. & Systems 2024-06-18 Yushen Huang , Ertai Luo , Stanley Bak , Yifan Sun

To analyze complex and heterogeneous real-time embedded systems, recent works have proposed interface techniques between real-time calculus (RTC) and timed automata (TA), in order to take advantage of the strengths of each technique for…

Performance · Computer Science 2010-06-29 Karine Altisen , Yanhong Liu , Matthieu Moy

To analyze complex and heterogeneous real-time embedded systems, recent works have proposed interface techniques between real-time calculus (RTC) and timed automata (TA), in order to take advantage of the strengths of each technique for…

Performance · Computer Science 2010-04-16 Karine Altisen , Yanhong Liu , Matthieu Moy

We introduce Harmonic Robustness, a powerful and intuitive method to test the robustness of any machine-learning model either during training or in black-box real-time inference monitoring without ground-truth labels. It is based on…

Machine Learning · Computer Science 2024-04-30 Nicholas S. Kersting , Yi Li , Aman Mohanty , Oyindamola Obisesan , Raphael Okochu

We consider multi-robot systems under recurring tasks formalized as linear temporal logic (LTL) specifications. To solve the planning problem efficiently, we propose a bottom-up approach combining offline plan synthesis with online…

The current algorithms are based on linear model, for example, Precision Time Protocol (PTP) which requires frequent synchronization in order to handle the effects of clock frequency drift. This paper introduces a nonlinear approach to…

Machine Learning · Computer Science 2019-03-05 Frank Wang , Danjue Li

Global protocol specifications are the starting point of top-down verification methodologies, and serve as a blueprint for synthesizing local specifications that guarantee the correctness of distributed implementations. In this work, we…

Formal Languages and Automata Theory · Computer Science 2026-02-11 Elaine Li , Felix Stutz