IFAC-PapersOnLine最新文献

{"title":"Security Metrics for Uncertain Interconnected Systems under Stealthy Data Injection Attacks⁎","authors":"Anh Tung Nguyen ,&nbsp;Sribalaji C. Anand ,&nbsp;André M.H. Teixeira","doi":"10.1016/j.ifacol.2025.07.063","DOIUrl":"10.1016/j.ifacol.2025.07.063","url":null,"abstract":"<div><div>This paper quantifies the security of uncertain interconnected systems under stealthy data injection attacks. In particular, we consider a large-scale system composed of a certain subsystem interconnected with an uncertain subsystem, where only the input-output channels are accessible. An adversary is assumed to inject false data to maximize the performance loss of the certain subsystem while remaining undetected. By abstracting the uncertain subsystem as a class of admissible systems satisfying an L₂ gain constraint, the worst-case performance loss is obtained as the solution to a convex semi-definite program depending only on the certain subsystem dynamics and such an L₂ gain constraint. This solution is proved to serve as an upper bound for the actual worst-case performance loss when the model of the entire system is fully certain. The results are demonstrated through numerical simulations of the power transmission grid spanning Sweden and Northern Denmark.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 4","pages":"Pages 169-174"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity Analysis for Network LQG Mean-Field Games: A Graphon Limit Approach","authors":"Tao Zhang ,&nbsp;Shuang Gao ,&nbsp;Peter E. Caines","doi":"10.1016/j.ifacol.2025.07.055","DOIUrl":"10.1016/j.ifacol.2025.07.055","url":null,"abstract":"<div><div>This paper provides the sensitivity analysis of Linear Quadratic Gaussian graphon mean-field games (LQG-GMFG), with a particular focus on how perturbations in initial conditions at different network locations affect system behavior. We quantify the impact of localized perturbations through a <em>L</em>²-perturbation metric via graphon spectral decompositions and establish explicit solutions for the perturbation analysis that reveal how network topology influences perturbation propagation patterns. Our theoretical results reveal fundamental connections among network topology, system dynamics, and sensitivity patterns, providing insights for robust network design and control strategies.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 4","pages":"Pages 121-126"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved Q-Learning-Based Path Planning Method for Unmanned Surface Vehicles Using Electronic Navigational Chart","authors":"Qingyu Zhao ,&nbsp;Lu Liu ,&nbsp;Guojie Ma ,&nbsp;Yanping Xu ,&nbsp;Hongye Gu ,&nbsp;Zhouhua Peng","doi":"10.1016/j.ifacol.2025.07.071","DOIUrl":"10.1016/j.ifacol.2025.07.071","url":null,"abstract":"<div><div>This paper proposes an improved Q-learning-based path planning method for unmanned surface vehicle (USV) in obstacle-dense marine environments using electronic navigational chart (ENC). First, a dynamic reward function integrating safety distance constraints and directional exploration is designed, ensuring efficient navigation towards the target destination while enabling safe obstacle avoidance. Second, a path short-cutting strategy based on Bresenham algorithm is introduced to eliminate redundant nodes on the path, improving the conciseness of the path. Third, a path expansion method based on the planned path is proposed to expand a single path into multiple paths. Simulation results demonstrate the feasibility of the proposed method.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 4","pages":"Pages 216-221"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Dynamic Prioritization Algorithm For Digital Concept Mapping Games⁎","authors":"Andrea Mutti ,&nbsp;Damiano Varagnolo","doi":"10.1016/j.ifacol.2025.08.043","DOIUrl":"10.1016/j.ifacol.2025.08.043","url":null,"abstract":"<div><div>We consider the problem of optimizing the time-aspect of the user experience of learners that use digital mapping games for enhancing their metacognition levels about some specific material. More precisely, we assume that students shall perform mapping tasks using an IT tool that asks users to visually organize some specific logical relations among course topics. The goal of the learners is to ideally reconstruct a map that their teacher built beforehand as a reference one. To do so, they interact with a graphical user interface that displays a subset of topics within the course, and asks them to establish connections between such topics. While doing so, the tool collects quantitative information about their understanding of the logical organization of the course content.</div><div>The paper focuses then on presenting a prioritization algorithm that dynamically selects which concepts are displayed to the users as they are playing the game. The algorithm tries to make students perform maximally informative tasks, and assigns priority scores to each concept by integrating hierarchical factors (such as node depth, number of child nodes, and a leaf factor) with weights that capture the significance of different types of relationships (e.g., necessary, important, useful). These scores are iteratively updated based on the input of the user, ensuring that the most relevant and informative topics are presented throughout the session. Field tests with engineering students demonstrate that the mapping game not only aids in visualizing complex interrelationships among concepts but also promotes active metacognitive engagement. The prioritization algorithm, with its modular and scalable design, effectively supports real-time adaptation to student feedback and the evolving structure of the reference map. This integrated framework thus offers a promising tool for both enhancing learning outcomes and providing educators with quantitative insights into students’ conceptual understanding. We thus also show that the dual objectives of the mapping game and its underpinning prioritization algorithm achieve a synergistic approach useful to interactive learning, and improve traditional study methods with a dynamic educational experience.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 7","pages":"Pages 177-182"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The AI Elephant in the Room: ChatGPT in Control Engineering Education","authors":"P.B. de Moura Oliveira ,&nbsp;Damir Vrančić","doi":"10.1016/j.ifacol.2025.08.053","DOIUrl":"10.1016/j.ifacol.2025.08.053","url":null,"abstract":"<div><div>Since the public unveiling of ChatGPT-3 in November 2022, its impact and consequences for society have been significant. This generative artificial intelligence has now become a disruptive technology. Education in general, and Engineering Education in particular, are feeling the effects of the widespread adoption of artificial intelligence tools by students. However, teachers and universities are still struggling with how to deal with these technologies. The current increase in digitalisation makes detecting unauthorised use of ChatGPT and similar tools a major challenge. This paper therefore explores several issues regarding the use of ChatGPT in the context of Engineering Education.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 7","pages":"Pages 236-241"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A MATLAB App for Teaching Multi-Objective Speed Planning: Minimizing Time and Energy Consumption","authors":"Stefano Ardizzoni ,&nbsp;Luca Consolini ,&nbsp;Mattia Laurini ,&nbsp;Marco Locatelli","doi":"10.1016/j.ifacol.2025.08.031","DOIUrl":"10.1016/j.ifacol.2025.08.031","url":null,"abstract":"<div><div>An important problem in motion planning is the computation of the speed profile along a predefined path, with the objective of minimizing travel time and energy consumption. This is a multi-objective optimization problem of clear industrial relevance. For control engineering students, addressing this problem requires the development of key skills. These include writing the dynamic equations of a road vehicles, formulating a multi-objective optimization problem, and using both convex and non-convex solvers for solving optimization problems. This paper presents a teaching unit focused on the speed planning problem, consisting of an initial lecture-based component delivered by the lecturer, followed by an interactive session supported by the use of a dedicated MATLAB-based application with a graphical user interface. This tool allows users to visualize instances of the speed planning problem and observe how solutions change as the problem parameters vary. Unlike traditional analytical approaches, this tool provides an interactive learning environment, where students can experiment with different scenarios in real time, gaining a more intuitive understanding of the trade-offs in multi-objective optimization.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 7","pages":"Pages 105-110"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Terminological Dictionary of Automatic Control, Systems and Robotics: an Example of Good Terminological Practice⁎","authors":"Gorazd Karer ,&nbsp;Rihard Karba ,&nbsp;Juš Kocijan ,&nbsp;Mojca Žagar Karer ,&nbsp;Tadej Bajd","doi":"10.1016/j.ifacol.2025.08.029","DOIUrl":"10.1016/j.ifacol.2025.08.029","url":null,"abstract":"<div><div>The paper describes a case of good terminological practice in the field of automatic control, systems and robotics. It presents the history and the outcomes of terminological work in this field, firstly the Slovenian Terminological Dictionary of Automatic Control, Systems and Robotics, which has been has been very well accepted by the wider control community in Slovenia. The feedback from the community encouraged the authors to adapt and upgrade the Slovenian dictionary to the monolingual English Terminological Dictionary of Automatic Control, Systems and Robotics. The objective of both terminological dictionaries is to collect and unify, as far as possible, the terminology in the field of automatic control, dynamic systems and robotics. The dictionaries represent a helpful resource for students, as well as experts in the field. We firmly believe that well-defined and harmonized terminology is essential for ensuring noiseless communication between experts. Therefore, the Terminological Dictionary of Automatic Control, Systems and Robotics is expected to provide a considerable boost to the development of the field.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 7","pages":"Pages 93-98"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling human-autonomy team steering behavior in shared-autonomy driving scenarios","authors":"Rene E. Mai ,&nbsp;Kara Daveron ,&nbsp;Agung Julius ,&nbsp;Sandipan Mishra","doi":"10.1016/j.ifacol.2025.07.003","DOIUrl":"10.1016/j.ifacol.2025.07.003","url":null,"abstract":"<div><div>Well-accepted models such as the two-point steering model and its variations describe human steering behavior in non-autonomous vehicles. However, these models may not describe human steering in a shared autonomous vehicle, where the human driver cooperates with an autonomous controller. This work explores how the generalized two-point steering model, a variation of the classical two-point model, may apply to human steering in a shared autonomous vehicle. This study reports two key findings: (1) We find that humans do not necessarily steer the vehicle to the exact lane center, perhaps due to imprecise distance perception or a preference to stay off-center in the lane. Thus, we propose adding a steering bias term to the generalized steering model to account for this behavior; (2) We also find that human steering adapts so that the overall team steering–the combined human and autonomous steering input–behaves according to the generalized steering model with this new bias term. We collected data over 150 runs across 5 drivers and 3 levels of autonomy, and found that the modified generalized steering model accurately predicts team steering behavior.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 3","pages":"Pages 13-18"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient and Risk-Aware Framework for Autonomous Navigation in Resource-Constrained Configurations","authors":"Mohamed Benrabah ,&nbsp;Charifou Orou Mousse ,&nbsp;Roland Chapuis ,&nbsp;Romuald Aufrère","doi":"10.1016/j.ifacol.2025.07.022","DOIUrl":"10.1016/j.ifacol.2025.07.022","url":null,"abstract":"<div><div>Path planning is a key challenge for autonomous vehicles, requiring solutions that balance safety and efficiency. This article proposes an autonomous road navigation system that does not rely on precise GPS, HD maps, or high-speed communication, making it particularly suitable for sparsely urbanized rural areas. The proposed method uses a tentacle-based path planning algorithm to compute the fastest possible trajectory while ensuring safety. A real-time traversability map, built and continuously updated from LiDAR (or alternative sensor) data, allows the robot to dynamically assess the risk of collision. The algorithm accounts for sensor perception limits, ensuring that any new obstacle appearing beyond the sensor range will not cause a collision. Simulation results are presented to evaluate and demonstrate our approach’s ability to simultaneously optimize speed while ensuring safety garentees.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 3","pages":"Pages 127-132"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning Autonomy: Off-Road Navigation Enhanced by Human Input","authors":"Akhil Nagariya ,&nbsp;Dimitar Filev ,&nbsp;Srikanth Saripalli ,&nbsp;Srikanth Saripalli ,&nbsp;Gaurav Pandey","doi":"10.1016/j.ifacol.2025.07.024","DOIUrl":"10.1016/j.ifacol.2025.07.024","url":null,"abstract":"<div><div>In the area of autonomous driving, navigating off-road terrains presents a unique set of challenges, from unpredictable surfaces like grass and dirt to unexpected obstacles such as bushes and puddles. In this work, we present a novel learning-based local planner that addresses these challenges by directly capturing human driving nuances from real-world demonstrations using only a monocular camera. The key features of our planner are its ability to navigate in challenging of-road environments with various terrain types and its fast learning capabilities. By utilizing minimal human demonstration data (5-10 mins), it quickly learns to navigate in a wide array of of-road conditions. The local planner significantly reduces the real world data required to learn human driving preferences. This allows the planner to apply learned behaviors to real-world scenarios without the need for manual fine-tuning, demonstrating quick adjustment and adaptability in off-road autonomous driving technology.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 3","pages":"Pages 139-144"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}