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Privacy-preserving filtering, control and optimization for industrial cyber-physical systems

Science China(Information Sciences) 2025年第4期68卷 267-283页

作者： Derui DING Qing-Long HAN Xiaohua GE Xian-Ming ZHANG Jun WANG Department of Control Science and Engineering University of Shanghai for Science and Technology School of Engineering Swinburne University of Technology Department of Computer Science City University of Hong Kong

Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection between cyberspace and physical processes results in the exposure of industrial production information to unprecedented security risks. It is imperative to develop suitable strategies to ensure cyber security while meeting basic performance *** the perspective of control engineering, this review presents the most up-to-date results for privacy-preserving filtering,control, and optimization in industrial cyber-physical systems. Fashionable privacy-preserving strategies and mainstream evaluation metrics are first presented in a systematic manner for performance evaluation and engineering *** discussion discloses the impact of typical filtering algorithms on filtering performance, specifically for privacy-preserving Kalman filtering. Then, the latest development of industrial control is systematically investigated from consensus control of multi-agent systems, platoon control of autonomous vehicles as well as hierarchical control of power systems. The focus thereafter is on the latest privacy-preserving optimization algorithms in the framework of consensus and their applications in distributed economic dispatch issues and energy management of networked power systems. In the end, several topics for potential future research are highlighted.

关键词： industrial cyber-physical systems privacy preservation distributed control distributed optimization power systems

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Enhancing Social Experiences in Immersive Virtual Reality with Artificial Facial Mimicry

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IEEE Transactions on Visualization and computer Graphics 2025年第5期31卷 3325-3335页

作者： Visconti, Alessandro Calandra, Davide Giorgione, Federica Lamberti, Fabrizio Politecnico di Torino Department of Control and Computer Engineering Italy Politecnico di Torino Italy

The growing availability of affordable Virtual Reality (VR) hardware and the increasing interest in the Metaverse are driving the expansion of Social VR (SVR) platforms. These platforms allow users to embody avatars in immersive social virtual environments, enabling real-time interactions using consumer devices. Beyond merely replicating real-life social dynamics, SVR platforms offer opportunities to surpass real-world constraints by augmenting these interactions. One example of such augmentation is Artificial Facial Mimicry (AFM), which holds significant potential to enhance social experiences. Mimicry, the unconscious imitation of verbal and non-verbal behaviors, has been shown to positively affect human-agent interactions, yet its role in avatar-mediated human-to-human communication remains under-explored. AFM presents various possibilities, such as amplifying emotional expressions, or substituting one emotion for another to better align with the context. Furthermore, AFM can address the limitations of current facial tracking technologies in fully capturing users' emotions. To investigate the potential benefits of AFM in SVR, an automated AM system was developed. This system provides AFM, along with other kinds of head mimicry (nodding and eye contact), and it is compatible with consumer VR devices equipped with facial tracking. This system was deployed within a test-bench immersive SVR application. A between-dyads user study was conducted to assess the potential benefits of AFM for interpersonal communication while maintaining avatar behavioral naturalness, comparing the experiences of pairs of participants communicating with AFM enabled against a baseline condition. Subjective measures revealed that AFM improved interpersonal closeness, aspects of social attraction, interpersonal trust, social presence, and naturalness compared to the baseline condition. These findings demonstrate AFM's positive impact on key aspects of social interaction and highlight its pote

关键词： Virtual environments

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Real-time drone detection framework based on advanced texture feature extraction and pattern recognition model using GUI

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Neural Computing and Applications 2025年第5期37卷 3435-3454页

作者： Hussen, Noha Salem, Mofreh Eldesouky, Ali I. Sakr, Noha Elghamrawy, Sally Computers and Control Systems Engineering Department Mansoura University Mansoura Egypt Computer Engineering Department Misr Higher Institute for Engineering and Technology Mansoura Egypt

The increasing prevalence of drones has raised significant concerns regarding their potential for misuse in activities such as smuggling, terrorism, and unauthorized access to restricted airspace. Consequently, the development of robust and efficient drone detection systems has become paramount. Traditional detection methods such as radar and acoustic sensors have limitations in detecting small drones and can be costly to implement. This can lead to lower detection rates and increased security breaches and safety concerns. However, prevailing methodologies often falter in achieving real-time detection with requisite precision and efficacy, particularly within complex operational environments. Motivated by the imperative to surmount these challenges, our research endeavors to introduce a pioneering real-time drone detection framework. Our study encapsulates several seminal advancements. Firstly, we proffer a groundbreaking framework that synergizes advanced integration technique based on texture feature extraction and pattern recognition techniques for real-time drone detection to increase accuracy to detect drones in different conditions such as bad weather and low resolution. Secondly, we introduce an intuitive graphical user interface, enhancing the usability and accessibility of the system in real-time scenario. Lastly, through exhaustive evaluation and comparative analysis, we substantiate the superior performance of our framework in terms of accuracy, precision, and real-time detection capabilities compared to conventional DDS methodologies. Its stability and effectiveness render it a compelling solution for security-focused entities, notably those within air force and military systems. Our experimental results reveal a commendable accuracy rate of 97%, affirming the reliability and precision 98% and recall parameter 98% of our framework in accurately identifying and detecting drones, thus surpassing recent models in the field. © The Author(s), under exclusive

关键词： Graphical user interfaces

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Aerial Robots Carrying Flexible Cables: Dynamic Shape Optimal control via Spectral Method Model

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IEEE Transactions on Robotics 2025年 41卷 3162-3182页

作者： Shen, Yaolei Franchi, Antonio Gabellieri, Chiara Faculty AE Enschede7500 Netherlands Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy

In this work, we present a model-based optimal boundary control design for an aerial robotic system composed of a quadrotor carrying a flexible cable. The whole system is modeled by partial differential equations (PDEs) combined with boundary conditions described by ordinary differential equations (ODEs). The proper orthogonal decomposition (POD) method is adopted to project the original infinite-dimensional system on a finite low-dimensional space spanned by orthogonal basis functions. Based on such a reduced order model, nonlinear model predictive control (NMPC) is implemented online to realize both position and shape trajectory tracking of the flexible cable in an optimal predictive fashion. The proposed POD-based reduced modeling and optimal control paradigms are verified in simulation using an accurate high-dimensional finite difference method- (FDM) based model and experimentally using a real quadrotor and a cable. The results show the viability of the POD-based predictive control approach (allowing to close the control loop on the full system state) and its superior performance compared to an optimally tuned PID controller (allowing to close the control loop on the quadrotor state only). © 2004-2012 IEEE.

关键词： Orthogonal functions

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AquaID: Authentication for Underwater Nodes with Decentralised Identity 24

AquaID: Authentication for Underwater Nodes with Decentralis...

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18th ACM International Conference on Underwater Networks and Systems, WUWNET 2024

作者： Altamura, Nicola Giona, Emanuele Nati, Michele Petrioli, Chiara Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Computer Science Sapienza University of Rome Italy WSense Srl Italy

ISBN: (纸本)9798400711602

The increasing pervasiveness of digital infrastructures, also extending into marine domains, makes Underwater Wireless Sensor Networks (UWSNs) an essential tool for the development of novel marine sustainability and monitoring paradigms. Applications in sensitive scenarios may require data encryption, non-repudiation, and provenance tracking. Moreover, the broadcast nature of the underwater acoustic channel makes the task of identifying and authenticating nodes of critical importance. To meet such requirements, we introduce AquaID, a protocol for resource-constrained hardware that leverages Distributed Ledger Technologies (DLTs) and Decentralised Identities. It guarantees confidentiality, authentication, and integrity using low bandwidth and CPU usage, while supporting high scalability and interoperability. We validate our solution in a threefold manner: via embedded board implementation, network simulation, and sea trials using commercially-available acoustic modems and underwater nodes. We also include a cost comparison among possible DLT choices. Results show AquaID to be robust to scaling, achieving low authentication delays and overhead, thus proving suitable even for large deployments. © 2024 Copyright held by the owner/author(s).

关键词： Authentication

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Multi-Step Clustering of Smart Meters Time Series:Application to Demand Flexibility Characterization of SME Customers

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computer Modeling in Engineering & Sciences 2025年第1期142卷 869-907页

作者： Santiago Bañales Raquel Dormido Natividad Duro Department of Computer Sciences and Automatic Control Universidad Nacional de Educación a Distancia(UNED)Madrid28040Spain Iberdrola Innovation Middle East Doha210177Qatar

Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy *** study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time *** meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns *** dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series *** intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire *** the first time,a step function approach is applied to reduce time series *** attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy *** addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined *** application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the *** research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditio

关键词： Electric load clustering load profiling smart meters machine learning data mining demand flexibility demand response

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AdaLightLog: Enhancing Application Logs Anomaly Detection via Adaptive Federating Learning 19th

AdaLightLog: Enhancing Application Logs Anomaly Detection vi...

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19th International Conference on Critical Information Infrastructures Security, CRITIS 2024

作者： Menegatti, Danilo De Santis, Emanuele Felli, Stefano Giuseppi, Alessandro Department of Computer Control and Management Engineering ‘Antonio Ruberti’ Sapienza University of Rome Rome Italy

ISBN: (纸本)9783031842597

The role of anomaly detection systems in Critical Infrastructures (CIs) is critical due to the complexity of CIs and their control systems, which are usually implemented by computer-based controllers that constantly produce logs of their activities. Moreover, many CIs, located in different locations or even belonging to different companies, may share similar application software for controlling the CIs themselves. The goal of this work is to use such logs to perform automatic anomaly detection in a federated learning (FL) paradigm, which ensures that no data is exchanged between sites to train the anomaly detection models, but each learning agent learns on its own data, leveraging the knowledge acquired by the other agents. Our proposed approach - AdaLightLog - which implements a modified FL paradigm with adaptive loss functions at local servers side and weighted averaging of local server models, so to differentiate the quality of the different local servers’ models in the global averaging, is tested against state-of-the-art methods and shows an improvement in performance in terms of accuracy, precision and recall with respect to the standard FL implementation (FedAvg). Furthermore, a comparison between different metrics for the adaptive loss functions and the dynamic weights is presented. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

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An enhanced neuro-adaptive PID sliding mode control for robot manipulators:promoting sustainable automation

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Neural Computing and Applications 2025年第9期37卷 6877-6898页

作者： Elmogy, Ahmed Alhemaly, Nagah El-Ghaish, Hany Elawady, Wael Computer Engineering Deptartment Prince Sattam Ibn Abdelaziz University Alkharj16273 Saudi Arabia Computers & Control Engineering Department Tanta University Tanta31527 Egypt

The control of robot manipulators presents significant challenges, primarily due to their complex, nonlinear dynamics. Another major difficulty arises from environmental and operational disturbances. Numerous control frameworks and approaches have been proposed in the literature to address these issues. However, many of these approaches are discontinuous or non-adaptive, which negatively affects their performance and makes them unsuitable for real-time applications. This paper proposes a novel integrated control scheme that combines adaptive control with an improved continuous second-order sliding mode control (CSOS), utilizing generalized artificial neural networks (GANN) for enhanced performance in robot manipulators. The proposed control method consists of two key components: An adaptive proportional-integral-derivative (PID) controller and an adaptive CSOS-based control module (CSOSSD-APID), designed to deliver superior transient and steady-state performance. In this approach, the adaptive CSOS benefits from GANN’s strong noise handling capabilities and its ability to estimate uncertainties effectively. This integration significantly enhances the robustness of robot manipulator control across various tracking tasks, using a single pre-trained GANN model with fine-tuned weights tailored to each task. Numerical simulations demonstrate the effectiveness and versatility of the proposed control scheme, particularly in managing highly time-varying trajectories while contributing to more sustainable and efficient automation practices. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Adaptive control systems

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control valve simulation method integrable into the global gradient algorithm

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ISH Journal of Hydraulic Engineering 2025年第1期31卷 1-7页

作者： Sivakumar, P. Gorev, N.B. Gorev, V.N. Kodzhespirova, I.F. Shedlovsky, I.A. Itanagar India Department for Functional Elements of Control Systems Institute of Technical Mechanics Dnipro Ukraine Department of Physics Dnipro University of Technology Dnipro Ukraine Department of Automation and Computer Systems Dnipro University of Technology Dnipro Ukraine

This paper presents a refinement of a method that simulates flow- and pressure-regulating valves by replacing them with pipes and adjusting the resistances (diameters) of those pipes to meet the valve settings. The method, referred to as the replacing pipe method (RPM), is readily integrable into the global gradient algorithm, which is the heart of the commonly used EPANET 2 water distribution system modeling software. The RPM proved to be more robust, yet slower than the EPANET 2 valve handling heuristics. In this work, the RPM was modified to increase its computational speed. The modification involved the RPM check valve handling algorithm and condition for updating the diameters of the valve-replacing pipes. The modified RPM was tested as part of a hybrid simulator, which switches from the EPANET 2 valve handling heuristics to the RPM when the former fails. The test networks included a large network with thousands of nodes, pipes, and valves, and a case of an ill-posed problem. As the testing showed, the modified RPM offers a significant reduction in the number of iterations compared to its previous version. © 2024 Indian Society for Hydraulics.

关键词： Safety valves

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Application of a digital intelligent assistant to support industrial processes: The case of adaptive allocation in the face of cyber attacks 6

Application of a digital intelligent assistant to support in...

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6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Colabianchi, Silvia Department of Computer Control and Management Engineering Antonio Ruberti Via Ariosto 25 Rome00185 Italy

The research proposes the application of Digital Intelligent Assistants (DIAs) as proactive agents that can support employees in dealing with cybersecurity issues in sustainable industrial processes underlying the importance of a fruitful Human-Artificial Intelligence collaboration. Cyber-attacks around the world are constantly increasing. DIAs are becoming more effective, also thanks to the use of Large Language Models. Users are required to recall security procedures and rules. Moreover, attacks are constantly evolving and following different patterns. The study presents how a DIA can be a backup agent during and after an attack. The application of digital intelligent assistance technology helps to reduce the cognitive load and pressure that users feel during downtime. In addition, the solution enhances attack reporting by decreasing the shame experienced by the victims. The research proposes a methodological design defining the agent's technical and functional characteristics and its adaptive relationship with human characteristics. The solution is developed using the RASA framework and evaluated through a case study based on a phishing attack scenario. © 2025 The Authors. Published by Elsevier B.V.

关键词： Chatbots

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