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63rd IEEE Conference on Decision and control, CDC 2024

作者： Liu, Tong Krstic, Miroslav Jiang, Zhong-Ping New York University Control and Networks Lab Department of Electrical and Computer Engineering Tandon School of Engineering BrooklynNY11201 United States University of California Department of Mechanical and Aerospace Engineering San DiegoCA92093-0411 United States

ISBN: (纸本)9798350316339

This paper studies the distributed feedback optimization problem for linear multi-agent systems without precise knowledge of local costs and agent dynamics. The proposed solution is based on a hierarchical approach that uses upper-level coordinators to adjust reference signals toward the global optimum and lower-level controllers to regulate agents' outputs toward the reference signals. In the absence of precise information on local gradients and agent dynamics, an extremum-seeking mechanism is used to enforce a gradient descent optimization strategy, and an adaptive dynamic programming approach is taken to synthesize an internal-model-based optimal tracking controller. The whole procedure relies only on measurements of local costs and input-state data along agents' trajectories. Moreover, under appropriate conditions, the closed-loop signals are bounded and the output of the agents exponentially converges to a small neighborhood of the desired extremum. A numerical example is conducted to validate the efficacy of the proposed method. © 2024 IEEE.

关键词： Dynamic programming

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Multi-Agent Coordination for a Partially Observable and Dynamic Robot Soccer Environment with Limited Communication 10

Multi-Agent Coordination for a Partially Observable and Dyna...

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10th Italian Workshop on Artificial Intelligence and Robotics, AIRO 2023

作者： Affinita, Daniele Volpi, Flavio Spagnoli, Valerio Suriani, Vincenzo Nardi, Daniele Bloisi, Domenico D. Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Italy Faculty of Political Science and Sociopsychological Dynamics UNINT University Rome Italy

RoboCup represents an International testbed for advancing research in AI and robotics, focusing on a definite goal: developing a robot team that can win against the human world soccer champion team by the year 2050. To achieve this goal, autonomous humanoid robots' coordination is crucial. This paper explores novel solutions within the RoboCup Standard Platform League (SPL), where a reduction in WiFi communication is imperative, leading to the development of new coordination paradigms. The SPL has experienced a substantial decrease in network packet rate, compelling the need for advanced coordination architectures to maintain optimal team functionality in dynamic environments. Inspired by market-based task assignment, we introduce a novel distributed coordination system to orchestrate autonomous robots' actions efficiently in low communication scenarios. This approach has been tested with NAO robots during official RoboCup competitions and in the SimRobot simulator, demonstrating a notable reduction in task overlaps in limited communication settings. © 2024 Copyright for this paper by its authors.

关键词： Anthropomorphic robots

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Reinforcement Learning-Based Output Stabilization control for Nonlinear Systems With Generalized Disturbances 25

Reinforcement Learning-Based Output Stabilization Control fo...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Tang, Zezhi Rossiter, J Anthony Dong, Yi Panoutsos, George University Of Sheffield Department Of Automatic Control And Systems Engineering SheffieldS13JD United Kingdom University Of Southampton Department Of Electronics And Computer Science Southampton United Kingdom

ISBN: (纸本)9798350340266

This paper proposes a new disturbance observer (DO)-based reinforcement learning (RL) control approach for nonlinear systems with unmatched (generalized) disturbances. While a nonlinear disturbance observer (NDO) is utilized to measure the plant uncertainties, disturbances can exist in the plant via distinct channels from those of the control signals;so-called mismatched disturbances are theoretically difficult to attenuate within the channel of the system's states. A generalized disturbance observer-based compensator is implemented to address the uncertainty cancellation problem by removing the influence of uncertainties from the output channels. Con-currently, a composite actor-critic RL scheme is utilized for approximating the optimal control policy as well as the ideal value function pertaining to the compensated system by solving a Hamilton-Jacobi-Bellman (HJB) equation for both online and offline iterations simultaneously. Stability analysis verifies the convergence of the proposed framework. Simulation results are included to illustrate the effectiveness of the proposed scheme. © 2024 IEEE.

关键词： Nonlinear systems

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Sustainable business model in practice: a digital business game training for high school students 15

Sustainable business model in practice: a digital business g...

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15th International Conference on Society and Information Technologies, ICSIT 2024

作者： Fontanella, Sabrina Fraccascia, Luca Nonino, Fabio Scarnicchia, Alessandra Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome Roma Lazio Italy Department of High-Tech Business and Entrepreneurship University of Twente Enschede Overijssel Netherlands

ISBN: (纸本)9781950492770

This paper explores the nexus between sustainable business models, education and technology, addressing pressing challenges in economic, social, and environmental spheres. On one hand, education is identified as a key tool for fostering sustainability principles and essential skills for future managers;on the other, businesses, particularly through sustainable business models (SBMs) and evolving digital platforms, play a pivotal role in advancing sustainability goals. The research answer to the need for sustainable development examining the potential of educational business games, blending entertainment and education to engage the 'gamer generation' actively. Considering the growing literature upon sustainable entrepreneurship and business models, the objective of the paper is to implement a digital business game for sustainability education designed to teach high school students how to implement an entrepreneurial activity through a sustainable business model. This study contributes to understanding sustainable business practices and innovative educational approaches, aligning with the global imperative for a sustainable future. In the end of the manuscript some prelaminar result of the game testing phase are presented. © Proceedings ICSIT, International Conference on Society and Information Technologies. All Rights Reserved.

关键词： Blending

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Hier-EgoPack: Hierarchical Egocentric Video Understanding with Diverse Task Perspectives

arXiv

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arXiv 2025年

作者： Peirone, Simone Alberto Pistilli, Francesca Alliegro, Antonio Tommasi, Tatiana Averta, Giuseppe Department of Control and Computer Engineering Politecnico di Torino Italy

Our comprehension of video streams depicting human activities is naturally multifaceted: in just a few moments, we can grasp what is happening, identify the relevance and interactions of objects in the scene, and forecast what will happen soon, everything all at once. To endow autonomous systems with such a holistic perception, learning how to correlate concepts, abstract knowledge across diverse tasks, and leverage tasks synergies when learning novel skills is essential. A significant step in this direction is EgoPack, a unified framework for understanding human activities across diverse tasks with minimal overhead. EgoPack promotes information sharing and collaboration among downstream tasks, essential for efficiently learning new skills. In this paper, we introduce Hier-EgoPack, which advances EgoPack by enabling reasoning also across diverse temporal granularities, which expands its applicability to a broader range of downstream tasks. To achieve this, we propose a novel hierarchical architecture for temporal reasoning equipped with a GNN layer specifically designed to tackle the challenges of multi-granularity reasoning effectively. We evaluate our approach on multiple Ego4D benchmarks involving both clip-level and frame-level reasoning, demonstrating how our hierarchical unified architecture effectively solves these diverse tasks simultaneously. Project page: ***/hier-egopack. Copyright © 2025, The Authors. All rights reserved.

关键词： Multi-task learning

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Benchmarking Semantic Communications for Image Transmission Over MIMO Interference Channels 16

Benchmarking Semantic Communications for Image Transmission ...

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16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Wang, Yanhu Guo, Shuaishuai Dong, Anming Zhao, Hui School of Control Science and Engineering Shandong University China School of Computer Science and Technology Qilu University of Technology China Eurecom Communication Systems Department France

ISBN: (纸本)9798350390643

Semantic communications offer promising prospects for enhancing data transmission efficiency. However, existing schemes have predominantly concentrated on point-to-point transmissions. In this paper, we aim to investigate the validity of this claim in interference scenarios compared to baseline approaches. Specifically, our focus is on general multiple-input multiple-output (MIMO) interference channels, where we propose an interference-robust semantic communication (IRSC) scheme. This scheme involves the development of transceivers based on neural networks (NNs), which integrate channel state information (CSI) either solely at the receiver or at both transmitter and receiver ends. Moreover, we establish a composite loss function for training IRSC transceivers, along with a dynamic mechanism for updating the weights of various components in the loss function to enhance system fairness among users. Experimental results demonstrate that the proposed IRSC scheme effectively learns to mitigate interference and outperforms baseline approaches, particularly in low signal-tonoise (SNR) regimes. © 2024 IEEE.

关键词： Radio transceivers

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Tangentially-Magnetized-Slot-PM-Assisted Magnet Saturation Relieving Design for Doubly Salient Reluctance Machine Position Sensorless Drive Electric Propulsion Applications 6

Tangentially-Magnetized-Slot-PM-Assisted Magnet Saturation R...

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6th International Conference on Electrical engineering and control Technologies, CEECT 2024

作者： Wang, Weiyu Zhang, Xiaodong Niu, Shuangxia Zhao, Xing Pan, Jianfei Fu, Weinong Great Bay University School of Engineering Dongguan China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Hong Kong University of York Department of Electronic Engineering York United Kingdom Shenzhen University College of Mechatronics and Control Engineering Shenzhen China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen China

ISBN: (纸本)9798331528096

For doubly salient reluctance machines, the magnetic saturation effect easily occurs, thereby the saturated inductance with complex analytical expression brings difficulties to the inductance modeling procedure during position sensorless control. To tackle this issue, a direct solution from electrical machine design is introduced to regulate magnetic flux distribution. The key is to insert tangentially-magnetized-slot-permanent-magnet into stator slots, thus relieving the magnetic saturation in the stator teeth. Consequently, unsaturated inductance characteristics can be acquired through the magnetic saturation relieving effect, thereby the inductance modeling effort can be significantly decreased, and such design is friendly for doubly salient reluctance machine position sensorless drive application. © 2024 IEEE.

关键词： Stators

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Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

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computers, Materials & Continua 2023年第2期74卷 2677-2693页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Manal Abdullah Alohali Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.

关键词： Feature selection grey wolf optimization dipper throated optimization intrusion detection internet-of-things(IoT)

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On the Fault Tolerance of Self-Supervised Training in Convolutional Neural Networks

On the Fault Tolerance of Self-Supervised Training in Convol...

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IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Rosario Milazzo Vincenzo De Marco Corrado De Sio Sophie Fosson Lia Morra Luca Sterpone Department of Control and Computer Engineering Polytechnic of Torino Italy

Deep neural networks (DNNs) are increasingly used in critical applications from healthcare to autonomous driving. However, their predictions were shown to degrade in the presence of transient hardware faults, leading to potentially catastrophic and unpredictable errors. Consequently, several techniques have been proposed to increase the fault tolerance of DNNs by modifying network structures and/or training procedures, thereby reducing the need for costly hardware redundancy. There are, however, design or training choices whose impact on fault propagation has been overlooked in the literature. In particular, self-supervised learning (SSL), as a pretraining technique, was shown to improve the robustness of the learned features, resulting in better performance in downstream tasks. This study investigates the fault tolerance of several SSL techniques on image classification benchmarks, including several related to Earth Observation. Experimental results suggests that SSL pretraining, alone or in combination with fault mitigation techniques, generally improves DNNs' fault tolerance, although the performance gap vary among datasets and SSL techniques.

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Security Issues in Software-Defined Networking (SDN) Environments 23

Security Issues in Software-Defined Networking (SDN) Environ...

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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Yalda, Khirota Gorgees Hamad, Diyar Jamal Tapus, Nicolae Okumus, Ibrahim Taner Politehnica University of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Erbil Polytechnic University Kurdistan Region IT Department Soran Technical College Erbil Iraq Kahramanmaras Sutcu Imam University Kahramanmaras Computer Engineering Faculty of Engineering Turkey

ISBN: (纸本)9798331540388

Software-Defined Networking (SDN) represents a significant shift in network architecture, providing exceptional programmability, flexibility, and simplified management. However, this paradigm shift introduces a unique set of security challenges that must be addressed to fully realize the potential of SDN. This paper examines the security issues in SDN environments, detailing the threats and vulnerabilities at various layers of the SDN architecture, including the control plane, data plane, and application plane. Through an extensive review of current literature, critical security challenges such as controller attacks, data plane breaches, and vulnerabilities in inter-plane communications are identified. Existing security solutions and mitigation strategies, such as authentication and authorization mechanisms, encryption techniques, and intrusion detection systems, are also explored. Furthermore, the paper discusses recent advances and emerging trends in SDN security, offering insights into ongoing research and future directions. The findings underscore the importance of robust security measures in ensuring the reliability and integrity of SDN deployments, providing a foundation for future innovation and development in this dynamic field. © 2024 IEEE.

关键词： Network intrusion

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