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arXiv 2024年

作者： Berahman, Mehran Rostami-Shahrbabaki, Majid Bogenberger, Klaus Department of Electrical and Computer Engineering Shiraz University Shiraz Iran Chair of Traffic Engineering and Control Technical University of Munich Munich Germany

Deep reinforcement learning has shown promise in various engineering applications, including vehicular traffic control. The non-stationary nature of traffic, especially in the lane-free environment with more degrees of freedom in vehicle behaviors, poses challenges for decision-making since a wrong action might lead to a catastrophic failure. In this paper, we propose a novel driving strategy for Connected and Automated Vehicles (CAVs) based on a competitive Multi-Agent Deep Deterministic Policy Gradient approach. The developed multi-agent deep reinforcement learning algorithm creates a dynamic and non-stationary scenario, mirroring real-world traffic complexities and making trained agents more robust. The algorithm’s reward function is strategically and uniquely formulated to cover multiple vehicle control tasks, including maintaining desired speeds, overtaking, collision avoidance, and merging and diverging maneuvers. Moreover, additional considerations for both lateral and longitudinal passenger comfort and safety criteria are taken into account. We employed inter-vehicle forces, known as nudging and repulsive forces, to manage the maneuvers of CAVs in a lane-free traffic environment. The proposed driving algorithm is trained and evaluated on lane-free roads using the Simulation of Urban Mobility platform. Experimental results demonstrate the algorithm’s efficacy in handling different objectives, highlighting its potential to enhance safety and efficiency in autonomous driving within lane-free traffic environments. © 2024, CC BY-NC-SA.

关键词： Reinforcement learning

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Nonsingular Fast Terminal Sliding Mode Attitude control Design for a Coaxial Tilt-Rotor UAV

Nonsingular Fast Terminal Sliding Mode Attitude Control Desi...

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SICE Annual Conference

作者： Zheng Hou Longlong Chen Zongyang Lv Yuhu Wu Huijuan Song Man Wang School of Control Science and Engineering Dalian University of Technology Dalian China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

ISBN: (数字)9784907764838

ISBN: (纸本)9798331544461

This paper proposes an attitude controller utilizing the sliding mode technique for a coaxial tilt-rotor unmanned aerial vehicle (CTRUAV) in the presence of external disturbances. The CTRUAV features two servos that empower two pairs of coaxial rotors to tilt independently, along with a rear rotor. This sophisticated configuration sets it apart from regular unmanned aerial vehicles (UAVs) and imposes stringent requirements on the attitude controller design. A nonsingular fast terminal sliding mode controller (NFTSMC) is designed to achieve high speed, accuracy, and robust attitude tracking performance to address these challenges. The finite-time convergence property of NFTSMC is theoretically proved, and the singularity issue is addressed. The effectiveness of the developed control system is validated through comparative simulations and real-time experiments.

关键词： Accuracy Attitude control Rotors Autonomous aerial vehicles control systems Real-time systems Iron Servomotors Convergence

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Network construction of small and medium-sized enterprises based on virtual cloud WEB in the information age

Network construction of small and medium-sized enterprises b...

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作者： Zhibin Liu Bo Peng Mingming Cai School of Computer and Control Engineering Qiqihar University Department of Information Engineering Qiqihar Institute of Engineering School of Computer and Information Engineering Henan University of Economics and Law

With the continuous development of the Internet and the promotion of the epidemic, the construction of enterprise networking is becoming more and more important. Website construction has become an essential part of enterprise ***, small and medium-sized enterprises are facing economic and human pressures. Enterprise website, online office, online mall VPN, forums and other services for the development of the company is particularly important. Through the investigation and analysis of 20 small and medium-sized enterprises, domestic and foreign academic papers and online data, this paper introduces the importance of cloud on enterprise network, constructs the virtual cloud construction system based on CMS, and provides solutions from the aspects of capital cost, hardware procurement, software environment, system development, later operation and maintenance and labor cost, so as to realize simple, rapid, efficient, safe and lowcost deployment. At the same time, it meets the development of enterprise science and technology, perfects and summarizes the architecture model, realizes the demand of network construction of small and medium-sized enterprises efficiently and quickly, and encourages the development of entrepreneurs and small and medium-sized enterprises.

关键词： small and medium-sized enterprises cloud services CMS WEB network site

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Egocentric zone-aware action recognition across environments

arXiv

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arXiv 2024年

作者： Peirone, Simone Alberto Goletto, Gabriele Planamente, Mirco Bottino, Andrea Caputo, Barbara Averta, Giuseppe Department of Control and Computer Engineering Politecnico di Torino Corso Castelfidardo 34/d Turin10138 Italy

Human activities exhibit a strong correlation between actions and the places where these are performed, such as washing something at a sink. More specifically, in daily living environments we may identify particular locations, hereinafter named activity-centric zones, which may afford a set of homogeneous actions. Their knowledge can serve as a prior to favor vision models to recognize human activities. However, the appearance of these zones is scene-specific, limiting the transferability of this prior information to unfamiliar areas and domains. This problem is particularly relevant in egocentric vision, where the environment takes up most of the image, making it even more difficult to separate the action from the context. In this paper, we discuss the importance of decoupling the domain-specific appearance of activity-centric zones from their universal, domain-agnostic representations, and show how the latter can improve the cross-domain transferability of Egocentric Action Recognition (EAR) models. We validate our solution on the EPIC-Kitchens-100 and Argo1M datasets. Project page: ***/EgoZAR. Copyright © 2024, The Authors. All rights reserved.

关键词： Video analysis

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A Tube-Based Reinforcement Learning Approach for Optimal Motion Planning in Unknown Workspaces

A Tube-Based Reinforcement Learning Approach for Optimal Mot...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Panagiotis Rousseas Charalampos P. Bechlioulis Kostas J. Kyriakopoulos School of Mechanical Engineering Control Systems Laboratory National Technical University of Athens Greece Department of Electrical and Computer Engineering University of Patras

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this work, a tube-based nearly optimal solution to motion planning in unknown workspaces is presented. The advantages of reactive motion planning are combined with a Policy Iteration Reinforcement Learning scheme to yield a novel solution for unknown workspaces that inherits provable safety, convergence and optimality. Moreover, in simply-connected workspaces, our method is proven to asymptotically provide the globally optimal path. Our method is compared against a provably asymptotically optimal RRT ⋆ method, as well as a relevant reactive method and provides satisfactory performance, closely matching or outperforming the former.

关键词： Reinforcement learning Planning Safety Robotics and automation Convergence

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Model-plant mismatch detection for a plant under Model Predictive control: A grinding mill circuit case study

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IFAC-PapersOnLine 2023年第2期56卷 11778-11783页

作者： Heinz K. Mittermaier Johan D. le Roux Laurentz E. Olivier Ian K. Craig Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa Analyte Control Pretoria South Africa

This articles investigates two different techniques of identifying model-plant mismatch for a grinding mill circuit under model predictive control. A previous attempt at model-plant mismatch detection for a grinding mill, in the form of a partial cross correlation analysis, is used as a benchmark for model-plant mismatch detection and degraded sub-model isolation. This is followed by an investigation of the plant model ratio technique applied to the same system. The plant model ratio technique is able to isolate the sub-model containing a mismatch as well as detect the specific parameter in a first-order-plus-time-delay model responsible for the mismatch. A simulation study is used to quantify and compare the results between the two model-plant mismatch detection methodologies. The results indicate plant model ratio accurately and timeously detects mismatches in sub-models. This allows for system reidentification or controller adaption to ensure optimal process performance. The advantage above partial cross correlation is the parameter diagnosis within the degraded sub-model coupled with the mismatch direction.

关键词： controller performance monitoring grinding mill circuit model predictive control model-plant mismatch process performance monitoring

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On Detecting Anomalous TLS Connections with Artificial Intelligence Models

On Detecting Anomalous TLS Connections with Artificial Intel...

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IEEE Symposium on computers and Communications (ISCC)

作者： Diana Gratiela Berbecaru Stefano Giannuzzi Department of Control and Computer Engineering Politecnico di Torino Italy Politecnico di Torino Italy Torino Italy

ISBN: (数字)9798350354232

ISBN: (纸本)9798350354249

In recent years, anomaly-based intrusion detection systems using machine learning (ML) and deep learning techniques have started to be developed to mitigate cybersecurity attacks. An anomaly-based intrusion detection system performs traffic analysis by exploiting supervised or unsupervised ML algorithms and raises alerts if a suspicious pattern is encountered. In this paper, we exploit the Autoencoder neural network model to detect variants of a very famous attack discovered in 2014, namely Heartbleed. The attack was caused by an implementation flaw in the OpenSSL library, widely used in web servers, database systems, or e-mail servers to support the Transport Layer Security (TLS) protocol. To evaluate our model, we exploited the CIC-IDS2017 dataset and a custom one created on purpose. The proposed model recognized the anomalous TLS connections containing variants of the Heartbleed attack and distinguished them from the benign traffic in 85% of the cases.

关键词： Protocols Machine learning algorithms Computational modeling Supervised learning Neural networks Intrusion detection Semisupervised learning Libraries Web servers Malware

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False Data Injection Attack Detection Based on Wavelet Packet Decomposition and Random Forest in Smart Grid 23

False Data Injection Attack Detection Based on Wavelet Packe...

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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Chen, Zhenyu Yuan, Shuai Wu, Longfei Guan, Zhitao Du, Xiaojiang School of Control and Computer Engineering North China Electric Power University China Brock University Department of Finance Operations and Information Systems ON Canada Fayetteville State University Department of Mathematics and Computer Science Fayetteville United States Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States

ISBN: (纸本)9781665494571

As one of the critical infrastructures, the safety and reliability of the smart grid are directly associated with the development and stability of society. However, studies have shown that the power grid is at risk when the parameters are manipulated and cyber-attacks are generated against the state estimation, i.e., under false data injection attack (FDIA). Currently, a rich body of literature has studied on the FDIA defense methods, but most of them focus on the direct current (DC) scenario. This paper proposes a novel detection model that combines the wavelet packet decomposition (WPD) technique with the random forest (RF) algorithm. The WPD is able to capture the deviation of parameters from the normal conditions, whereas the RF is developed to classify these features and effectively identify the malicious data. The proposed model is also evaluated using real-world data on IEEE 118-bus power system. The results demonstrate excellent performance on precision rate and recall rate under varying scenarios. © 2021 IEEE.

关键词： Radio frequency Training data Interference Power system stability Feature extraction Data models Wavelet packets

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Gain Scheduling Position control for Fully-Actuated Morphing Multi-Rotor UAVs

Gain Scheduling Position Control for Fully-Actuated Morphing...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Youssef Aboudorra Aaron Saini Antonio Franchi Robotics and Mechatronics Faculty of Electrical Engineering Mathematics & Computer Science University of Twente Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This work presents techniques for scheduling the position controller gains for a class of fully-actuated morphing multi-rotor UAVs that use synchronized tilting to change their actuation capabilities. The feasible set of forces and torques that can be produced by the platform changes with the tilting angle, thus the tracking and disturbance rejection capabilities also change. To exploit the platform limits, two methods are proposed for gain scheduling using a simplified example, then one method is tested in simulation with an omnidirectional morphing multi-rotor (OmniMorph). The simulation results show that the developed techniques achieve consistent position tracking performance along the range of tilting angles when rejecting step disturbance forces of values close to the maximum force capabilities. The proposed methods offer a trade-off between simplicity and accuracy, that could be potentially applied for any multi-rotor with synchronized tilting capabilities. A video summary can be found in: https://***/kH-rrO8gWeU

关键词： Accuracy Processor scheduling Attitude control Simulation Force Rotors Position control

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High Efficiency Crypto-Watermarking System Based on Clifford-Multiwavelet for 3D Meshes Security

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computers, Materials & Continua 2022年第11期73卷 4329-4347页

作者： Wajdi Elhamzi Malika Jallouli Yassine Bouteraa Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Engineering and Sciences Higher School of Sciences and Technology of Hammam SousseUniversity of SousseSousse4011Tunisia LATIS Laboratory of Advanced Technology and Intelligent Systems University of SousseSousse4023Tunisie Control and Energy Management Laboratory(CEM Lab.) Ecole Nationale d Ingenieurs de Sfax(ENIS)Institut Superieur de Biotechnologie de Sfax(ISBS)University of SfaxSfax3038Tunisia

Since 3D mesh security has become intellectual property,3D watermarking algorithms have continued to appear to secure 3D meshes shared by remote users and saved in distant multimedia *** novelty of our approach is that it uses a new Clifford-multiwavelet transform to insert copyright data in a multiresolution domain,allowing us to greatly expand the size of the *** that,our method does two rounds of insertion,each applying a different type of Clifford-wavelet *** being placed into the Clifford-multiwavelet coefficients,the watermark,which is a mixture of the mesh description,source mesh signature(produced using SHA512),and a logo encrypted using the RSA(Ronald Shamir Adleman)technique,is encoded using *** the Least Significant Bit method steps,data embedding involves modulation and insertion ***,the watermarked mesh is reconstructed using the inverse Cliffordmultiwavelet *** to the utilization of a hybrid insertion domain,our technique has demonstrated a very high insertion rate while retaining mesh *** mesh is watermarked,and the extracted data is acquired in *** approach is also resistant to the most common types of *** findings reveal that the current approach improves on previous efforts.

关键词： Digital watermarking Clifford-multiwavelet transform Multiwavelet entropy LSB method RSA algorithm RSA algorithm Turbocode 3D multiresolution meshes

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