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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Wafa Akermi Nouha Alyaoui Awatef Benfradj Guiloufi Karim Chabir Computer Science and Telecommunications Department Higher Institute of Applied Science and Technology Gafsa University Gafsa Tunisia Laboratory of Modeling Analysis and Control of Systems (MACS) National Engineering School of Gabes (ENIG) Gabes University Gabes Tunisia Departement of Computer Engineering College of Computer Qassim University Buraidh Saudi Ababia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

High node mobility, rapid topology changes provide specific challenges for vehicular ad hoc networks (VANETs), which have an immediate impact on the routing protocols' performance. Traditional approaches, like the Optimized Link State Routing (OLSR) protocol, provide proactive route management but fail to fully account for critical dynamic parameters like link stability, relative vehicle speed, node distance, and bandwidth availability. This work proposes a hybrid method combining OLSR with Q-learning to facilitate real-time adaptive routing. The model leverages dynamic metrics to proactively evaluate links while employing Q-learning to optimize routing decisions based on rewards computed from performance factors like delay, packet loss rate, and link duration. Simulation results demonstrate that our approach significantly outperforms classic OLSR. The improvements include reduced packet loss rates, increased average throughput, lower average latency, and a reduction in control overhead. These findings confirm that integrating dynamic metrics and adaptive learning effectively addresses the challenges posed by VANETs.

关键词： Q-learning Simulation Vehicular ad hoc networks Packet loss Routing Throughput Routing protocols Stability analysis Topology Vehicle dynamics

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computer vision for road imaging and pothole detection:a state-of-the-art review of systems and algorithms

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Transportation Safety and Environment 2022年第4期4卷 3-18页

作者： Nachuan Ma Jiahe Fan Wenshuo Wang JinWu Yu Jiang Lihua Xie Rui Fan Department of Control Science and Engineering Frontiers Science Center for Intelligent Autonomous Systemsand State Key Laboratory of Intelligent Autonomous SystemsTongji UniversityShanghai 201804P.R.China Department of Civil Engineering McGill UniversityMontréalQC H3A 0C3Canada Department of Electronics and Computer Engineering the Hong Kong University of Science and TechnologyHong Kong SAR 999077P.R.China CTO Office ClearMotion Inc.BillericaMA 01821USA School of Electrical and Electronic Engineering Nanyang Technological University50 Nanyang Avenue639798Singapore

computer vision algorithms have been utilized for 3-D road imaging and pothole detection for over two ***,there is a lack of systematic survey articles on state-of-the-art(SoTA)computer vision techniques,especially deep learningmodels,developed to tackle these *** article first introduces the sensing systems employed for 2-D and 3-D road data acquisition,including camera(s),laser scanners and Microsoft *** then comprehensively reviews the SoTA computer vision algorithms,including(1)classical 2-D image processing,(2)3-D point cloud modelling and segmentation and(3)machine/deep learning,developed for road pothole *** article also discusses the existing challenges and future development trends of computer vision-based road pothole detection approaches:classical 2-D image processing-based and 3-D point cloud modelling and segmentation-based approaches have already become history;and convolutional neural networks(CNNs)have demonstrated compelling road pothole detection results and are promising to break the bottleneck with future advances in self/un-supervised learning for multi-modal semantic *** believe that this survey can serve as practical guidance for developing the next-generation road condition assessment systems.

关键词： computer vision road imaging pothole detection deep learning image processing point cloud modelling convolutional neural networks

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Secure-by-Construction controller Synthesis via control Barrier Functions

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IFAC-PapersOnLine 2023年第2期56卷 239-245页

作者： Bingzhuo Zhong Siyuan Liu Marco Caccamo Majid Zamani TUM School of Engineering and Design Technical University of Munich Germany Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Computer Science CU Boulder USA

In this paper, we propose a secure-by-construction scheme for synthesizing controllers to enforce safety and security properties simultaneously over control systems. As a key insight, we establish a bridge between the desired safety and security properties by leveraging notions of (augmented) control barrier functions. Based on these functions, we show that one can synthesize secure-by-construction controllers for control systems with continuous state and input sets. Additionally, we provide sum-of-square (SOS) conditions under which the desired (augmented) control barrier functions can be constructed. Finally, we demonstrate the applicability of our results on a case study.

关键词： Secure-by-Construction controller Synthesis Safety Opacity control Barrier Function Security

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Risk-Averse Certification of Bayesian Neural Networks

arXiv

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arXiv 2024年

作者： Zhang, Xiyue Wang, Zifan Gao, Yulong Romao, Licio Abate, Alessandro Kwiatkowska, Marta Department of Computer Science University of Oxford United Kingdom Division of Decision and Control Systems KTH Royal Institute of Technology Sweden Department of Electrical and Electronic Engineering Imperial College London United Kingdom Department of Wind and Energy Systems Technical University of Denmark Denmark

In light of the inherently complex and dynamic nature of real-world environments, incorporating risk measures is crucial for the robustness evaluation of deep learning models. In this work, we propose a Risk-Averse Certification framework for Bayesian neural networks called RAC-BNN. Our method leverages sampling and optimisation to compute a sound approximation of the output set of a BNN, represented using a set of template polytopes. To enhance robustness evaluation, we integrate a coherent distortion risk measure—Conditional Value at Risk (CVaR)—into the certification framework, providing probabilistic guarantees based on empirical distributions obtained through sampling. We validate RAC-BNN on a range of regression and classification benchmarks and compare its performance with a state-of-the-art method. The results show that RAC-BNN effectively quantifies robustness under worst-performing risky scenarios, and achieves tighter certified bounds and higher efficiency in complex tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Risk assessment

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Output Feedback Position Tracking control of Marine Vessels Subject to Periodic Disturbances

Output Feedback Position Tracking Control of Marine Vessels ...

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American control Conference (ACC)

作者： Deniz Kurtoglu Enver Tatlicioglu Erkan Zergeroglu Department of Mechanical Engineering Laboratory for Autonomy Control Information and Systems (LACIS) University of South Florida Tampa FL United States of America Department of Electrical Electronics Engineering Ege University Izmir Turkey Department of Computer Engineering Gebze Technical University Gebze Kocaeli Turkey

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This work deals with the design and implementation of a novel output feedback position tracking controller for marine vessels subject to uncertainties in their dynamical parameters and periodic external disturbance. Specifically, an adaptive controller that does not make use of velocity measurements has been presented which can compensate for uncertainties in the system's dynamical parameters and periodic external disturbance. A filtered based velocity surrogate formulation in conjunction with a periodic noise estimator and a desired model compensation based adaptive parameter estimator have been utilized to tackle the problem. Boundedness of the closed loop system and convergence of the position tracking error to the origin are proven via Lyapunov-type arguments. Comparative numerical simulations are presented to illustrate the effectiveness of the proposed controller.

关键词： Uncertain systems Uncertainty Noise Estimation Numerical simulation Filtering theory Numerical models

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FixGPT: A Novel Three-Tier Deep Learning Model for Automated Program Repair 8

FixGPT: A Novel Three-Tier Deep Learning Model for Automated...

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8th International Conference on Data Science in Cyberspace, DSC 2023

作者： Ye, Wenhao Xia, Jun Feng, Shuo Zhong, Xiangyu Yuan, Shuai Guan, Zhitao State Grid Hunan Electric Power Company Limited Changsha China School of Control and Computer Engineering North China Electric Power University Beijing China Hunan Sgit Technology CO. LTD. Changsha China Brock University Department of Finance Operations and Information Systems ON Canada

ISBN: (纸本)9798350331035

Automatic program repair plays a crucial role in the software development and implementation. While deep learning-based approaches have made significant progress, one inherent challenge is the inefficiency in code representation, which hampers accurate patch generation. Furthermore, the training data used by these data-driven approaches may be limited, and they may not be able to capture the subtle differences between vulnerabilities and patches. To address these issues, FixGPT, we propose a three-tier deep learning model in the study. Specifically, a generative pre-trained transformer model is designed in the first tier to capture code characteristics and programming patterns. The second tier integrates a generation model based on the structure of neural machine translation, for the purpose of generating potential patches. Finally, a contrast model is introduced in the last tier to differentiate between the vulnerability and the patch. We also incorporate the Byte Pair Encoding approach to reduce the search space by converting identifiers into subwords. Detailed experimental studies have been carried out to evaluate the performance of FixGPT on two well-known benchmarking datasets: QuixBugs and Defects4J. The results demonstrated significant improvements in the effectiveness and accuracy in comparison with existing solutions. We complement these findings through the analysis of two case studies. © 2023 IEEE.

关键词： deep learning program repair programming language model vulnerability

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Optimal Sensor Placement for Full-Set TDOA Localization Accounting for Sensor Location Errors

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Zhang, Chengjie Han, Xinyang Kong, He Ho, K.C. Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China University of Missouri Electrical Engineering and Computer Science Department ColumbiaMO65211 United States

The positioning accuracy of a signal source is influenced by where the sensors are deployed. Studies in the literature for the optimal sensor placement (OSP) of localization often ignore the presence of sensor position errors. In practice, however, it is impossible to place the sensors precisely at the desired locations. This work designs OSP by accounting for the presence of Gaussian sensor position errors that are independent and identically distributed (IID), with the full set of Time Difference of Arrival measurements corrupted by Gaussian IID noise. The criterion is the A-optimality equal to the trace of the source position Cramer-Rao Bound (CRB). We show that the presence of sensor position errors introduces a multiplication factor to the same criterion for the case without sensor position errors. The latter factor is dependent on the ratio of the sensor position error power to the range difference noise power but independent of the sensor positions, implying that the A-optimality OSP in the presence of sensor position errors is the same as in the absence. To our knowledge, this is the first time such results have been derived. Simulation studies validate the derived OSP, show the minimal OSP performance gap with sensor positioning error and without, and illustrate the better source localization accuracy by OSP. © 1965-2011 IEEE.

关键词： Cramer-Rao bounds

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements

arXiv

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arXiv 2024年

作者： Xu, Gehui Chen, Guanpu Fidan, Baris Hong, Yiguang Qi, Hongsheng Parisini, Thomas Johansson, Karl H. The Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom The Department of Engineering and Architecture University of Trieste Trieste34127 Italy

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multi-player non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies. Copyright © 2024, The Authors. All rights reserved.

关键词： Sensor nodes

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Monitoring of Energy Processes in the Electrohydraulic Complex with a Variable-Frequency Electric Drive in Unsteady Operation Modes 4

Monitoring of Energy Processes in the Electrohydraulic Compl...

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4th IEEE International Conference on Modern Electrical and Energy System, MEES 2022

作者： Qawaqzeh, Mohamed Zaidan Kovalchuk, Viktoriya Korenkova, Tetyana Serdiuk, Oleksandr Bilyk, Oleksandr Al-Balqa' Applied University Department of Electrical and Electronics Engineering Al-Salt66110 Jordan Kremenchuk Mykhailo Ostrohradskyi National University Department of Systems of Automatic Control and Electric Drive Kremenchuk39600 Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Department of Computer Engineering and Electronics Kremenchuk39600 Ukraine

ISBN: (纸本)9798350346831

An energy model of an electrohydraulic complex has been developed. It allows analyzing the energy processes in the power channel in dynamic modes during the development of cavitation and turbulent oscillations in the pipeline network. It has been shown that the nature of energy processes in the considered cases is periodic constant power fluctuations in the analyzed time interval. The variable component in technological and energy signals of the electrohydraulic complex has been assessed. Their frequency analysis has been performed. The coefficient of power controllability of the electrohydraulic complex and its critical values, whereat the development of emergency modes is possible, have been determined. © 2022 IEEE.

关键词： Electric drives

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Dual-beam photothermal material trace detection method based on self-mixing interference

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Applied Optics 2025年第16期64卷 4549-4558页

作者： Yan Zhao Yunlong Zhi Hui Zhao Daming Dong Jigang Tong Chunling Tu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin 300384 China National Engineering Research Center for Intelligent Agricultural Equipment Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China Department of Computer Systems Engineering Faculty of ICT Tshwane University of Technology Pretoria 0188 South Africa

In this paper, a dual-beam photothermal self-mixing substance trace detection system is proposed. The crystal violet (CV) solution of the sample undergoes a thermal lens effect under the action of pump photoperiod excitation, and the refractive index changes cause the deviation of the probe beam, and the self-mixing interference (SMI) effect occurs when the modulated light returns to the cavity. By combining theoretical and experimental results, the power fluctuation of the SMI signal caused by the thermo-optic effect is linearly related to CV concentration and other parameters. At an excitation power of 24 mW, the detection limit can reach $8.0 \times {10^{- 8}}\;{\rm mol/L}$ . This method does not require labeling or complex CV pretreatment and has high sensitivity and flexibility, providing a guide for CV characterization in biological, environmental, and pharmaceutical research.

关键词： Gaussian beams Laser beams Optical fields Phase shift Refractive index Spatial resolution

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