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Robust Practical Stabilization for Complex Dynamical Networks With DoS Attacks and Actuator Saturation

IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3108-3118页

作者： Shi, Xueya Peng, Zhinan Yu, Junzhi Li, Hongfei Southwest University College of Electronic and Information Engineering Chongqing400715 China Sichuan Artificial Intelligence Research Institute Yibin644000 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China

This article addresses the problem of designing an attack-resilient adaptive event-triggered (AET) controller for complex dynamical networks (CDNs) under DoS attacks and actuator saturation, with a focus on robust practical stability (RPS). First, considering the impact of DoS attacks on closed-loop systems, an AET controller against DoS attacks is designed. Unlike other event-triggered controllers, the complete timeline is divided, and the AET controller is built with two switching modes based on the intervals of dormant and active periods of DoS attacks in which the system is located. Second, to reconcile AET controller with actuator saturation, a switched system modeling approach is established that explicitly incorporates saturation constraints into the coupled network dynamics. Third, a switched Lyapunov-Krasovskii functional (LKF) is proposed, with which sufficient conditions are provided to ensured the RPS, and a joint design strategy is developed for the desired triggered matrix and feedback gain using linear matrix inequalities (LMIs). Moreover, the results are generalized to the case of actuator faults, indicating that the system is able to achieve RPS with actuator faults. Finally, the proposed method is verified through an example. © 2013 IEEE.

关键词： Lyapunov functions

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Kinematic Parameter Calibration for Parallel Robot Based on Robust Estimation and PCR Algorithm 7

Kinematic Parameter Calibration for Parallel Robot Based on ...

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7th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Wang, Jin Zhang, Renge Hu, Weijun Zhang, Haiyun Lu, Guodong Chen, Silu Luo, Jingbo School Of Mechanical Engineering Zhejiang University State Key Laboratory Of Fluid Power And Mechatronic Systems Hangzhou310027 China School Of Robotics Ningbo University Of Technology Ningbo315211 China Robotics Institute Of Zhejiang University Hangzhou310027 China Zhejiang Qiantang Robot And Intelligent Equipment Research Co. Ltd Hangzhou310018 China Ningbo Institute Of Materials Technology And Engineering Chinese Academy Of Sciences Ningbo315201 China

ISBN: (纸本)9798350361445

Due to the existence of redundant identification parameters and parallel branch chains, the nonlinear error model of parallel robot is likely to produce multicollinearity, which will lead to the undesirable ill-conditioned identification matrix. Though PCR method can modify the ill-conditioned identification matrix, it is still susceptible to the gross error of the original data. In terms of these problems, this paper proposes a parameter calibration algorithm for parallel robot based on robust estimation and principal component regression (RE-PCR). Firstly, the linear identification model is established based on the closed-loop vector chain perturbation theory to improve the identification accuracy. On this basis, for the configuration types with redundant identification parameters and parallel branch chains, PCR is used to modify the ill-conditioned matrix and a robust estimation (RE) algorithm is designed to improve the resistance capacities of PCR to gross error data points. Finally, through the identification experiment based on 4PPa-2PaR parallel robot, the proposed algorithm demonstrates higher efficiency and stronger robustness in comparison with traditional methods. © 2024 IEEE.

关键词： Parameter estimation

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DORM: Distance-based opportunistic routing and medium access protocol for multi-AUV monitoring system 23

DORM: Distance-based opportunistic routing and medium access...

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2nd International Conference on Networks, Communications and information technology, CNCIT 2023

作者： Qiu, Tianyou Li, Yiping Feng, Xisheng School of Information Science and Technology University of Science and Technology of China Anhui230026 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Key Laboratory of Marine Robotics Liaoning Province Shenyang110169 China

ISBN: (纸本)9798400700620

In a multi-AUV (autonomous underwater vehicle) monitoring system, each vehicle uploads sensor data to the surface central control platform through underwater acoustic communication, and the control platform sends commands or task files to AUVs. For a multi-AUV system with many vehicles and a large-scale underwater network, it is a challenge to design protocols to achieve reliable, low-latency, and energy-efficient communication due to the unique characteristics of underwater acoustic channels. We propose a distance-based opportunistic routing-MAC protocol (DORM), which combines opportunistic routing and CSMA, using distance and hop counts information to determine backoff time and forwarding priority. We conducted simulation experiments to analyze the performance of DORM and compared it with P-AUV and Probabilistic Broadcast (PB). The results show that DORM ensures reliable transmission and has apparent advantages in latency and energy efficiency. © 2023 Owner/Author.

关键词： Routing protocols

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DD-Net: Dynamic Network Architecture for Optimized Curve Segmentation and Reduce Computational Redundancy 27th

DD-Net: Dynamic Network Architecture for Optimized Curve Seg...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Cao, Yunxiang Chen, Li Wang, Yubo Feng, Zhida Tian, Jing School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China Institute of Systems Science National University of Singapore Singapore Singapore

ISBN: (纸本)9783031783821

Curvilinear Structure segmentation has numerous applications in various fields, including providing a better understanding of defects such as cracks on roads or walls, thereby assessing the structural safety of buildings. Numerous curve segmentation methods based on Convolutional Neural Networks(CNN) have been developed in recent years. However, preserving feature integrity remains a challenge. To address this issue, this paper introduces a double dynamic network, called DD-Net, which consists of a dynamic structure for training and dynamic masking for inference. Firstly, to enhance the nonlinearity of the model, a paradigm to auto-adjust the CNN structure via a trainable module is formed for better fine-grained feature extraction. This dynamic structure (DS) paradigm enables a trade-off to extract or discard the feature data in the model training. Due to the data heterogeneity between the training and inference data, models may contain some useless nodes that are less effective during inference. The dynamic masking (DM) is proposed to omit the useless nodes based on the score difference between the train and inference feature statistics, thereby reducing redundant computations. To further improve the model’s performance on thin-curve segmentation and to preserve feature integrity, we introduce a non-curve suppression (NCS) module. This module focuses on background information while considering foreground prediction to address noisy conditions. The experimental results show that our DD-Net achieves promising results on three benchmark datasets and outperforms state-of-the-art curve segmentation models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Depth image restoration method based on improved FMM algorithm 2021

Depth image restoration method based on improved FMM algorit...

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2021 13th International Conference on Machine Learning and Computing, ICMLC 2021

作者： Li, Lin Wu, Huaiyu Chen, Zhihuan Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781450389310

Aiming at the lack of depth information obtained by Kinect sensor, the collected depth images have holes, noise that affect subsequent practical applications such as the accuracy of semantic map construction , proposed a method of improved FMM algorithm to improve the quality of depth images. Firstly, clustering color images by K-means, the result as a guide image;Secondly, according to the source of the holes, it is divided into object surface holes and occlusion holes;The holes introduced by the surface holes of the object are repaired by the improved Fast Marching Method algorithm(FMM), the occlusion holes are filled by the Directional Joint Bilateral Filter(DJBF), and finally the adaptive median filter is used to denoise. The experimental results show that the way can effectively repair holes and the edge details of the depth map are clearer, and more importantly, the restored point cloud image is more complete. © 2021 ACM.

关键词： Median filters

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Off-axis digital holographic phase compensation recovery method based on Gaussian filtering 4

Off-axis digital holographic phase compensation recovery met...

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4th International Conference on Optics and Image Processing, ICOIP 2024

作者： Dong, Wenbo Yu, Lei Nie, Jiafa College of information and Communication Engineering Harbin Engineering University Heilongjiang Harbin150001 China Heilongjiang Collaborative Innovation Center of Advanced Intelligent Perception Technology Heilongjiang Harbin150001 China The Academy of Robotics Engineering Harbin Far East Institute of Technology Heilongjiang Harbin150001 China

ISBN: (纸本)9781510682481

A novel approach utilizing a Gaussian filtering is presented to eliminate aberrations in the phase recovery for off-axis digital holography. After applying the Fourier-transform-based method to the off-axis hologram, a complex amplitude map containing object phase and phase aberrations can be obtained. A Gaussian filter is then employed to extract the phase aberrations map from the complex amplitude map. In this case, the object phase can be reconstructed through a division between the complex amplitude map and the phase aberration map. The proposed method does not require the sample-free hologram containing aberration information and avoids complex procedures such as surface fitting or spectral filtering. Experimental result shows that the proposed method can realize accurate and fast off-axis digital holographic phase compensation recovery. © 2024 SPIE.

关键词： Holograms

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Deep Learning for Biomarkers Discovery in Auto-inflammatory Disorders

Deep Learning for Biomarkers Discovery in Auto-inflammatory ...

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2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Papagiannopoulos, Orestis D. Papaloukas, Costas Fotiadis, Dimitrios I. University of Ioannina Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering IoanninaGR 45110 Greece University of Ioannina Biomedical Research Institute - Forth Dept. of Biological Applications and Technology IoanninaGR 45110 Greece University of Ioannina Biomedical Research Institute - Forth Dept. of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems IoanninaGR 45110 Greece

ISBN: (纸本)9798350383386

A novel feature selection approach is presented for the identification of potential biomarkers in auto-inflammatory disorders. It involves training a deep neural network for binary classification, and subsequently selecting features based on the most significant shifts in neuron weight contributions. The findings demonstrate enhanced performance against the standard false discovery rate analysis, as evidenced by the improved classification metrics (~11% increase in sensitivity) when the selected features are *** Relevance: The improved performance suggests that the selected features may be more accurate and effective in distinguishing auto-inflammatory diseases, thus having significant implications in early diagnosis, disease monitoring, and targeted treatment strategies. © 2023 IEEE.

关键词： Biomarkers

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Vehicle Automatic Charging System Guided Electric by 3D Vision and F/T Sensor 4

Vehicle Automatic Charging System Guided Electric by 3D Visi...

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4th International Conference on intelligent Autonomous systems, ICoIAS 2021

作者： Liu, Bin Lin, Yunhan Min, Huasong Wuhan University of Science and Technology Institute of Robotics and Intelligent Systems Wuhan China

ISBN: (纸本)9781665441957

In this paper, a new energy vehicle automatic charging system is built on the cooperative robot by using 3D vision and F/T sensor. In particular, aiming at the problem that the attitude error is not taken into account in the peg-in-hole problem of the existing system, this paper proposes a position and attitude adjustment method based on the classification of force and torque information, which divides the contact force and torque obtained by the F/T sensor into nine categories. According to different classification results, different compensation strategies are adopted to adjust the motion control, and finally the charging plug is inserted accurately and flexibly into the charging port. Finally, the random contact data classification experiment and the automatic charging actual insertion experiment are designed. the experimental results show that the accuracy of the classifier is 92.59%, and the success rate of insertion is 94%. With these two experiments, the feasibility of our system is verified from the aspects of precision rate, recall rate, F-Measure and actual insertion success rate of the classifier. © 2021 IEEE.

关键词： Cameras

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Language Models Hallucinate, but May Excel at Fact Verification

Language Models Hallucinate, but May Excel at Fact Verificat...

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2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024

作者： Guan, Jian Dodge, Jesse Wadden, David Huang, Minlie Peng, Hao The CoAI group DCST Institute for Artificial Intelligence China State Key Lab of Intelligent Technology and Systems China Beijing National Research Center for Information Science and Technology China Tsinghua University Beijing100084 China Allen Institute for AI United States University of Illinois Urbana-Champaign United States

ISBN: (纸本)9798891761148

Recent progress in natural language processing (NLP) owes much to remarkable advances in large language models (LLMs). Nevertheless, LLMs frequently "hallucinate," resulting in non-factual outputs. Our carefully-designed human evaluation substantiates the serious hallucination issue, revealing that even GPT-3.5 produces factual outputs less than 25% of the time. This underscores the importance of fact verifiers in order to measure and incentivize progress. Our systematic investigation affirms that LLMs can be repurposed as effective fact verifiers with strong correlations with human judgments. Surprisingly, FLAN-T511B, the least factual generator in our study, performs the best as a fact verifier, even outperforming more capable LLMs like GPT3.5 and ChatGPT. Delving deeper, we analyze the reliance of these LLMs on high-quality evidence, as well as their deficiencies in robustness and generalization ability. Our study presents insights for developing trustworthy generation models. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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A tripartite evolutionary game analysis of providing subsidies for pick-up/drop-off strategy in carpooling problem

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Autonomous intelligent systems 2023年第1期3卷 50-65页

作者： Zeyuan Yan Li Li Hui Zhao Yazan Mualla Ansar Yasar College of Electronics and Information Engineering Tongji UniversityShanghai201804China. Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201203China. Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai201804China. UTBM CIAD UMR 7533F-90010 Belfort cedexFrance. IMOB Hasselt UniversityMaartelarenlaan 423500 HasseltBelgium.

Although the pick-up/drop-off(PUDO)strategy in carpooling offers the convenience of short-distance walking for passengers during boarding and disembarking,there is a noticeable hesitancy among commuters to adopt this travel method,despite its numerous ***,this paper establishes a tripartite evolutionary game theory(EGT)model to verify the evolutionary stability of choosing the PUDO strategy of drivers and passengers and offering subsidies strategy of carpooling platforms in carpooling *** model presented in this paper serves as a valuable tool for assessing the dissemination and implementation of PUDO strategy and offering subsidies strategy in carpooling ***,an empirical analysis is conducted to examine and compare the sensitivity of the parameters across various *** findings suggest that:firstly,providing subsidies to passengers and drivers,along with deductions for drivers through carpooling platforms,is an effective way to promote wider adoption of the PUDO ***,the decision-making process is divided into three stages:initial stage,middle stage,and mature *** strategy progresses from initial rejection to widespread acceptance among drivers in the middle stage and,in the mature stage,both passengers and drivers tend to adopt it under carpooling platform subsidies;the factors influencing the costs of waiting and walking times,as well as the subsidies granted to passengers,are essential determinants that require careful consideration by passengers,drivers,and carpooling platforms when choosing the PUDO *** work provides valuable insight into the PUDO strategy’s applicability and the declared results provide implications for traffic managers and carpooling platforms to offer a suitable incentive.

关键词： Carpooling problem Pick-up/drop-off strategy Offering subsidies strategy Tripartite evolutionary game theory Evolutionarily stable strategy

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