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检索条件"基金资助= in part by Guangdong Basic and Applied Basic Research Foundation under Grant 2024A1515030153"

共 165 条记录，以下是61-70 订阅

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Cooperative Enclosing Control of Multiple USVs with Collision Avoidance and Connectivity Maintenance 43

Cooperative Enclosing Control of Multiple USVs with Collisio...

引用

43rd Chinese Control Conference, CCC 2024

作者： Li, Mengdi Huang, Yunchang Dai, Shi-Lu South China University of Technology School of Automation Science and Engineering Guangzhou510641 China Zhuhai519000 China

ISBN: (纸本)9789887581581

This paper studies the enclosing control problem of multiple unmanned surface vehicles (USVs) without the velocity information of the target. The cooperative enclosing motions of multiple USVs are determined by maintaining the target-vehicle relative distance constraints and the inter-vehicle angle constraints. Barrier Lyapunov functions (BLFs) are introduced to ensure these relative distance and angle constraints. A cooperative enclosing control protocol is presented to achieve that all USVs converge to the desired spacing from neighboring vehicles while guaranteeing prescribed transient and steady-state performance. During encircle motion, collisions with target and neighboring USVs can be avoided, and communication connectivity, in the sense that and the relative distances between USVs and target are less than the limited sensing ranges of USVs, is always maintained. Numerical simulation results demonstrate the performance of the proposed control protocol. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Lyapunov functions

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Image-Based Formation Control of Unmanned Surface Vehicles with Field-of-View Constraints 43

Image-Based Formation Control of Unmanned Surface Vehicles w...

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43rd Chinese Control Conference, CCC 2024

作者： Yang, Jianan Huang, Yunchang Dai, Shi-Lu South China University of Technology School of Automation Science and Engineering Guangzhou510641 China Zhuhai519000 China

ISBN: (纸本)9789887581581

This paper presents an image-based control of a group of unmanned surface vehicles (USVs) to achieve leader-follower formation. Each follower in the USV group equipped with a monocular camera is driven to guarantee that the image coordinate of the leader's feature point converge to the reference image point in the image space. The monocular camera is limited field of view, which relates to the issue of visibility maintenance. A velocity observer is employed to estimate the surge and sway velocities of the leader. Using barrier Lyapunov synthesis, image-based leader-follower formation controllers are designed such that the image coordinate errors converge to a small neighborhood while guaranteeing prescribed transient and steady-state performance. The designed formation controllers depend only on the image information acquired by onboard camera without relative position measurements and an explicit communication. Simulation results show the efficacy of the proposed image-based leader-follower formation controllers. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Unmanned surface vehicles

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A Performance Investigation of Multimodal Multiobjective Optimization Algorithms in Solving Two Types of Real-World Problems

A Performance Investigation of Multimodal Multiobjective Opt...

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2024 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2024

作者： Chen, Zhiqiu Chen, Zong-Gan Jiang, Yuncheng Zhan, Zhi-Hui School of Computer Science South China Normal University Guangzhou China College of Artificial Intelligence Nankai University Tianjin China

ISBN: (纸本)9798331504755

In recent years, multimodal multiobjective optimization algorithms (MMOAs) based on evolutionary computation have been widely studied. However, existing MMOAs are mainly tested on benchmark function sets such as the 2019 IEEE Congress on Evolutionary Computation test suite (CEC′ 2019), and their performance on real-world problems is neglected. In this paper, two types of real-world multimodal multiobjective optimization problems in feature selection and location selection respectively are formulated. Moreover, four real-world datasets of Guangzhou, China are constructed for location selection. An investigation is conducted to evaluate the performance of seven existing MMOAs in solving these two types of real-world problems. An analysis of the experimental results explores the characteristics of the tested MMOAs, providing insights for selecting suitable MMOAs in real-world applications. © 2024 IEEE.

关键词： Optimization algorithms

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A Knowledge Archive-Based Framework for Multitask Multimodal Optimization Problems

A Knowledge Archive-Based Framework for Multitask Multimodal...

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2024 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2024

作者： Lin, Guo-Yun Chen, Zong-Gan Li, Jian-Yu Jiang, Yuncheng Zhan, Zhi-Hui School of Computer Science South China Normal University Guangzhou China College of Artificial Intelligence Nankai University Tianjin China

ISBN: (纸本)9798331504755

Evolutionary computation algorithms have been extensively studied to locate multiple global peaks in multimodal optimization problems (MMOPs). However, multitask multimodal optimization, which aims to deal with multiple MMOPs simultaneously, is not sufficiently considered in the literature. In this article, a knowledge archive-based framework (KAF) is proposed to extract and transfer knowledge among different tasks to help locate more peaks in each task, which is generic and can be combined with existing multimodal optimization algorithms to solve multitask MMOPs (MTMMOPs). In KAF, two novel strategies are designed. Firstly, a transferred individual generation strategy (TIGS) is designed to construct knowledge archives based on found global peaks and to generate transferred individuals who carry elite knowledge. Secondly, an adaptive competitor matching strategy (ACMS) is designed to adaptively conduct knowledge transfer between a transferred individual and its nearest individual or the worst individual in the population. In the experiments, a benchmark set of MTMMOPs is constructed. KAF is combined with five existing multimodal optimization algorithms and experimental results validate the effectiveness of KAF. © 2024 IEEE.

关键词： Optimization algorithms

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IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency 41

IBD-PSC: Input-level Backdoor Detection via Parameter-orient...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Hou, Linshan Feng, Ruili Hua, Zhongyun Luo, Wei Zhang, Leo Yu Li, Yiming School of Computer Science and Technology Harbin Institute of Technology Shenzhen China Alibaba Group China University of Science and Technology of China China School of Information Technology Deakin University Australia School of Information and Communication Technology Griffith University Australia Nanyang Technological University Singapore

Deep neural networks (DNNs) are vulnerable to backdoor attacks, where adversaries can maliciously trigger model misclassifications by implanting a hidden backdoor during model training. This paper proposes a simple yet effective input-level backdoor detection (dubbed IBD-PSC) as a 'firewall' to filter out malicious testing images. Our method is motivated by an intriguing phenomenon, i.e., parameter-oriented scaling consistency (PSC), where the prediction confidences of poisoned samples are significantly more consistent than those of benign ones when amplifying model parameters. In particular, we provide theoretical analysis to safeguard the foundations of the PSC phenomenon. We also design an adaptive method to select BN layers to scale up for effective detection. Extensive experiments are conducted on benchmark datasets, verifying the effectiveness and efficiency of our IBD-PSC method and its resistance to adaptive attacks. Codes are available at BackdoorBox. Copyright 2024 by the author(s)

关键词： Deep neural networks

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Adaptive Cooperative Path Following Control for Autonomous Surface Vehicles via Path-Dependent Constraints

Adaptive Cooperative Path Following Control for Autonomous S...

引用

2024 China Automation Congress, CAC 2024

作者： Zhang, Yixu Wen, Penghai Dai, Shi-Lu School of Automation Science and Engineering South China University of Technology Guangzhou China Zhuhai519000 China

ISBN: (纸本)9798350368604

This paper proposes an adaptive path-following cooperative control method for multiple underactuated autonomous surface vehicles (ASVs). To satisfy the feasible region constructed by the environment boundaries, the path-dependent constraints based on path parameters are designed, rather than depending on the time variable directly. The universal barrier function is incorporated with the control design to handle the prescribed performance requirements, which further ensures the satisfaction of position and heading angle constraints. The transversal function is employed to address the underactuation issue such that ASVs can follow the desired path while maintaining a predefined formation. With the use of radial basis function (RBF) neural network and adaptive control technology, the position and heading angle errors converge to the equilibrium point in the presence of internal uncertain dynamics and external time-varying disturbances. Simulation results verify the effectiveness of the proposed control scheme. © 2024 IEEE.

关键词： Radial basis function networks

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A Multiobjective particle Swarm Optimizer based Localized Feature Selection for Imbalanced Fault Diagnosis 13

A Multiobjective Particle Swarm Optimizer based Localized Fe...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Gao, Lin Zhou, Yu Guo, Hainan Wu Kwong, Sam Tak College of Computer Science and Software Engineering Shenzhen University Guangdong Shenzhen China College of Management Shenzhen University Guangdong Shenzhen China Lingnan University Department of Computing and Decision Sciences Hong Kong

ISBN: (纸本)9798350308365

Modern fault diagnosis faces an imbalance issue at both the sample and feature levels. A common approach is to combine balancing strategies with feature selection algorithms to address this problem. However, this may result in feature subsets that cannot accurately represent the true data distribution. This paper proposes an imbalanced fault diagnosis method called RPLFS-MOBPSO, which combines region purity (RP) with local feature selection to achieve class balance implicitly by partitioning local regions. RP is used as a new objective in the optimization process to achieve accurate fault detection. The adaptive reference point method from Non-Dominated Sorting Genetic Algorithm III is employed to maintain a diverse and evenly distributed external archive. On both the simulated Tennessee Eastma (TE) benchmark datasets and the real bearing experimental bench datasets, the proposed method achieves the best results compared to two LFS methods and four imbalanced ensemble algorithms based on different balancing strategies. Our source codes are available at: https://***/EMRGSZU/papers-code/tree/main/RPLFS-MOBPSO. © 2024 IEEE.

关键词： Genetic algorithms

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Monitoring Method for Pollution Class of Roof Insulators in EMUs Using Lissajous Figure and Morphologic Characters

Monitoring Method for Pollution Class of Roof Insulators in ...

引用

2024 IEEE China International Youth Conference on Electrical Engineering, CIYCEE 2024

作者： Jiang, Weihui Zhang, Lele Wang, Dongyang Liu, Bokai Zhou, Lijun School of Electrical Engineering Southwest Jiao-tong University Sichuan Province Chengdu611756 China Shijiazhuang Power Supply Section of China Railway Beijing Bureau Group Co. Ltd Hebei Province Shijiazhuang China

ISBN: (纸本)9798331530174

Accurately grasping the surface pollution class (PC) of roof insulators is of great importance for the safe operation of electric multiple units (EMUs). In this paper, we propose a new method for monitoring the PC of roof insulators in EMUs. In this approach, the input voltage and the leakage current of the insulator are combined into a graph, i.e., a Lissajous figure with more characteristic information. The variation of the Lissajous figure under different factors is then studied. Digital image processing technique was used for morphological analysis of the Lissajous figure. The results show that the eccentricity of the insulator's Lissajous ellipse can be used as an effective monitoring index of the PC of roof insulators. © 2024 IEEE.

关键词： Lissajous figure pollution class Roof insulators

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Adaptive Formation Control of USVs-UAVs Heterogeneous Systems With Visibility Constraints in Obstacle Environments

Adaptive Formation Control of USVs-UAVs Heterogeneous System...

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2024 China Automation Congress, CAC 2024

作者： Qi, Yilin Wen, Penghai Dai, Shi-Lu School of Automation Science and Engineering South China University of Technology Guangzhou China Zhuhai519000 China

ISBN: (纸本)9798350368604

This paper presents a heterogeneous formation control algorithm for unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs) in obstacle environments. The control algorithm guides the followers to track their leaders and forms a desired formation. To simplify the design process, the dynamics models of underactuated USVs and quadrotor UAVs are described to be unified. Time-varying performance functions are applied to ensure that field-of-view constraints and collision avoidance requirements are met, and to guarantee the tracking errors to converge within a controllable range at the specified speed. Additionally, an artificial potential function is designed to ensure obstacle avoidance in obstacle environments. Finally, simulation results show the effectiveness of the proposed formation control algorithm. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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HFIP: High-Frequency Information Prompt Network for Single Image Dehazing

HFIP: High-Frequency Information Prompt Network for Single I...

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2024 International Symposium on Digital Home, ISDH 2024

作者： Li, Jufeng Feng, Yuxin Lin, Mouguang Su, Zhuo School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798331509873

Current dehazing methods perform well on synthetic haze datasets but often struggle with complex real-world scenarios. To enhance the model's generalization ability, we incorporate Fourier transform and Gaussian filter to capture frequency domain information. Based on this, we propose a high-frequency information prompt network to more effectively locate haze and restore texture details. Additionally, to address the issue of overly dark dehazing results commonly observed in networks trained on synthetic datasets, we introduce a brightness loss function based on threshold division, which effectively enhances the brightness of the output images. Through extensive experiments, our method demonstrates not only excellent dehazing performance in challenging and complex scenarios such as daytime fog and sandstorm, but also significant potential value for downstream applications. © 2024 IEEE.

关键词： Demulsification

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