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A self-correction algorithm for positioning error in sequential point bending tests of a microbeam for Young’s modulus based on atomic force microscopy 认领 引用
1
作者 Yuxin Liu Linyan Xu 《Nanotechnology and Precision Engineering》 EI CAS CSCD 2025年第3期131-137,共7页
The single-point bending method,based on atomic force microscopy(AFM),has been extensively validated for characterizing the structural mechanical properties of micro-and nanobeams.Nevertheless,the influence of AFM pro... The single-point bending method,based on atomic force microscopy(AFM),has been extensively validated for characterizing the structural mechanical properties of micro-and nanobeams.Nevertheless,the influence of AFM probe loading and positioning has yet to be subjected to comprehensive investigation.This paper proposes a novel bending-test method based on sequential loading points,in which a series of evenly distributed loads are applied along the length of the central axis on the upper surface of the cantilever.The preliminary measured values of Young’s modulus for an unknown alloy material were 193,178,and 176 GPa,exhibiting a considerable degree of dispersion.An algorithm for self-correction of the positioning error was developed,and this resulted in a positioning error of 53 nm and a final converged Young’s modulus of 161 GPa. 展开更多
关键词 Microbeam structure Young’s modulus Sequential point bending test Self-correcting positioning error Atomic force microscopy
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A Novel Distributed Controller Design for Robust Global Coordination of MASs With Heterogeneous Saturation 认领 引用 被引量：1
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作者 Xiaoling Wang Shengnan Zhu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第1期230-232,共3页
Dear Editor,This letter addresses the challenge of achieving robust global coordination in multi-agent systems(MASs)subject to heterogeneous actuator saturation and additive input disturbances.We develop a novel distr... Dear Editor,This letter addresses the challenge of achieving robust global coordination in multi-agent systems(MASs)subject to heterogeneous actuator saturation and additive input disturbances.We develop a novel distributed control framework that strategically integrates a redesigned saturation function to handle the nonlinear actuator constraint and a high-gain feedback mechanism for effective disturbance rejection. 展开更多
关键词 robust global coordination disturbance rejection nonlinear actuator constraint distributed control multi agent systems actuator saturation distributed control framework heterogeneous actuator saturation
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String stability of disturbed switched vehicle platoon systems via robust event-triggered mechanism 认领 引用
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作者 Jiansong Chen Liwei Xu +2 位作者 Yan Wang Xianjian Jin Guodong Yin 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第3期376-385,共10页
This paper investigates the robust event-triggered control problem for vehicle platooning with a discrete event-triggered communication scheme.The communication topology of the vehicle platoon is described by a direct... This paper investigates the robust event-triggered control problem for vehicle platooning with a discrete event-triggered communication scheme.The communication topology of the vehicle platoon is described by a directed graph,and the packet loss process is modeled as a Markov chain.Considering the time delay and air resistance,a variable gain distributed controller is designed based on the event-triggered mechanism.By constructing an appropriate Lyapunov–Krasovskii functional and applying the stability theory of Markov jump systems and H∞ control method,sufficient conditions are derived to guarantee the ℒ2 stochastic string stability of the vehicle platoon.Furthermore,the upper bound of the H∞ performance index is obtained,which reflects the disturbance attenuation level of the platoon.Finally,simulation results are provided to demonstrate the effectiveness of the proposed control protocol. 展开更多
关键词 Vehicle platoon Robust event-triggered mechanism Switching topologies Disturbance String stability
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Robust control strategy for semi-active air suspension systems based on reinforcement learning with entropy theory 认领 引用
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作者 Da Wang Guoqing Zhang +3 位作者 Chunyang Qi Chuanxue Song Feng Xiao Liqiang Jin 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第7期541-554,共14页
This study proposes a robust control strategy for semi-active air suspension systems(SASS)based on entropy theory.The multi-objective optimization of a system can be described as a long-term problem using entropy valu... This study proposes a robust control strategy for semi-active air suspension systems(SASS)based on entropy theory.The multi-objective optimization of a system can be described as a long-term problem using entropy values by innovatively introducing entropy theory.The state marginal probability of the SASS is incorporated into the reward function as the entropy value.This incorporation incentivizes the agent to focus on reducing the entropy value of the system state over a period of time during the exploration process,thereby reducing the degree of coupling between system states.This study also proposes an optimization strategy that introduces a state observer based on a variational auto-encoder.The observer can extract environmental features from historical states and expand the dimension of the state,thereby enhancing the generalization performance of the system under different road excitations.Bench test results show that the algorithm improves ride comfort while ensuring robustness.The root mean square(RMS)of body vertical acceleration decreased by 13.01%,while the RMS of dynamic tyre displacement only increased by 2.36%. 展开更多
关键词 Semi-active air suspension Entropy theory Robust controls Variational auto-encoder
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Robust Multitask Diffusion Bias-Compensated LMS Algorithm for Distributed Estimation with Noisy Link and Input 认领 引用
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作者 Xuzhao Chai Linru Zhang +2 位作者 Pengwei Wen Sheng Zhang Haiquan Zhao 《Journal of Beijing Institute of Technology》 EI CAS 2026年第2期137-149,共13页
This paper presents a robust multitask diffusion average bias compensation least mean square(RM-DABC-LMS)algorithm for distributed estimation in noisy input and communication link noise.The algorithm utilizes a robust... This paper presents a robust multitask diffusion average bias compensation least mean square(RM-DABC-LMS)algorithm for distributed estimation in noisy input and communication link noise.The algorithm utilizes a robust cost function based on the maximum Versoria criterion,incorporates bias compensation,and applies adaptive combination coefficients to reduce noise impacts.Theoretical analysis demonstrates the stability of the algorithm,providing closed-form expressions for the steady-state mean square deviation(MSD).A compression diffusion strategy is introduced to reduce communication cost of the RM-DABC-LMS algorithm,ensuring fast convergence and accurate estimation.Simulation results indicate that the proposed algorithm outperforms existing methods in noisy environments,achieving faster convergence and lower steady-state error. 展开更多
关键词 multitask networks robust bias compensation average estimate
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Robust Recommendation Adversarial Training Based on Self-Purification Data Sanitization 认领 引用
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作者 Haiyan Long Gang Chen Hai Chen 《Computers, Materials & Continua》 SCIE EI 2026年第4期840-859,共20页
The performance of deep recommendation models degrades significantly under data poisoning attacks.While adversarial training methods such as Vulnerability-Aware Training(VAT)enhance robustness by injecting perturbatio... The performance of deep recommendation models degrades significantly under data poisoning attacks.While adversarial training methods such as Vulnerability-Aware Training(VAT)enhance robustness by injecting perturbations into embeddings,they remain limited by coarse-grained noise and a static defense strategy,leaving models susceptible to adaptive attacks.This study proposes a novel framework,Self-Purification Data Sanitization(SPD),which integrates vulnerability-aware adversarial training with dynamic label correction.Specifically,SPD first identifies high-risk users through a fragility scoring mechanism,then applies self-purification by replacing suspicious interactions with model-predicted high-confidence labels during training.This closed-loop process continuously sanitizes the training data and breaks the protection ceiling of conventional adversarial training.Experiments demonstrate that SPD significantly improves the robustness of both Matrix Factorization(MF)and LightGCN models against various poisoning attacks.We show that SPD effectively suppresses malicious gradient propagation and maintains recommendation accuracy.Evaluations on Gowalla and Yelp2018 confirmthat SPD-trainedmodels withstandmultiple attack strategies—including Random,Bandwagon,DP,and Rev attacks—while preserving performance. 展开更多
关键词 Robustness adversarial defense recommendation system poisoning attack self-purification
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Robust nonlinear MPC for tracking piece-wise constant reference signals 认领 引用
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作者 Huahui Xie Li Dai +2 位作者 Zhongqi Sun Di-Hua Zhai Yuanqing Xia 《Control Theory and Technology》 EI CSCD 2026年第2期230-239,共10页
This work provides a robust model predictive control framework tailored for tracking piece-wise constant reference signals for nonlinear dynamics subject to additive disturbances.The approach integrates setpoint optim... This work provides a robust model predictive control framework tailored for tracking piece-wise constant reference signals for nonlinear dynamics subject to additive disturbances.The approach integrates setpoint optimization and robust constraint satisfaction into a unified optimization problem,guaranteeing the robust stability within a vicinity of an optimal admissible setpoint.A crucial feature of the approach is its ability to preserve recursive feasibility despite abrupt variations in the target.An offline implementation based on set-valued system representations is also discussed.Numerical examples demonstrate the effectiveness of the controller. 展开更多
关键词 Nonlinear model predictive control Setpoint tracking Robust control
Robust self-triggered switching control of autonomous ground vehicles with varying linear parameters 认领 引用
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作者 Yuanlong XIE Shuting WANG +3 位作者 Liquan JIANG Hu LI Hao WU Sheng-quan XIE 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第5期453-465,I0001-I0007,共13页
We propose a robust self-triggered switching control scheme for four-wheel-steering autonomous ground vehicles(FAGVs)to enhance tracking precision in the face of significant parameter variations.First,using the polyto... We propose a robust self-triggered switching control scheme for four-wheel-steering autonomous ground vehicles(FAGVs)to enhance tracking precision in the face of significant parameter variations.First,using the polytopic mechanism,the nonlinear dynamics of an FAGV are formulated as a switched linear parameter-varying system to accommodate parametric perturbations.With suitable dwell time,a novel self-triggered switching law is designed using energy density in terms of the tracking accuracy and system robustness;this satisfies the required control criteria while also preventing the Zeno phenomenon caused by traditional high-frequency switching.Through the application of multiple parameter-correlated Lyapunov functions,the resultant closed-loop system is ensured to be asymptotically stable with suitable auto-tuned gains.Finally,the efficacy and superiority of the proposed method are verified through experiments with an FAGV system. 展开更多
关键词 Varying linear parameters Autonomous ground vehicle Switching controller Zeno avoidance Robust control
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Lightweight and Robust Cross-Domain Microseismic Signal Classification Framework with Bi-Classifier Adversarial Learning 认领 引用
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作者 Dingran Song Feng Dai +2 位作者 Yi Liu Hao Tan Mingdong Wei 《Engineering》 SCIE EI CSCD 2026年第1期267-283,共17页
Automatic identification of microseismic(MS)signals is crucial for early disaster warning in deep underground engineering.However,three major challenges remain for practical deployment,namely limited resources,severe ... Automatic identification of microseismic(MS)signals is crucial for early disaster warning in deep underground engineering.However,three major challenges remain for practical deployment,namely limited resources,severe noise interference,and data scarcity.To address these issues,this study proposes the lightweight and robust entropy-regularized unsupervised domain adaptation framework(LRE-UDAF)for cross-domain MS signal classification.The framework comprises a lightweight and robust feature extractor and an unsupervised domain adaptation(UDA)module utilizing a bi-classifier disparity metric and entropy regularization.The feature extractor derives high-level representations from the preprocessed signals,which are subsequently fed into two classifiers to predict class probability.Through three-stage adversarial learning,the feature extractor and classifiers progressively align the distributions of the source and target domains,facilitating knowledge transfer from the labeled source to the unlabeled target domain.Source-domain experiments reveal that the feature extractor achieves high effectiveness,with a classification accuracy of up to 97.7%.Moreover,LRE-UDAF outperforms prevalent industry networks in terms of its lightweight design and robustness.Cross-domain experiments indicate that the proposed UDA method effectively mitigates domain shift with minimal unlabeled signals.Ablation and comparative experiments further validate the design effectiveness of the feature extractor and UDA modules.This framework presents an efficient solution for resource-constrained,noise-prone,and data-scarce environments in deep underground engineering,offering significant promise for practical implementations in early disaster warning. 展开更多
关键词 Deep learning Microseismic classification Lightweight design Noise robustness Unsupervised domain adaptation
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Novel robust cross-modal integration fusion model for rapid moisture content detection in concrete sand 认领 引用
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作者 Zhijian CAI Jun ZHANG +3 位作者 Xiaoling WANG Jiajun WANG Kehao ZHAO Guohua WU 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第7期711-729,I0033-I0042,共19页
The rapid and accurate detection of concrete sand moisture content(MC)is crucial for ensuring concrete quality.However,existing unimodal detection methods are constrained by limited representative features and lack ro... The rapid and accurate detection of concrete sand moisture content(MC)is crucial for ensuring concrete quality.However,existing unimodal detection methods are constrained by limited representative features and lack robustness.Multimodal operations often involve simple concatenation of features from different modalities,lacking potential interactivity among features.To address this issue,a novel robust cross-modal integration fusion model,which uses five branches to extract the features of images,near-infrared spectrum,and dielectric constant and a multilevel cross-modal integration fusion network to fuse these features,is proposed for the rapid detection of MC in concrete sand.Specifically,the multilevel cross-modal integration fusion network comprises a feature attention module,a cross-modal self-attention fusion module,and an integrated output module.The feature attention module enhances the feature representation from each modality,reducing the interference from redundant features and noise.The cross-modal self-attention fusion module employs a residual self-attention mechanism to deeply mine and fuse interactions between modalities while retaining low-level features,improving model accuracy and stability.The integrated output module is utilized to obtain more robust prediction results.The results show that the proposed model outperforms unimodal,traditional multimodal,and cross-modal methods on our concrete sand dataset,achieving excellent and robust prediction results for both machine-made sand(root mean square error ERMS=0.458,coefficient of determination R2=0.983,and residual predictive deviation DRP=7.900)and natural sand(ERMS=0.705,R2=0.984,and DRP=7.931).The detection time was within 71 s,significantly enhancing the detection frequency and efficiency,which provides a reliable solution for the rapid detection of MC in concrete sand. 展开更多
关键词 Concrete sand Rapid moisture content(MC)detection Cross-modal integration fusion Robust prediction
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Boundary Decision-Based Multi-Objective Robust Optimization for Microgrid Dispatching 认领 引用
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作者 Junjian Wu Jingliao Sun +2 位作者 Yejun Xiang Zhenyu Zhou Zhengchai Shi 《Energy Engineering》 EI 2026年第7期404-423,共20页
The inherent unpredictability of renewable energy generation poses significant challenges to the reliable and economic dispatch of grid-connected microgrids.In response,this paper proposes a novel robust optimization ... The inherent unpredictability of renewable energy generation poses significant challenges to the reliable and economic dispatch of grid-connected microgrids.In response,this paper proposes a novel robust optimization strategy grounded in uncertain boundary decision-making and enhanced through innovations in the multi-objective cross-entropy method.An uncertainty budget-aware environmental economic dispatch model is first established,integrating photovoltaic and wind power generation.By employing mathematical sophistication-particularly Lagrangian transformation-the proposed method effectively resolves embedded uncertainties,transforming the original model into a deterministic multi-objective optimization framework robust against renewable energy volatility.Furthermore,by incorporating the dynamic operational demands of microgrids,this paper culminates in a robust optimization approach that is both fundamentally based on and adaptively responsive to uncertainty boundaries.To address the critical challenges of convergence and diversity in multi-objective optimization,crossover operators and an adaptive parameter update mechanism are introduced,significantly refining the conventional multi-objective cross-entropy algorithm.Case studies demonstrate the rationality and effectiveness of the proposed dispatch strategy and corroborate the superior performance and applicability of the enhanced algorithm. 展开更多
关键词 Microgrid environmental economic dispatch uncertain boundary robust optimization multi-objective cross entropy algorithm
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A robustness analysis of joint predictions under a general linear model 认领 引用
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作者 TIAN Yong-ge JIANG Bo 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2026年第2期386-400,共15页
Robustness refers to the relative stability of statistical inference results with respect to assumption conditions of regression models, namely, when the model assumptions change slightly, wether the corresponding sta... Robustness refers to the relative stability of statistical inference results with respect to assumption conditions of regression models, namely, when the model assumptions change slightly, wether the corresponding statistical inference changes only slightly. This paper considers robustness analysis of joint predictions under a general linear model. We first establish the definitions and analytical expressions of Best Linear Unbiased Predictions(BLUPs) and Best Linear Minimum Bias Predictions(BLMBPs), and discuss algebraic and statistical properties of the BLUPs and the BLMBPs, including the robustness of joint predictions with respect to model matrices and covariance matrices under a general linear model by implementing the block matrix representation method and the matrix rank method. 展开更多
关键词 BLMBP BLUP covariance matrix general linear model model matrix rank robustness
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Robust Swin Transformer for Vehicle Re-Identification with Dynamic Feature Fusion 认领 引用
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作者 Saifullah Tumrani Abdul Jabbar Siddiqui 《Computers, Materials & Continua》 SCIE EI 2026年第5期605-620,共16页
Vehicle re-identification(ReID)is a challenging task in intelligent transportation,and urban surveillance systems due to its complications in camera viewpoints,vehicle scales,and environmental conditions.Recent transf... Vehicle re-identification(ReID)is a challenging task in intelligent transportation,and urban surveillance systems due to its complications in camera viewpoints,vehicle scales,and environmental conditions.Recent transformer-based approaches have shown impressive performance by utilizing global dependencies,these models struggle with aspect ratio distortions and may overlook fine-grained local attributes crucial for distinguishing visually similar vehicles.We introduce a framework based on Swin Transformers that addresses these challenges by implementing three components.First,to improve feature robustness and maintain vehicle proportions,our Aspect Ratio-Aware Swin Transformer(AR-Swin)preserve the native ratio via letterbox,uses a non-square(16×8)patch-embedding stem,and keeps fixed 7×7 token windows.Second,we introduce a Dynamic Feature Fusion Network(DFFNet)that adaptively integrates global Swin features with local attribute embeddings;such as color and vehicle type enablingmore discriminative representations.Third,our Regional Attention Blocks incorporate regionalmasks into the transformer’s windowed attentionmechanism,effectively highlighting critical details like manufacturer logos or lights.On VeRi-776,we obtain 82.55 mAP,97.26 Rank-1 and 99.23 Rank-5,and on VehicleID we obtain 91.8 Rank-1 and 97.75 Rank-5.The design is drop-in for Swin backbones and emphasizes robustness without increasing architectural complexity.Code:http://gffzz188fe103f8f1460asob5n696ukv6b6upk.ffgz.tsg.suse.edu.cn/sft110/Swinvreid. 展开更多
关键词 Vehicle ReID swin transformer aspect ratio robustness multi-attribute learning
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Robust Tracking Control of Automated Vehicles With Model Uncertainties:An Actor-Critic Learning Strategy 认领 引用
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作者 Zhao-Qing Liu Hao Xie +1 位作者 Lei Ding Liping Han 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第7期1773-1775,共3页
Dear Editor,This letter is concerned with the robust tracking control problem of automated vehicles(AVs).First,the dynamics of an AV is constructed by taking into account model uncertainties.Then,to guarantee the succ... Dear Editor,This letter is concerned with the robust tracking control problem of automated vehicles(AVs).First,the dynamics of an AV is constructed by taking into account model uncertainties.Then,to guarantee the successful completion of tracking tasks,an actor-critic learning-based robust tracking control scheme is designed.At last,formal stability analysis and experiment results are provided to verify the tracking performance of the designed control scheme. 展开更多
关键词 automated vehicles avs firstthe actor critic learning stability analysis taking account model robust tracking control control scheme automated vehicles model uncertainties
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Robust current tracking control for three-phase grid-connected inverters with LCL filter 认领 引用 被引量：1
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作者 LIU Wei WU Ben +2 位作者 SUN Wei-jie XUE Ying CAI Feng-huang 《控制理论与应用》 EI CAS CSCD 北大核心 2026年第1期41-51,共11页
This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons... This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters. 展开更多
关键词 grid-connected inverter internal model principle current tracking disturbance suppression robust control
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Robust Interfaces and Advanced Materials:Critical Designs and Challenges for High-Performance Supercapacitors 认领 引用
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作者 Yuzhao Liu Lanlan Feng +5 位作者 Mingfei Li Xiuyang Qian Chuanqi Sun Wenxuan Sun Yunshan Zheng Baohua Li 《Energy & Environmental Materials》 SCIE EI CAS CSCD 2026年第1期420-442,共23页
With the growing global energy demand and the pressing need for a clean energy transition,supercapacitors(SCs)have demonstrated significant application potential in electric vehicles,wearable electronics,and renewable... With the growing global energy demand and the pressing need for a clean energy transition,supercapacitors(SCs)have demonstrated significant application potential in electric vehicles,wearable electronics,and renewable energy storage systems owing to their rapid charge-discharge capability,exceptional power density,and prolonged cycle life.The improvement of their overall performance fundamentally depends on the synergistic design of electrode materials and electrolyte systems,as well as the precise regulation of the electrode-electrolyte interface.This review focuses on the key components of supercapacitors,systematically reviewing the design strategies of high-performance electrode materials,outlining recent advances in novel electrolyte systems,and comprehensively discussing the critical roles of interfacial reinforcement and optimization in enhancing device energy density,power performance,and cycling stability.Furthermore,interfacial engineering strategies and innovations in device architecture are proposed to address interfacial degradation in flexible SCs under mechanical stress.Finally,key future research directions are highlighted,including the development of high-voltage and wide-temperature-range electrolyte systems and the integrated advancement of multiscale in situ characterization techniques and theoretical modeling.This review aims to provide theoretical guidance and innovative strategies for material design,contributing toward the realization of next-generation supercapacitors with enhanced energy density and reliability. 展开更多
关键词 electrode materials electrolytes interface optimization robust interfaces supercapacitors
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A Robust Design Method for Low-Pressure Die Casting Process Based on Surrogate Models 认领 引用
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作者 Yunlang Zhan Fuhao Fan +4 位作者 Xilin Li Zhenfei Zhan Yongzhi Jiang Yutong Yang Shiyao Huang 《Computers, Materials & Continua》 SCIE EI 2026年第6期957-983,共27页
The batch-to-batch variability in low-pressure die casting(LPDC),caused by inherent process parameter fluctuations,poses a significant challenge to consistent quality.However,traditional single-point optimization meth... The batch-to-batch variability in low-pressure die casting(LPDC),caused by inherent process parameter fluctuations,poses a significant challenge to consistent quality.However,traditional single-point optimization methods ignore parameter fluctuations.This study presents a robust design framework to overcome this limitation.First,an integrated simulation workflow was established by coupling ProCAST casting simulation with Abaqus finite element analysis to predict shrinkage pore volume and load-bearing capacity(LBC).Subsequently,a dataset was constructed from the integrated simulations,and then served to develop a surrogate model using the Extreme Gradient Boosting algorithm.Finally,robust process windows were derived via an inverse search employing the swarm intelligence algorithm.The framework is implemented with a case study on A356 aluminum-alloy wheel casting.The results showed that the surrogate model for defect regression and LBC prediction has high prediction accuracy.SHapley Additive exPlanations analysis identified the interfacial heat-transfer coefficient and half-mold temperature as the dominant factors.Three optimization algorithms,Bayesian-optimized Particle Swarm Optimization(BO-PSO),Bayesian-optimized Genetic Algorithm(BO-GA),and Logistic-Chaos Sparrow Search Algorithm(LCSSA)were evaluated.LCSSA consistently identifies robust process windows satisfying both defect-control and LBC requirements across all target levels,whereas BO-PSO exhibits premature convergence at higher targets and BO-GA yields dispersed solutions with insufficient robustness.The proposed framework provides a systematic methodology for robust process-window design in LPDC applications. 展开更多
关键词 Low-pressure die casting robust design integrated simulation surrogate model optimization
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CalibRobustBEV:calibration-robust 3D object detection from BEV 认领 引用
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作者 Chunwang He Lu Zhang +1 位作者 Yuxuan Xiao Yanyong Zhang 《Journal of University of Science and Technology of China》 CAS CSCD 北大核心 2026年第1期13-22,I0001,共10页
Multi-modality sensor fusion has emerged as a prevailing trend in 3D object detection tasks.However,existing research predominantly emphasizes the efficient fusion of data from diverse sensors,overlooking the potentia... Multi-modality sensor fusion has emerged as a prevailing trend in 3D object detection tasks.However,existing research predominantly emphasizes the efficient fusion of data from diverse sensors,overlooking the potential severe consequences of calibration failures.In this paper,we present an innovative analysis and prediction of scenarios that could lead to fusion algorithm failures,along with introducing remedial measures to enhance model robustness.Specifically,leveraging our predicted outcomes,we proactively generate similar hazardous scenarios during the model training phase to facilitate generalization capabilities.Subsequently,we introduce a query mechanism during data fusion to identify the appropriate fusion target in the event of miscalibration.Evaluation on the nuScenes dataset demonstrates that our approach can mitigate model instability by up to 90%,and our framework can be seamlessly adapted to other fusion algorithms. 展开更多
关键词 3D object detection sensor fusion calibration robustness
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Robustness analysis of binary-coupled logistics-supply chain interdependent networks under load redistribution 认领 引用
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作者 Hai-Bo Yu Yan-Li Gao +3 位作者 Guang-Ming Chen Qiu-Yu Tang Chao Feng Lei Zhang 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第7期886-900,共15页
To capture the interdependencies between logistics and supply chain networks in real-world systems,this paper develops a load redistribution-based logistics-supply chain binary-coupled network(LSBCN)model.Employing a ... To capture the interdependencies between logistics and supply chain networks in real-world systems,this paper develops a load redistribution-based logistics-supply chain binary-coupled network(LSBCN)model.Employing a dynamic load redistribution strategy,we systematically investigate the robustness of the LSBCN under cascading failures.We evaluate network performance under both random and deliberate failures,thoroughly analyze the mechanisms of influence of capacity factor(β)and capacity index(γ)on network robustness,and design three optimization strategies:parameter optimization,critical edge protection,and redundant edge addition.Furthermore,we quantitatively examine the synergistic effects and cost-effectiveness among these strategies.The results reveal that capacity factors exert significant regulatory effects on network robustness;however,the marginal improvement diminishes beyond a critical threshold.Distinct optimal capacity parameter configurations correspond to different failure proportions.Protecting critical edges of the logistics network demonstrates superior robustness enhancement under random failures,whereas adding redundant edges proves more effective under deliberate failures.The synergistic effects between strategies exhibit strong dependence on both failure modes and proportions.Under random failures,critical edge protection should be prioritized,while under deliberate failures,redundant edge addition is preferable.These findings provide theoretical foundations and decision-making references for vulnerability assessment,collaborative optimization,and risk management in logistics-supply chain systems. 展开更多
关键词 binary-coupled logistics–supply chain networks load redistribution cascading failure robustness analysis
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Distributed Generalized Distributionally Robust Equilibrium Seeking for Dynamical Games Under Unknown Time-Varying Interference 认领 引用
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作者 Longcheng Liu Shuai Liu +2 位作者 Yiguang Hong Lihua Xie Guangchen Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第3期647-664,共18页
This paper investigates a distributed generalized Nash equilibrium-seeking problem in stochastic dynamical systems,focusing on two key challenges:1)nonlinear coupled constraints and nonlinear dynamics,and 2)nonconvex ... This paper investigates a distributed generalized Nash equilibrium-seeking problem in stochastic dynamical systems,focusing on two key challenges:1)nonlinear coupled constraints and nonlinear dynamics,and 2)nonconvex objectives influenced by disturbances with unknown time-varying distributions.To address these challenges,a distributionally robust game framework with an exact penalty is proposed.We introduce a first-order equilibrium concept suitable for nonconvex-nonsmooth settings and ensure finite-sample guarantees.Furthermore,a distributed zeroth-order feedback algorithm is proposed to solve the problem.This algorithm utilizes gradient estimators for the objective functions and subgradient estimators for the exact penalty terms.We provide a detailed analysis of the relationship between communication errors and the dynamic energy of the system,along with an expected upper bound for the zeroth-order gradient estimation.Our findings indicate that the expectation of the time-accumulated regret grows at a sublinear rate.Furthermore,as the distribution stabilizes,we show that the empirical distribution converges with O(1)sampling complexity. 展开更多
关键词 Distributionally robust game dynamical system equilibrium seeking non-convex non-smooth games stochastic game
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