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第41届中国控制会议

作者： Shanshan Fu Liling Ma Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper is aimed at the second-order linear multi-agent formation *** to the failure of the actuator in a node,the wrong interactive information is transmitted between nodes,so that the entire system cannot complete the expected task.A distributed adaptive fault isolation and fault tolerance method based on consistency theory is *** the consistency error variable is designed according to the connection relationship between nodes and the faulty node,which eliminates the influence of the faulty node on the neighbor ***,an overall distributed adaptive fault isolation and fault tolerance approach is designed according to the local information of neighbor *** stability of the designed approach is proved by constructing a reasonable Lyapunov *** results show that the proposed adaptive control approach has good robustness.

关键词： Fault Isolation Adaptive control Fault Tolerant control Uniformity

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A Multimodal Emotion Perception Model based on Context-Aware Decision-Level Fusion 41

A Multimodal Emotion Perception Model based on Context-Aware...

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第41届中国控制会议

作者： Yishan Chen Zhiyang Jia Kaoru Hirota Yaping Dai School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

A Multimodal Emotion Perception model with Audio and Visual modalities(MEP-AV) is proposed to detect the individual emotions in public *** framework of MEP-AV model consists of four parts,i.e.,data collection module,audio expression analysis module,visual expression analysis module and multimodal fusion *** order to ensure that the emotion perception results meet the requirement of short-term continuity,a Context-Aware Decision-Level Fusion(CADLF) model is proposed and applied in multimodal fusion *** CADLF model estimates the affective status by using context information of multimodal *** short-term continuity is considered to improve the accuracy of the emotion perception *** experiment results evaluated by various metrics demonstrate that the performance of the multimodal structure is improved compared with that of unimodal emotion *** MEP-AV model using multimodal fusion algorithm provides the accuracies of70.89% and 77.07% in valence and arousal *** F1-scores reaches 70.2% and 75.6% respectively,indicating the boost performance on emotion perception.

关键词： Emotion Perception Decision-level Fusion Context-aware

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Distributed adaptive stabilization for stochastic nonlinear systems with unknown boundaries: a novel fixed-time stability in probability

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Nonlinear Dynamics 2025年 1-15页

作者： Zhu, Jiahui Xie, Liping Zhang, Kanjian The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China Advanced Ocean Institute of Southeast University Nantong China

This paper investigates the adaptive fixed-time stabilization problem for a class of strict-feedback stochastic nonlinear systems with unknown parameter vectors and unbounded but estimable nonlinear boundary functions. By employing distributed Lyapunov functions for state-space partitioning and distinct error transformations, this paper ensures system states converge to zero in a fixed-time regardless of initial conditions and stochastic disturbances. This paper introduces a distributed controller design that uniquely combines adaptive backstepping with the adding one power integrator method, restricting tracking errors to a positive invariant set to avoid the inherent singularity risks in traditional backstepping-based stochastic control. Unlike existing fixed-time control approaches for stochastic systems, which are typically limited to bounded uncertainties or rely on fuzzy logic with high computational overhead, this paper promotes a method handles fully unknown and unbounded nonlinear boundaries by means of adaptive estimation, thereby completely eliminating the redundant terms inherent in fuzzy approximations and enhancing 30–40% computing efficiency. Two simulations evaluate the robustness and efficacy of the proposed method under diverse initial conditions and stochastic disturbances, using settling time within the theoretically derived fixed convergence time to validate its practical applicability.

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Robust Model Predictive control for PMSM Drives Against Parameter Mismatch 41

Robust Model Predictive Control for PMSM Drives Against Para...

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第41届中国控制会议

作者： Luwei Shao Wei Shen Fan Li Chuanyu Ge State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

As an advanced control method of permanent magnet synchronous motor(PMSM),finite control set model predictive control(FCS-MPC) has earned widespread attention for its advantages of intuitive concept,splendid dynamic performance and capability of handling the constraints and ***,the dependence on the model parameter accuracy is the main barrier for FCS-MPC to be applied to the industry *** order to solve this issue,this paper presents a robust FCS-MPC against parameter *** proposed strategy utilizes the prediction error in the d-and q-axis currents during the past instant to calculate the compensation which should be added to the predicted currents in the next ***,the cost function in the proportional-integral form is designed as ***,the simulation results and experimental results prove the proposed method's effectiveness in suppressing the influence of model parameter mismatch on the control performance of PMSM.

关键词： permanent magnet synchronous motor finite control set model predictive control parameter mismatch

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An Adversarial Video Moment Retrieval Algorithm 41

An Adversarial Video Moment Retrieval Algorithm

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第41届中国控制会议

作者： Mohan Jia Zhongjian Dai Yaping Dai Zhiyang Jia School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In one-stage methods for video moment retrieval,the common representations indirectly supervised by boundary prediction fail to fully preserve the inherent characteristic of the video and query,which limits the retrieval *** solve this problem,an Adversarial Video Moment Retrieval(AVMR) algorithm is proposed to learn the common representations with modality invariance and cross-modal *** is implemented through the process of adversarial learning between a feature projector and a modality *** feature projector tries to generate a modality-invariant common representation and to confuse the modality *** modality classifier tries to discriminate between different modalities based on the generated representation by the feature *** triplet constraints are further imposed on the feature projector to preserve the underlying cross-modal semantic structure of *** experimental results show that AVMR surpasses the baseline Attentive Cross-modal Relevance Matching(ACRM) by 1.10% and 1.73% in the "mIoU" metric on two public datasets Charades-STA and TACoS,respectively.

关键词： Video Moment Retrieval Cross-modal Retrieval Deep learning Adversarial Learning

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LAUNet:A Latent Action Units Network for Facial Expression Recognition 41

LAUNet:A Latent Action Units Network for Facial Expression R...

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第41届中国控制会议

作者： Junlin Zhang Kaoru Hirota Yaping Dai Sijie Yin School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The inter-class similarity of facial expressions is one of the key challenges in Facial Expression Recognition(FER).In this manuscript,a Latent Facial Action Units Network(LAUNet) is proposed for the problem of inter-class similarity of facial expressions in *** proposed method recognizes subtle differences between facial expressions by learning Latent Facial Action Units Features(LAUFs).Specifically,LAUNet is composed of two parts:the Latent Facial Action Units Features Extraction Network(LEN) and the Latent Facial Action Units Selection Network(LSN).Firstly,LEN extracts LAUFs from the feature map of the backbone using the spatial attention ***,taking advantage of the channel attention mechanism,LSN captures the latent relationships between features from LAUFs to select effective features for *** are performed on the dataset after removing the invalid data of non-face images from the original FER2013 *** with some previous state-of-the-art methods,LAUNet achieves the highest accuracy rate of 71.31%.Depending on the backbone,LAUNet can improve the accuracy by up to 5.46% compared to the original architecture of the backbone.

关键词： Facial Expression Recognition Attention Mechanism Computer Vision

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Topological edge state analysis of hexagonal phononic crystals

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Acta Mechanica Sinica 2022年第3期38卷 78-85,I0002页

作者： Kai Zhang Fang Hong Je Luo Zichen Deng School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi'an 710072China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical UniversityXi'an 710072China

In this study,we propose valley phononic crystals that consist of a hexagonal aluminum plate with six chiral arrangements of *** phononic crystals were introduced into a topological insulator(TI)system to produce topologically protected edge waves(TPEW s)along the topological *** implementation of chiral topological edge states is different from the implementation of topological edge states of systems with *** the conventional breaking of mirror symmetry,a new complete band with topological edge modes gap was opened up at the Dirac point by tuning the difference in lengths of the ligaments in the chiral unit *** investigated the dispersion properties in chiral systems and applied the dispersion properties to waveguides on the interfaces to achieve designable route ***,we simulated the robust propagation of TPEWs in different routes and demonstrated their immunity to backscattering at ***,the existence of the valley Hall effect in chiral systems was *** study findings may lead to the further study of the topological states of chiral materials.

关键词： Phononic crystals Topologically protected edge waves Chiral unit cells Topological insulator

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Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 231-239页

作者： Yahui Liu Bin Tian Yisheng Lv Lingxi Li Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190 IEEE the Transportation and Autonomous Systems Institute(TASI)and the Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis(IUPUI)Indianapolis 46202 USA

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://***/yahuiliu99/PointC onT.

关键词： Content-based Transformer deep learning feature aggregator local attention point cloud classification

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Lattice thermal conductivity switching via structural phase transition in ferromagnetic VI_(3)

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Chinese Physics B 2023年第5期32卷 20-26页

作者：吴超刘晨晗 Laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China Micro-and Nano-scale Thermal Measurement and Thermal Management Laboratory School of Energy and Mechanical EngineeringNanjing Normal UniversityNanjing 210023China Jiangsu Key Laboratory for Numerical Simulation of Large-Scale Complex Systems Nanjing Normal UniversityNanjing 210023China Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments School of Mechanical EngineeringSoutheast UniversityNanjing 211100China

The realization of reversible thermal conductivity through ferromagnetic ordering can improve the heat management and energy efficiency in magnetic materials-based ***_(3),as a new layered ferromagnetic semiconductor,exhibits a structural phase transition from monoclinic(C2/m)to rhombohedral(R3^(-))phase as temperature decreases,making it a suitable platform to investigate thermal switching in magnetic phase transition *** work reveals that the thermal switching ratio of VI_(3)can reach 3.9 along the *** properties analysis indicates that the C2/m structure is stiffer than the R^(-)one,causing the larger phonon velocity in C2/m ***,due to the fewer phonon branches in C2/m phase,the number of phonon–phonon scattering channels in C2/m phase is smaller compared to that of R^(-)*** the larger phonon velocity and the longer phonon lifetime lead to larger lattice thermal conductivity in C2/m *** study uncovers the mechanical and thermal properties of VI_(3),which provides useful guides for designing magnetic materials-based devices such as thermal switch.

关键词： thermal switching ferromagnetic ordering phonons

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Multi-task Learning Based Single Temporal Remote Sensing Image Change Detection 12

Multi-task Learning Based Single Temporal Remote Sensing Ima...

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12th International Conference on Computing and Pattern Recognition, ICCPR 2023

作者： Yang, Peixuan Cao, Yichao Lu, Xiaobo College of Software Engineering Southeast University JiangSu NanJing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education JiangSu NanJing China School of Automation Southeast University JiangSu NanJing China

ISBN: (纸本)9798400707988

Change Detection is a classic and fundamental task in remote sensing(RS), and has accomplish remarkable achievement on bitemporal image based methods. However, bitemporal images are very expensive and needs professional researchers to align and label the paired images. Furthermore, most bitemporal image based methods are only semantic-aware not instance-aware, which indicates these methods only use paired images' semantic information. Thus, we propose a method that only needs unpaired RS images with semantic labels. In this paper, we introduce multi-task learning into change detection progress, which comprises four major parts: Boundary-Aware Module, Contextual-Aware Module, Segmentation Module, Change Detection Module. At first, we construct Boundary-Aware Module and Contextual-Aware Module to extract sharp boundary and dense contextual features. Then we feed the feature maps to Change Detection Module and Segmentation Module to accomplish the subtasks. The comprehensive experiments on a single temporal image dataset demonstrate the efficiency of our approach over other bitemporal image based methods, and the experimental results shows our approach is competitive with other methods while all methods was trained on bitemporal image dataset. © 2023 ACM.

关键词： Change detection

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