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第41届中国控制会议

作者： Kai Wang Weijing Dou Haikun Wei Kanjian Zhang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Accurate photovoltaic power forecasting(PVPF) can ensure the stability of grid operation and the reliability of economic ***,PV power generation is greatly affected by weather conditions,thus more external information needs to be combined to improve the forecasting *** on the measured data and NWP data,this paper proposes a PSC-SVR model to forecast the intra-hour PV *** model consists of PV physical model(PSC) and support vector regression(SVR).PSC converts the irradiance as a priori feature of the model,including calculating the sun position,irradiance separation and transposition *** is used for the two-stage data fusion of NWP power modeling and power *** method was verified on 4 power stations in the public data set *** forecasting PV power in the next one hour,the average RMSE/MAE of all stations is 1.927 MW/1.167 MW,which decreases by 40%/55% compared with persistent model,6%/7% compared with NWP correction forecasting method,9%/13% and 32%/34% compared with the single measured data and single NWP *** above results show the effectiveness of our proposed model in multi-source data fusion and PV power forecasting.

关键词： Photovoltaic Power Forecasting NWP Data Fusion Physical Model Support Vector Regression

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Model Predictive Tracking control for Rigid Manipulators with Disturbance Rejection 41

Model Predictive Tracking Control for Rigid Manipulators wit...

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第41届中国控制会议

作者： Yihui Lu Linyan Han Jinhao Liu Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

A model predictive tracking control algorithm for rigid manipulators considering the existence of external time-varying disturbances is studied in this *** the field of manipulators,disturbances are *** the influence of disturbances will lead to poor control accuracy and even *** a two-degree-of-freedom(2-DoF) rigid manipulator,a composite algorithm combing model predictive control(MPC) and a generalized proportional integral observer(GPIO) is *** the proposed method,feedback linearization technology is used to decouple the *** order to improve the ability of disturbance rejection,a GPIO is used to estimate the lumped disturbances and the estimated values are added to the control law by feedforward *** is conducted to validate the proposed algorithm.

关键词： Model Predictive control(MPC) Manipulator Generalized Proportional Integral Observer(GPIO) Feedback Linearization

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Continuous Non-Singular Terminal Sliding Mode control for High Pressure Common Rail systems Using a FTDO 41

Continuous Non-Singular Terminal Sliding Mode Control for Hi...

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第41届中国控制会议

作者： Zheng Yuan Chen Dai Hao Sun Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

High pressure common rail(HPCR) technology has been widely applied in diesel *** tracking speed and the steady-state fluctuations of the rail pressure determine the performance of the HPCR *** this paper,the fuel injection disturbance which has a main impact on rail pressure fluctuations is fully *** on fluid dynamics and Newtonian mechanics,a nonlinear model of the HPCR system is *** order to suppress the fuel injection disturbance,a finitetime disturbance observer(FTDO) based continuous non-singular terminal sliding mode controller(CNTSMC+FTDO) is designed based on the three-step analysis *** is proved that the system tracking error can converge to the equilibrium point in a finite ***,a group of simulations and experiments are conducted in Simulink and the more realistic AMESim environment respectively and the results verify the effectiveness and feasibility of the proposed algorithm.

关键词： High pressure common rail Non-singular terminal sliding mode FTDO Rail pressure control AMESim

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Interaction Torque Estimation for Robotic Manipulators under Low-Speed Condition 41

Interaction Torque Estimation for Robotic Manipulators under...

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第41届中国控制会议

作者： Yufeng He Wenwu Zhu Linyan Han Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper studies the interaction torque estimation method of the rigid robotic manipulator under the low-speed ***,a nonlinear friction model is established to analysis the influence of *** the noise into consideration,a least square identification method is ***,a finite-time extended state observer is established to estimate the interaction torque,which is capable of estimating time-varying *** stability of the system is demonstrated based on the Lyapunov *** results are given to show the effectiveness of the proposed method.

关键词： Force estimation Robotic manipulator Stribeck friction Finite-time observer

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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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A Hierarchical Formation-Containment control Scheme for Second-Order Multi-agent systems 7th

A Hierarchical Formation-Containment Control Scheme for Sec...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Cao, Yue Wang, Xiangyu Chen, Yangyang School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

ISBN: (纸本)9789819733231

In this paper, a hierarchical formation-containment control scheme is proposed for second-order multi-agent systems. The proposed hierarchical scheme decouples the control task into two layers, i.e., reference signal generator and agents’ tracking controllers. First, a reference signal generator is designed in Layer 1 for leader agents and follower agents, respectively, to produce the formation reference signals and containment reference signals, whose outputs "achieve" formation-containment asymptotically. Second, tracking controllers are designed in Layer 2 for each agent to track the reference signal. The proposed hierarchical formation-containment scheme realizes formation-containment asymptotically. The simulations are performed to validate the effectiveness and practicality of the scheme. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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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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Pylon Reconstruction Based on NeRF 14

Pylon Reconstruction Based on NeRF

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14th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2024

作者： Hu, Zijian Wang, Chenxing Southeast University School of Automation Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350361889

In this paper, we propose a pylon reconstruction method based on Neural Radiance Fields (NeRF) technology. The advantage of this method lies in its ability to reconstruct pylons from images, with a multi-view model maintaining good performance even under complex lighting and occlusion conditions. We demonstrate the process of using NeRF to reconstruct electric power towers through experiments. During the experimental process, we collect images of electric power towers from different environments and angles, then apply NeRF to process these images, using deep learning to learn and generate a network model capable of expressing the scene. The experimental results show that our method can complete the reconstruction of scenes with only image inputs, and the reconstructed models have a certain accuracy in terms of geometric details and textures. © 2024 IEEE.

关键词： Deep learning

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