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Distributed Economic MPC for Synergetic Regulation of the Voltage of an Island DC Micro-Grid

IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 734-745页

作者： Yi Zheng Yanye Wang Xun Meng Shaoyuan Li Hao Chen IEEE the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Haixi Institutes Chinese Academy of SciencesJinjiang 362216China

In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time *** on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction ***,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire *** voltage stabilization of the MG is achieved by this strategy with the cooperation of *** numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC.

关键词： Distributed model predictive control(DMPC) Lyapunovbased model predictive control micro-grid(MG) voltage control

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HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation

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Chinese Journal of Electronics 2023年第1期32卷 189-198页

作者： GUAN Qi SHENG Zihao XUE Shibei Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

Real-time six degrees-of-freedom(6D)object pose estimation is essential for many real-world applications, such as robotic grasping and augmented reality. To achieve an accurate object pose estimation from RGB images in real-time, we propose an effective and lightweight model, namely high-resolution 6D pose estimation network(HRPose). We adopt the efficient and small HRNetV2-W18 as a feature extractor to reduce computational burdens while generating accurate 6D poses. With only 33% of the model size and lower computational costs, our HRPose achieves comparable performance compared with state-of-the-art models. Moreover, by transferring knowledge from a large model to our proposed HRPose through output and feature-similarity distillations, the performance of our HRPose is improved in effectiveness and efficiency. Numerical experiments on the widely-used benchmark LINEMOD demonstrate the superiority of our proposed HRPose against state-of-the-art methods.

关键词： Knowledge engineering Computational modeling Pose estimation Grasping Benchmark testing Feature extraction Real-time systems

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Current-Aided Multiple-AUV Cooperative Localization and Target Tracking in Anchor-Free Environments

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 792-806页

作者： Yichen Li Wenbin Yu Xinping Guan Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China IEEE

In anchor-free environments,where no devices with known positions are available,the error growth of autonomous underwater vehicle(AUV)localization and target tracking is unbounded due to the lack of references and the accumulated errors in inertial *** paper aims to improve the localization and tracking accuracy by involving current information as extra *** first integrate current measurements and maps with belief propagation and design a distributed current-aided message-passing scheme that theoretically solves the localization and tracking *** on this scheme,we propose particle-based cooperative localization and target tracking algorithms,named CaCL and CaTT,*** AUV localization,CaCL uses the current measurements to correct the predicted and transmitted position information and alleviates the impact of the accumulated errors in inertial *** target tracking,the current maps are applied in CaTT to modify the position prediction of the target which is calculated through historical *** effectiveness and robustness of the proposed methods are validated through various simulations by comparisons with alternative methods under different trajectories and current conditions.

关键词： Anchor-free belief propagation cooperative localization current-aided target tracking

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Review and prospects on the low-voltage Na_(2)Ti_(3)O_(7) anode materials for sodium-ion batteries

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Journal of Energy Chemistry 2024年第1期88卷 446-460,I0011页

作者： Jun Dong Yalong Jiang Ruxing Wang Qiulong Wei Qinyou An Xiaoxing Zhang Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068HubeiChina State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200HubeiChina Xiamen Key Laboratory of High-Performance Metals and Materials College of MaterialsXiamen UniversityXiamen 361005FujianChina State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070HubeiChina

Due to its low cost and natural abundance of sodium,Na-ion batteries(NIBs)are promising candidates for large-scale energy storage *** development of ultralow voltage anode materials is of great significance in improving the energy density of ***-voltage anode materials,however,are severely lacking in *** all the reported insertion oxides anodes,the Na_(2)Ti_(3)O_(7) has the lowest operating voltage(an average potential of 0.3 V ***^(+)/Na)and is less likely to deposit sodium,which has excellent potential for achieving NIBs with high energy densities and high *** significant progress has been made,achieving Na_(2)Ti_(3)O_(7) electrodes with excellent performance remains a severe *** paper systematically summarizes and discusses the physicochemical properties and synthesis methods of Na_(2)Ti_(3)O_(7).Then,the sodium storage mechanisms,key issues and challenges,and the optimization strategies for the electrochemical performance of Na_(2)Ti_(3)O_(7) are classified and further ***,remaining challenges and future research directions on the Na_(2)Ti_(3)O_(7) anode are *** review offers insights into the design of high-energy and high-safety NIBs.

关键词： Sodium-ion batteries Low-voltage anode materials Na_(2)Ti_(3)O_(7) Electrochemical performances Electrochemical mechanism

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Spatial confinement of free-standing graphene sponge enables excellent stability of conversion-type Fe_(2)O_(3)anode for sodium storage

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Chinese Chemical Letters 2025年第3期36卷 544-549页

作者： Jun Dong Senyuan Tan Sunbin Yang Yalong Jiang Ruxing Wang Jian Ao Zilun Chen Chaohai Zhang Qinyou An Xiaoxing Zhang Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Nanjing University of Aeronautics and Astronautics Nanjing 210016China

Conversion-type anode materials are highly desirable for Na-ion batteries(NIBs)due to their high theoretical ***,the active materials undergo severe expansion and pulverization during the sodiation,resulting in inferior cycling ***,a self-supporting three-dimensional(3D)graphene sponge decorated with Fe_(2)O_(3)nanocubes(rGO@Fe_(2)O_(3))is ***,the 3D graphene sponge with resilience and high porosity benefits to accommodate the volume expansion of the Fe_(2)O_(3)nanocubes and facilitates the rapid electrons/ions transport,enabling spatial confinement to achieve outstanding ***,the free-standing rGO@Fe_(2)O_(3)can be directly used as an electrode without additional binders and conductive additives,which helps to obtain a higher energy *** on the total mass of the rGO@Fe_(2)O_(3)material,the rGO@Fe_(2)O_(3)anode presents a specific capacity of 859 mAh/g at 0.1 A/*** also delivers an impressive cycling performance(327 mAh/g after 2000 cycles at 1 A/g)and a superior rate capacity(162mAh/g at 20 A/g).The coin-type Na_(3)V_(2)(PO_(4))_(3)@C//rGO@Fe_(2)O_(3)NIB exhibits an energy density of 265.3Wh/*** unique 3D ionic/electronic conductive network may provide new strategies to design advanced conversion-type anode materials for high-performance NIBs.

关键词： Conversion-type anode Spatial confinement Fe_(2)O_(3) Graphene network Self-supporting Sodium-ion batteries

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HScore: A Target Attention-based Filter Pruning with Visualizing the Area of Feature Map

HScore: A Target Attention-based Filter Pruning with Visuali...

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International Neural Network Society Workshop on Deep Learning Innovations and Applications, INNS DLIA 2023

作者： Zhang, Chenrui Zhuang, Chenyi Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

Neural network pruning plays an important role in the deployment on resource-constrained devices by reducing the scale of the network and the computational complexity. Different from existing pruning methods that only consider the amount of information filters contain, we think the distribution of information is more important to the model accuracy. Then we use visualization of feature map to consider the impact of the attention area on the network decision. In order to directly relate the attention area with confidence score, we propose HScore to use interpolation and normalization to visualize the attention area of feature map and calculate the confidence score by putting only the attention area into the model. The principle behind is that if the feature map focuses on an area which can achieve a higher classification confidence, then the corresponding channel is important to keep the accuracy of model. The confidence score of attention area represents the importance of the channel to the model and filters with smaller confidences would be pruned. The experiment results prove that HScore can prune more redundant filters while maintaining better accuracy. Notably, our method can reduce 68.6% parameters and 73.0% FLOPs of ResNet-110 even with 0.14% top-1 accuracy increase on CIFAR-10. With ResNet-50, we achieve a 55% FLOPs reduction with only a loss of 1.03% in the top-1 accuracy on LSVRC-2012, which has advanced the state-of-the-art. © 2023 The Authors. Published by Elsevier B.V.

关键词： Industry 4.0

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Attitude Stabilization control for Unmanned Aerial Vehicle with Robotic Arm Based on Fixed-Time Observer Active Disturbance Rejection control 3rd

Attitude Stabilization Control for Unmanned Aerial Vehicle w...

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3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Mo, Fan Gu, Chaochen Wang, Kunkun Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9789819616930

To address the periodic disturbances introduced by the manipulator mounted on the drone, as well as the overall system parameter variations caused by the robotic arm carried by the Unmanned Aerial Vehicle (UAV), the fixed-time convergence observer (FTCO) is introduced to ADRC to enhance the dynamic characteristics, including overshoot and convergence speed. The Active Disturbance Rejection controller (ADRC) is employed as the fundamental controller for UAV systems while the FTCO is used to rapidly observe disturbances and compensate them to the controller, aiming to counteract interference. The UAV system is established to verify the effect of Fixed-Time Convergence Observer-Active Disturbance Rejection controller (FTCO-ADRC) when it is compared to conventional ADRC and PID controller. The simulation outcome reveals that the FTCO-ADRC perform better in convergence speed, overshoot and robustness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Disturbance rejection

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Weak signal detection method based on novel composite multistable stochastic resonance

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Chinese Physics B 2023年第5期32卷 178-187页

作者：焦尚彬高蕊薛琼婕史佳强 Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048China School of Electronic and Electrical Engineering Baoji University of Arts and SciencesBaoji 721016China

The weak signal detection method based on stochastic resonance is usually used to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer *** propose a novel composite multistable stochastic-resonance(NCMSR)model combining the Gaussian potential model and an improved bistable *** with the traditional multistable stochastic resonance method,all the parameters in the novel model have no symmetry,the output signal-to-noise ratio can be optimized and the output amplitude can be improved by adjusting the system *** model retains the advantages of continuity and constraint of the Gaussian potential model and the advantages of the improved bistable model without output saturation,the NCMSR model has a higher utilization of *** the output signal-to-noise ratio as the index,weak periodic signal is detected based on the NCMSR model in Gaussian noise andαnoise environment respectively,and the detection effect is *** application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer *** outstanding advantages of this method in weak signal detection are verified,which provides a theoretical basis for industrial practical applications.

关键词： weak signal detection composite multistable stochastic resonance bearing fault detection

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An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2621-2640页

作者： Jing Xin Kenan Du Jiale Feng Mao Shan Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an710048China Australian Centre for Field Robotics The University of SydneySydney2006Australia

This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D *** current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time *** address these issues,we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space ***,an indoor RGB-D image semantic segmentation network is proposed,which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud ***,Bayesian updating is used to conduct incremental semantic label fusion on the established spatial point cloud *** also employ dense conditional random fields(CRF)to optimize the 3D semantic map model,resulting in a high-precision spatial semantic map of indoor *** results show that the proposed semantic mapping system can process image sequences collected by RGB-D sensors in real-time and output accurate semantic segmentation results of indoor scene images and the current local spatial semantic ***,it constructs a globally consistent high-precision indoor scenes 3D semantic map.

关键词： 3D semantic map online reconstruction RGB-D images semantic segmentation indoor mobile robot

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Vibration-Based Fault Diagnosis for Railway Point Machines Using VMD and Multiscale Fluctuation-Based Dispersion Entropy

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Chinese Journal of Electronics 2024年第3期33卷 803-813页

作者： Yongkui SUN Yuan CAO Peng LI Guo XIE Tao WEN Shuai SU National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University School of Electronic and Information Engineering Beijing Jiaotong University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University

As one of the most important railway signaling equipment,railway point machines undertake the major task of ensuring train operation *** fault diagnosis for railway point machines becomes a hot *** the advantage of the anti-interference characteristics of vibration signals,this paper proposes an novel intelligent fault diagnosis method for railway point machines based on vibration signals.A feature extraction method combining variational mode decomposition(VMD) and multiscale fluctuation-based dispersion entropy is developed,which is verified a more effective tool for feature ***,a two-stage feature selection method based on Fisher discrimination and ReliefF is proposed,which is validated more powerful than single feature selection ***,support vector machine is utilized for fault *** comparisons show that the proposed method performs *** diagnosis accuracies of normal-reverse and reverse-normal switching processes reach 100% and 96.57% ***,it is a try to use new means for fault diagnosis on railway point machines,which can also provide references for similar fields.

关键词： Fault diagnosis Railway point machine Vibration signal Variational mode decomposition Two-stage feature selection

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