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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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Relay Selection and Power control for Mobile Underwater Acoustic Communication Networks: A Dual-Thread Reinforcement Learning Approach

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年第2期9卷 1-1页

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Key Lab of Industrial Computer Control Engineering of Hebei Province China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China

This paper deals with a cooperation communication problem (relay selection and power control) for mobile underwater acoustic communication networks. To achieve satisfactory transmission capacity, we propose a reinforcement-learning-based cooperation communication scheme to efficiently resist the highly dynamic communication links and strongly unknown time-varying channel states caused by the mobility of Autonomous Underwater Vehicles (AUVs). Firstly, a particular Markov decision process is developed to model the dynamic relay selection process of mobile AUV in the unknown scenario. In the developed model, an experimental statistical-based partition mechanism is proposed to cope with the greatly increasing dimension of the state space caused by the mobility of AUV, reducing the search optimization difficulty. Secondly, a dual-thread reinforcement learning structure with actual and virtual learning threads is proposed to efficiently track the superior relay action. In the actual learning thread, the proposed improved probability greedy policy enables the AUV to strengthen the exploration for the reward information of potential superior relays on the current state. Meanwhile, in the virtual learning thread, the proposed upper-confidence-bound-index-based uncertainty estimation method can estimate the action-reward level of historical states. Consequently, the combination of actual and virtual learning threads can efficiently obtain satisfactory Q value information, thereby making superior relay decision-making in a short time. Thirdly, a power control mechanism is proposed to reuse the current observed action-reward information and transform the multiple unknown parameter nonlinear joint power optimization problem into a convex optimization problem, thereby enhancing network transmission capacity. Finally, simulation results verify the effectiveness of the proposed scheme. IEEE

关键词： Convex optimization

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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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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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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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Few-shot object detection via class encoding and multi-target decoding

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IET Cyber-systems and Robotics 2023年第2期5卷 1-14页

作者： Xueqiang Guo Hanqing Yang Mohan Wei Xiaotong Ye Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province HangzhouChina

The task of few‐shot object detection is to classify and locate objects through a few annotated *** many studies have tried to solve this problem,the results are still not *** studies have found that the class margin significantly impacts the classification and representation of the targets to be *** methods use the loss function to balance the class margin,but the results show that the loss‐based methods only have a tiny improvement on the few‐shot object detection *** this study,the authors propose a class encoding method based on the transformer to balance the class margin,which can make the model pay more attention to the essential information of the features,thus increasing the recognition ability of the ***,the authors propose a multi‐target decoding method to aggregate RoI vectors generated from multi‐target images with multiple support vectors,which can significantly improve the detection ability of the detector for multi‐target *** on Pascal visual object classes(VOC)and Microsoft Common Objects in Context datasets show that our proposed Few‐Shot Object Detection via Class Encoding and Multi‐Target Decoding significantly improves upon baseline detectors(average accuracy improvement is up to 10.8%on VOC and 2.1%on COCO),achieving competitive *** general,we propose a new way to regulate the class margin between support set vectors and a way of feature aggregation for images containing multiple objects and achieve remarkable *** method is implemented on mmfewshot,and the code will be available later.

关键词： Class Margin Few-Shot Object Detection Multi-Target Transformer

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Geometric attitude tracking control of quadrotor UAVs with adaptive extended state observers

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ISA Transactions 2025年 160卷 289-297页

作者： Wang, Liping Chen, Jiapeng Huang, Yuyuan Zhu, Yongbin Pei, Hailong Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong School of Automation Science and Engineering South China University of Technology Guangzhou510640 China

This paper studies a geometric attitude tracking control problem of quadrotor unmanned aerial vehicles (UAVs) with adaptive extended state observers (AESOs). Through coordinate transformation, the error dynamic of AESO can be transformed into a canonical form which is easier to analyze by linear time-varying theory. In the presence of unknown disturbances and system uncertainties, the estimated error and stability of AESO can be analyzed. Simultaneously, a geometric tracking controller is developed on SO(3) with AESOs which guarantees that the error exponentially converges to a bounded set related to the estimated error. Some examples and a flight test are given to verify the availability of the control scheme. © 2025

关键词： Unmanned aerial vehicles (UAV)

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Fall-LSTM: A Fall Detection Network Based on Spatio-Temporal Location Module 42

Fall-LSTM: A Fall Detection Network Based on Spatio-Temporal...

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42nd Chinese control Conference, CCC 2023

作者： Xu, Dapeng Lu, Xiaobo Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9789887581543

Fall events have unique dynamic features, which are not fully utilized by existing fall detection methods. Based on video understanding, we propose Fall-LSTM to learn such features pertinently without additional inputs. Fall-LSTM is composed of CNN-LSTM framework and two excitation modules i.e., Spatial Attention Module (SAM) and Temporal Location Module (TLM). SAM provides spatial constraints on motion for feature layers through foreground extraction and spatial pooling. TLM emphasizes frames with high probability of fall events to LSTM by inferring the rate and trend of motion in clips. Experimental results show that our proposed modules significantly improve the performance of LSTM model, outperforming the state-of-the-art methods on two public Fall Detection Datasets i.e., Le2i and UR. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Location

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Implicit Representation for Interacting Hands Reconstruction from Monocular Color Images 12th

Implicit Representation for Interacting Hands Reconstructio...

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12th International Conference on Image and Graphics, ICIG 2023

作者： Zuo, Binghui Zhao, Zimeng Xie, Wei Wang, Yangang School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9783031463044

Reconstructing interacting hands from monocular color images plays an important role in promoting the understanding of human behavior and the application of existing AR/VR technology. With the emergence of interacting hands datasets, numerous data-driven methods attempt to regress the MANO parameters of the left and right hand from the network. This formulation not only limits the handedness and the number of hands in the image but also introduces the deficiencies of the MANO into the interacting-hand reconstruction task. To address this obstacle, we present a novel framework for representing the surface of interacting hands with implicit functions. Our key idea is to construct an implicit neural occupancy network, which implicitly reconstructs interacting hands with image features as query strategies and conditions. The proposed query strategies only require one sample to obtain enough points on the surface. Our unified framework efficiently completes the task of reconstructing hands with the unlimited number, handedness, and interaction compactness from monocular color images. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Color

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