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第41届中国控制会议

作者： Zichen Dai Xuewen Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Aiming at the problem that the existing image semantic segmentation schemes based on convolutional neural network require a large number of training data sets and high training cost,this paper presents a novel scheme for image semantic segmentation based on extreme gradient boosting(XGBoost),a scalable tree boosting system and the combination of convolution feature extraction(CFE).The scheme consists of three ***,convolution operation is performed on a small amount of RGB pixel information of the image processed by Gaussian filtering to acquire more multi-dimensional image feature ***,some preprocessing techniques of image feature information,including feature normalization and image label pixel number uniformity are performed to match the ***,the preprocessed image feature information and corresponding labels are input into XGBoost to train and predict the data of the test *** simulation and practical tests,compared with other commonly used few data classification algorithms like k-Nearest-Neighbor(kNN) and Support-VectorMachine(SVM),this scheme can achieve high precision pixel-level image semantic segmentation under the condition of lower training cost.

关键词： Image Semantic Segmentation Convolutional Feature Extraction XGBoost Gaussian Filtering Low Training Cost

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Hybrid Group Consensus of Multi-agent systems with Time-delays and Additive Noises 41

Hybrid Group Consensus of Multi-agent Systems with Time-dela...

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第41届中国控制会议

作者： Chuanjian Li Xiaofeng Zong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The hybrid group consensus of multi-agent systems that consist of two groups in environments with time-delays and additive noises is studied in this *** hybrid group consensus implies that the agents in one group achieve strong consensus and the agents in another group achieve weak consensus.A new type of control protocol is proposed to achieve the following hybrid group consensus behavior:the agents in the first group and in the second group achieve strong consensus and weak consensus,*** sufficient conditions are obtained for the hybrid group consensus problem in both mean square and almost sure ***,a simulation example is given to illustrate the feasibility of the theoretical results.

关键词： multi-agent system hybrid group consensus time-delays additive noises

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Constructing a Raman and surface-enhanced Raman scattering spectral reference library for fine-particle analysis

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Journal of Environmental Sciences 2022年第8期34卷 1-13页

作者： Hui Chen Fengkui Duan Kebin He Jingjing Du Zhenli Sun Suhua Wang Key Laboratory of Resources and Environmental System Optimization of Ministry of Education College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and Control School of Environmental Science and EngineeringGuangdong University of Petrochemical TechnologyMaoming 525000 China

Fine particles associated with haze pollution threaten the health of over 400 million people in China. Owing to excellent non-destructive fingerprint recognition characteristics, Raman and surface-enhanced Raman scattering(SERS) are often used to analyze the composition of fine particles to determine their physical and chemical properties as well as reaction mechanisms. However, there is no comprehensive Raman spectral library of fine particles. Furthermore, various studies that used SERS for fine-particle composition analysis showed that the uniqueness of the SERS substrates and different excitation wavelengths can produce a different spectrum for the same fine-particle component. To overcome this limitation, we conducted SERS experiments with a portable Raman spectrometer using two common SERS substrates(silver(Ag) foil and gold nanoparticles(Au NPs)) and a 785 nm laser. Herein, we introduced three main particle component types(sulfate-nitrate-ammonium(SNA), organic material, and soot) with a total of 39 chemical substances. We scanned the solid Raman, liquid Raman, and SERS spectra of these substances and constructed a fine-particle reference library containing 105 spectra. Spectral results indicated that for soot and SNA, the differences in characteristic peaks mainly originated from the solid-liquid phase transition;Ag foil had little effect on this difference, while the Au NPs caused a significant red shift in the peak positions of polycyclic aromatic hydrocarbons. Moreover, with various characteristic peak positions in the three types of spectra, we could quickly and correctly distinguish substances. We hope that this spectral library will aid in the future identification of fine particles.

关键词： Raman Surface-enhanced Raman scattering(SERS) Spectral library Fine-particle

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SVDM: Single-View Diffusion Model for Pseudo-Stereo 3D Object Detection

arXiv

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arXiv 2023年

作者： Shi, Yuguang School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

One of the key problems in 3D object detection is to reduce the accuracy gap between methods based on LiDAR sensors and those based on monocular cameras. A recently proposed framework for monocular 3D detection based on Pseudo-Stereo has received considerable attention in the community. However, so far these two problems are discovered in existing practices, including (1) monocular depth estimation and Pseudo-Stereo detector must be trained separately, (2) Difficult to be compatible with different stereo detectors and (3) the overall calculation is large, which affects the reasoning speed. In this work, we propose an end-to-end, efficient pseudo-stereo 3D detection framework by introducing a Single-View Diffusion Model (SVDM) that uses a few iterations to gradually deliver right informative pixels to the left image. SVDM allows the entire pseudo-stereo 3D detection pipeline to be trained end-to-end and can benefit from the training of stereo detectors. Afterwards, we further explore the application of SVDM in depth-free stereo 3D detection, and the final framework is compatible with most stereo detectors. Among multiple benchmarks on the KITTI dataset, we achieve new state-of-the-art performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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DSFFNet: Dual-Side Feature Fusion Network for 3D Pose Transfer

arXiv

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arXiv 2023年

作者： Liu, Jue School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

To solve the problem of pose distortion in the forward propagation of pose features in existing methods, this paper proposes a Dual-Side Feature Fusion Network for pose transfer (DSFFNet). Firstly, a fixed-length pose code is extracted from the source mesh by a pose encoder and combined with the target vertices to form a mixed feature;Then, a Feature Fusion Adaptive Instance Normalization module (FFAdaIN) is designed, which can process both pose and identity features simultaneously, so that the pose features can be compensated in layer-by-layer forward propagation, thus solving the pose distortion problem;Finally, using the mesh decoder composed of this module, the pose are gradually transferred to the target mesh. Experimental results on SMPL, SMAL, FAUST and MultiGarment datasets show that DSFFNet successfully solves the pose distortion problem while maintaining a smaller network structure with stronger pose transfer capability and faster convergence speed, and can adapt to meshes with different numbers of vertices. Code is available at https://***/YikiDragon/DSFFNet Copyright © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Distributed Secondary control of DC Microgrids with Operation Loss Reduction

Distributed Secondary Control of DC Microgrids with Operatio...

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第43届中国控制会议

作者： Maoxiang Qiu Zhicheng Zhang Zhiqiang Zuo Yijing Wang Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In DC microgrids, current sharing and voltage regulation are two main objectives for real-time control, while the operation loss reduction is typically achieved by steady-state optimization. However, the ratio of current sharing is generally determined by the result of the centralized optimization in the classical hierarchical control framework of DC microgrids. Such an issue brings insufficient capability in respond to the changes of photovoltaic power and stored energy in the solar-powered energy systems. To handle this, this work proposes a distributed control scheme for single-bus DC microgrids. Under the proposed controller, the objectives of current sharing, bus voltage regulation and the total operation loss(converter loss and line loss) reduction can be guaranteed simultaneously. Moreover, the constraints on line currents and bus voltage are tackled as ***, simulations verify the performance of the proposed control scheme.

关键词： DC Microgrids Current Sharing Voltage Regulation Operation Loss Reduction Distributed Secondary control

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Simulation Research on Generalized Proportional Integral Observer Based Active Disturbance Rejection control for Coarse Pointing Assembly 8

Simulation Research on Generalized Proportional Integral Obs...

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8th International Conference on Electrical, Mechanical and Computer engineering, ICEMCE 2024

作者： Ma, Jijun Guo, Yulong Wang, YuNing Shi, Yongkang Beijing Research Institute of Telemetry Beijing100074 China 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 Department of Automation Shanghai200240 China Research Institute of Telemetry Beijing China

ISBN: (纸本)9798331506230

The coarse pointing assembly (CPA), as the outer loop of the laser terminal, its tracking stability is the basis for ensuring laser communication. This paper presents the model of the CPA. Aiming at the disturbance factors in the low-speed operation process of the CPA, an active disturbance rejection control (ADRC) method for the position loop of the CPA is designed based on the generalized proportional integral observer (GPIO) to achieve disturbance compensation control. Finally, simulations are carried out on the system model. The simulation results show that compared with the PID control strategy adopted, the proposed ADRC strategy based on GPIO of the CPA can effectively improve the tracking accuracy. © 2024 IEEE.

关键词： Disturbance rejection

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Building Temperature and Humidity Adaptive control for a Multi-Zone HVAC system Using Hybrid Modeling Method

Building Temperature and Humidity Adaptive Control for a Mul...

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Jiang, Yuliang Zhu, Shanying Xu, Qimin Yang, Bo Guan, Xinping Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China 200240 Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China 200240

ISBN: (纸本)9781728119489

In this paper, the heating, ventilation and air conditioning (HVAC) system as the contributor of building climate management is studied on multi-zone climate dynamics modelling and control for occupancy comfort. The first-principles model together with data-driven model as the hybrid model is proposed for comprehensive multi-zone hygro-thermal dynamics. The unmodeled climate dynamics such as unknown nonlinearity and uncertainty is modeled in a linear form based on the compact form dynamic linearization (CFDL) method. Then model free adaptive control (MFAC) scheme including controller design and parameter estimation is proposed to realize multi-zone climate control and occupancy comfort. The dynamic response performance of the hybrid model-based adaptive control and the first-principles model-based adaptive control has been tested in a multi-zone building with four different zones. The results show that the proposed hybrid model-based adaptive control scheme can achieve obvious performance improvement in minimizing steady-state error. © 2022 IEEE.

关键词： controllers

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Stabilization of Port-controlled Hamiltonian systems subject to exogenous disturbances via compensation control approach

Stabilization of Port-Controlled Hamiltonian systems subject...

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Data Driven control and Learning systems (DDCLS)

作者： Baozeng Fu Qingzhi Wang Yongchao Liu Shandong Key Laboratory of Industrial Control Technology School of Automation Qingdao University Qingdao China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

The stabilization of Port-controlled Hamiltonian (PCH) systems under exogenous disturbances by designing a compensation control approach is studied in the paper. Firstly, a baseline feedback control is proposed utilizing the damping injection method. To estimate disturbances, then a novel exogenous disturbance observer is constructed, based on which a feedforward compensation control is developed. Next, a composite control law is proposed based on the feedforward compensation and the feedback control. For the Hamiltonian system, an asymptotic stability analysis is followed finally. The feasibility of the compensation control strategy is revealed by a numerical simulation example.

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A Review of Spiking Neural Network Research in the Field of Bearing Fault Diagnosis 1

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Wang, Yusen Wang, Hongjun Xie, Long Ge, Henglin Zhou, Mingyang Chen, Tao Shi, Yuxing School of Mechanical and Electrical Engineering Beijing Information Science & Technology University Beijing100192 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education BISTU Beijing100192 China Beijing International Science Cooperation Base of High-End Equipment Intelligent Perception and Control BISTU Beijing100192 China

ISBN: (数字)9783031694837

ISBN: (纸本)9783031694820

In view of the bearing fault diagnosis problem, in order to better deal with the temporal data, extract nonlinear features, enhance the model robustness and adaptability, and realize efficient distributed computing, the spiking neural network is introduced to improve the accuracy and efficiency in the process of bearing fault diagnosis. In recent years, after a series of studies, the spiking neural network has developed in supervised learning, unsupervised learning, semi-supervised learning, and some other derived methods, such as reinforcement learning and transfer learning, for its applicable scenarios with different advantages. From the perspective of learning principle, method advantages and practical applications, we introduced several spiking neural network for bearing fault diagnosis, discussed the advantages, disadvantages and applicable scenarios of each learning method, discussed the application prospect of spiking neural network for bearing fault diagnosis, and proposed the spiking neural network for bearing fault diagnosis in future research, so as to provide reference for subsequent research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Self-supervised learning

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