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第34届中国控制与决策会议

作者： Tian Gao Qinglin Wang Yaping Dai School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

In order to solve the problem that the clustering number in Fuzzy C-Means(FCM) needs to be set manually in advance,a two-phase hybrid fuzzy clustering approach using membership fusion(TPHFC) is *** the first phase,conventional FCM is used for *** the second phase,the results obtained by pre-clustering are fused according to the relationship between the membership of samples to different clusters and the membership threshold.A density-based clustering validity measurement is established for this *** proposed method obtains better clustering effect with setting fewer *** on synthetic datasets conforming to Gaussian distribution and UCI datasets demonstrate the effectiveness of the proposed clustering *** clustering number and clustering centers can be obtained adaptively.

关键词： Fuzzy Clustering Fuzzy C-Means Two-Stage Clustering Adaptive Parameter Adjustment

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Study on Disturbance Propagation Characteristics of Power Grid and Evaluation of Temporal and Spatial Correlation Characteristics of Voltage Phase Trajectory 41

Study on Disturbance Propagation Characteristics of Power Gr...

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第41届中国控制会议

作者： Yibo Kong Changyou Feng Hongying Yang Liping Yan Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Xinjiang Electric Power Research Institute of State Grid Xinjiang Electric Power Co. Ltd. National Electric Power Dispatching and Control Center of State Grid Corporation of China China Electric Power Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the access of large-scale new energy and power electronic equipment,as well as the influence of various random uncertain factors,the analysis and control of dynamic security of large power grids become particularly difficult,so it is of great practical significance to study the disturbance propagation characteristics of complex power *** is an important parameter that affects the security of power systems,and the voltage phase trajectory contains abundant power grid ***,based on the measured data,this paper quantitatively describes the characteristics of dynamic space-time distribution of the voltage,and numerically reveals the different influences of disturbance on different nodes and the characteristics of disturbance ***,the geometric characteristics of the measured voltage phase trajectory are mined,the new trajectory distance is defined,the characteristic trajectory plane is constructed,and the spatio-temporal evolution law of voltage phase trajectory is *** the sequel,through the density-based DBSCAN clustering method,the characteristic tracks of voltage movement are clustered and analyzed,and the temporal and spatial correlation characteristics of voltage movement trends of each node are measured,and the law of disturbance propagation is ***,based on the measured data of IEEE 39-bus system,the simulation analysis is carried out,and the effectiveness of the presented algorithm is verified.

关键词： Disturbance propagation Voltage phase trajectory Temporal and spatial correlation characteristics Trajectory clustering

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Temperature control system of Thermoelectric Cooler Based on Improved ADRC

Temperature Control System of Thermoelectric Cooler Based on...

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第34届中国控制与决策会议

作者： Xiyuan Shan Tao Cai Zhicheng Zong Hongbo Mu School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Aiming at the problems containing complex working conditions,modeling difficulties and long-time delay of thermoelectric cooler temperature control system,an improved ADRC control method combining ADRC and Smith predictor is proposed in this *** deals with the disturbances and uncertain dynamics in the system,SP compensates the time delay to improve the control *** with the traditional PID controller,the proposed control method has faster response speed and stronger anti-disturbance ability,meanwhile,overcomes the dependence of Smith predictor on object parameters to a certain *** simulation and experimental verification,a good control effect is obtained,which provides a positive guidance of the related application of thermoelectric cooler.

关键词： Thermoelectric cooler(TEC) Active Disturbance Rejection control(ADRC) Smith Predictor(SP) Temperature control system

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Towards Pose Estimation for Large UAV in Close Range

Towards Pose Estimation for Large UAV in Close Range

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Ni Ou Junzheng Wang Shangfei Liu Jiehao Li State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665465373

This paper deals with the problem of 4D pose estimation for large unmanned aerial vehicles (UAVs) in close range. A sensor system consisting of one single point laser range-finder and two cameras is designed and a novel pose estimation method based on vision fusion and point cloud registration is proposed. Our approach works on one-shot mode and only requires 10 samples with real poses for template construction. Through V-rep simulation environment, we generate two 200-sample datasets of different difficulty for evaluation. Error quantiles, 5cm5deg and 10cml0deg are three evaluation metrics used in our ablation experiments. It is illustrated that our method outperforms in robustness and precision due to proposed dimension extension modification and fusion of vision sensors.

关键词： Point cloud compression Measurement Cloud computing Pose estimation Vision sensors Autonomous aerial vehicles Laser modes

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An Improved Active Disturbance Rejection control Method for Crane system

An Improved Active Disturbance Rejection Control Method for ...

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第34届中国控制与决策会议

作者： Yubo Sun Xiyuan Shan Zhicheng Zong School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

In order to improve the dynamic performance of the underdriven crane system,an improved linear active disturbance rejection controller(LADRC) based on the new error was *** improved LADRC takes the error value between the disturbance and its observed value multiplied by a coefficient as the basis for adjusting the linear extended state observer(LESO).The improved method has two ***,the new error can prevent the traditional LESO from choosing larger parameter adjustment disturbances,which will limit the performance of the ***,the pole can be configured by adjusting the coefficient to obtain better dynamic ***,the effectiveness of the proposed method is verified by simulation and *** proposed method can effectively restrain the swing of the payload and it is robust to system parameters perturbation as well.

关键词： Crane LADRC New Error Underdriven system

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GAT-Net:A Network using Grid Attention and Transformer for Dynamic Facial Expression Recognition

GAT-Net:A Network using Grid Attention and Transformer for D...

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第34届中国控制与决策会议

作者： Wenxin Dai Yaping Dai Kaoru Hirota Shuai Shao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Dynamic facial expression recognition(DFER) in the wild has received widespread attention *** are complex factors such as face occlusion and pose variation in the *** expression recognition has a subtle competition between capturing local features of a human face and obtaining a global feature *** paper proposes an end-to-end DFER network GAT-Net based on the grid attention module and Transformer,which improves the robustness and accuracy of DFER in the ***,GAT-Net is divided into two components:spatial feature extraction and temporal feature *** grid attention module of the spatial feature extraction component guides the network to pay attention to the local salient features of the face,which reduces the interference of field occlusion and non-frontal *** Transformer in the temporal feature processing component guides the network to learn the temporal relationship of high-level semantic features and the global representation of facial expression *** two components balance the subtle competition between local features and global feature representations of facial *** ablation experiment has proved the effectiveness of the grid attention module and *** demonstrate that our GAT-Net outperforms state-of-the-art methods on DFEW and AFEW benchmarks with accuracies of 67.53%,and 50.14% respectively.

关键词： Facial Expression Recognition Deep Learning Attention Mechanism Transformer

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Relative Localization for UAV-UGV Based on Correlation of Bearing and Distance

Relative Localization for UAV-UGV Based on Correlation of Be...

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IEEE International Conference on Mechatronics and Automation

作者： Jia Guo Kang Hu Jinting Liu State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

To ensure reliable localization for Unmanned Aerial Vehicles(UAVs) in the presence of uncertain speed of the Unmanned Ground Vehicle (UGV), this study examines the relative localization problem of UAV-UGV using distance and bearing measurements. A Correlation of Bearing and Distance-based Relative Localization (CBDRL) algorithm is proposed in this paper under this scenario. The estimation of altitude, distance, and angle are simplified into a representation of the relative positioning between the UAV and UGV. The relative height difference is measured using the barometer in the algorithm. To determine the relative distance, Time of Arrival (TOA) ranging and Ultra Wide Band (UWB) communication are utilized. The relative direction measurement is then determined using the correlations of bearing and distance. We integrate these observations with height, direction, and distance data in an Extended Kalman Filter(EKF) to provide accurate and reliable relative position estimates that allow the UAV to track the target. The simulation results indicate that the CBDRL method developed in this study is superior to previous relative localization algorithms that rely on multi-sensor fusion, and can significantly enhance the accuracy of UAV positioning provided that range and angle measurements are precise enough.

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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Chinese Journal of Electronics 2023年第3期19卷 451-456页

作者： Bo Li Wenju Liu Lihua Dou School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词： Training Image segmentation Analytical models Parameter estimation Estimation Probability density function Speech processing

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Analysis of LoRa for Electronic Shelf Labels Based on Distributed Machine Learning

Analysis of LoRa for Electronic Shelf Labels Based on Distri...

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Chinese control Conference (CCC)

作者： Malak Abid Ali Khan Hongbin Ma Ying Jin Jingxiang Ma Zia Ur Rehman Mizanur Rahman School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

Deforestation is the primary source of global warming; traditional shelf labels use paper to display the price of the products, and human forces play a pivotal role in updating the tags where the pandemic has strictly limited its power. Various technologies provide connectivity and a fast-updating system to eliminate the paper-based approach. LoRa is one of the contenders to design the system for electronic shelf labels (ESLs). In this paper, LoRa has been used to minify data losses and guarantee the successful decoding of the carrier signals. The data parallelism at the network server (NS) is used to distribute the data packets among the gateways (GWs) for concurrent transmissions to the end devices (EDs). The EDs are placed in different ranges using machine clustering to avoid intra-SF interference and collision. The data rate (DR) and spreading factors (SFs) have been proposed to improve the performance of pure and slotted ALOHA for the properly allocated tags. The orthogonality principles follow industrial, scientific, and medical regulations (ISM) to avoid data traffic congestion. GWs under different duty cycles (DC) and bandwidth (BW) are examined to minify the network saturation and reduce the energy harvesting of the tags.

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Open-/Closed-loop Active Learning for Data-driven Predictive control

arXiv

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arXiv 2024年

作者： Feng, Shilun Shi, Dawei Shi, Yang Zheng, Kaikai The State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing100081 China The Department of Mechanical Engineering Faculty of Engineering University of Victoria VictoriaBCV8N 3P6 Canada

An important question in data-driven control is how to obtain an informative dataset. In this work, we consider the problem of effective data acquisition of an unknown linear system with bounded disturbance for both open-loop and closed-loop stages. The learning objective is to minimize the volume of the set of admissible systems. First, a performance measure based on historical data and the input sequence is introduced to characterize the upper bound of the volume of the set of admissible systems. On the basis of this performance measure, an open-loop active learning strategy is proposed to minimize the volume by actively designing inputs during the open-loop stage. For the closed-loop stage, an closed-loop active learning strategy is designed to select and learn from informative closed-loop data. The efficiency of the proposed closed-loop active learning strategy is proved by showing that the unselected data cannot benefit the learning performance. Furthermore, an adaptive predictive controller is designed in accordance with the proposed data acquisition approach. The recursive feasibility and the stability of the controller are proved by analyzing the effect of the closed-loop active learning strategy. Finally, numerical examples and comparisons illustrate the effectiveness of the proposed data acquisition strategy. Copyright © 2024, The Authors. All rights reserved.

关键词： Active learning

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