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检索条件"任意字段=9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020"

共 506 条记录，以下是261-270 订阅

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A Long Short Term Memory Network Based on Surface Electromyography for Continuous Estimation of Elbow Joint Angle 9

A Long Short Term Memory Network Based on Surface Electromyo...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Chai, Yuanyuan Liu, Keping Sun, Zhongbo Wang, Gang Shi, Tian Changchun Univ Technol Dept Control Engn Jilin 130000 Jilin Peoples R China Jilin Univ Minist Educ Key Lab Bion Engn Changchun 130025 Peoples R China Jilin Univ Dept Control Engn Jilin 130000 Jilin Peoples R China

ISBN: (纸本)9781728159225

A simple long short term memory (LSTM) network is built to estimate the model which is described the relationship between the elbow joint angle and the surface electromyography (sEMG) signals in this paper. the sEMG time series of biceps and triceps are the inputs of the model, and the elbow joint angle is the output of the model. the sEMG signals while the user is performing flexion and extension movements are collected by Biopac. Elbow joint angle is measured by angle sensor. the results show that for simple flexion and extension movements, the model is able to eatimate the movement intention of the elbow.

关键词： sEMG Rehabilitation Elbow joint LSTM network

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Approach of driving system for lower limb rehabilitation training robot based on strong tracking filtering 9

Approach of driving system for lower limb rehabilitation tra...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Jiang, Dawei Shi, Guoquan Zhang, Bing Tian, Yuan Changchun Univ Sci & Technol Sch Mechatron Engn Changchun 130022 Peoples R China Changchun Univ Technol Sch Mechatron Engn Changchun 130012 Peoples R China Jilin Univ Dept State Key Lab Automot Simulat & Control Changchun 130022 Peoples R China Changchun Vocat Inst Technol Changchun 130000 Peoples R China

ISBN: (纸本)9781728159225

To solve the problem of lowering the control accuracy of the robotic servo system of lower limb rehabilitation training due to inaccurate models and load disturbances, this paper takes the one degree of freedom(DOF) lower limb rehabilitation training robot servo system as the research object, and establish a mathematical model of the servo system of the lower limb rehabilitation training robot including several subsystems such as the execution system, feed system and drive system. A control algorithm for driving system of lower limb rehabilitation training robot based on strong tracking filter(STF) is adopted. through simulation analysis, the stability of STF algorithm is compared, which shows that the proposed algorithm has the advantages of fast tracking speed, noise suppression and high accuracy. the experimental results further show that the established servo system model of the lower limb rehabilitation training robot matches the actual nonlinear system model. the STF algorithm has better tracking ability, high control accuracy and smoother operation. the research results provide a reference for the research on the servo system of lower limb rehabilitation equipment.

关键词： Lower limb rehabilitation training robot STF Stability

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Visual Tracking Algorithm with Multi-Gaussian Correlation Filters Based on Confidence Feedback Adjustment 9

Visual Tracking Algorithm with Multi-Gaussian Correlation Fi...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Wang, Li Wang, Cong North China Univ Technol Beijing Key Lab Urban Intelligent Control Technol Beijing 100144 Peoples R China

ISBN: (纸本)9781728159225

In order to improve the speed and robustness of hierarchical convolutional features for visual tracking algorithm, the multi-Gaussian correlation filters for visual tracking based on confidence feedback adjustment is proposed. Our method extracts features for tracking from two appropriate convolutional layers, and proposes the average feature energy ratio to reduce the feature dimensions, along with the sparser model update scheme avoiding over-fitting to improve the tracking speed. then different Gaussian labeled functions are input to construct the multi-Gaussian correlation filters and adaptively fuse all the predicted results of multiple filters, expecting for higher accuracy. Finally, it introduces the average peak-to-correlation energy and the maximum response ratio to evaluate the tracking results, and adjust the learning rate and search area to further improve the robustness of the tracker. this algorithm is tested on the OTB100 benchmark datasets. the results show that it has an average distance precision of 88.6%, an improvement of 4.9 percentage points over the original hierarchical convolutional features for visual tracking approach, as well an average speed of 29.2 frames per second, 3 times that of the original method. the proposed multi-Gaussian correlation filters can effectively improve the speed and accuracy and has good robustness whatever challenges like occlusion, deformation and similar background interferences subjecting to.

关键词： Visual tracking convolutional features correlation filter confidence feedback Gaussian distribution

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An Abrasion Detection Method for Elevator Traction Wire Rope based on Template Matching 9

An Abrasion Detection Method for Elevator Traction Wire Rope...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Li, Zehua Chai, Zheng Zhao, Chunhui Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China

Elevators are gradually becoming an indispensable part of people9;s daily life. At the same time, various safety problems caused by elevators are also seriously threatening people9;s life and property security. ... 详细信息

ISBN: (纸本)9781728159225

Elevators are gradually becoming an indispensable part of people's daily life. At the same time, various safety problems caused by elevators are also seriously threatening people's life and property security. Elevator traction wire rope damage is a common type of potential safety hazard. At present, the defect detection method for elevator traction wire rope damage generally has high complexity and labor cost. this paper presents a method to detect the abrasion of elevator traction wire rope by taking full use of the texture feature of the traction wire rope images. First, the interference factors in the process of image acquisition are removed by the pretreatment methods of graying and denoising. then, the abrasion area of the traction wire rope is determined according to the similarity measurement criteria by combining edge detection and template matching. Finally, the image is finely segmented and the abrasion rates of different areas are calculated. this method is convenient and intuitive to detect the changes of elevator wire rope abrasion. On one hand, the complexity of the detection and the loss of the human labor can be reduced;on the other hand, valuable reference can be provided for elevator maintenance. Experiment on actual wire rope images validate the effectiveness of the proposed method.

关键词： Elevator wire rope abrasion detection template matching

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Sensor Correlation Network Based Anomaly Detection for thermal systems on Ships 9

Sensor Correlation Network Based Anomaly Detection for Therm...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Zheng, Wei Zhou, Hongkuan Qiu, Zhiqiang Ke, Zhiwu Tao, Mo Chen, Zhaoxu Sci & Technol Thermal Energy & Power Lab Wuhan 430064 Peoples R China China State Shipbldg Corp Ltd Wuhan Ship Design & Res Inst 2 Wuhan 430064 Peoples R China

ISBN: (纸本)9781728159225

In this paper, we propose an approach to handle the anomaly detection for the thermal system on ships by the sensor associated network method. A large number of sensors are placed in different positions of the thermal system. these sensors form a topological network which can represent the operation state of the thermal system. there are both linear correlation and nonlinear correlation between the operating parameters reflected by these sensors. the MAS index from MINE is utilized to represent the correlation information between sensors when the thermal system is in dynamic operation condition. Based on the MAS correlation coefficient, the sensor correlation network is constructed to represent the dynamic operation process of thermal system. Using DBSCAN clustering algorithm, the large topological network is divided into different subnetworks. When the system is running dynamically, the Manhattan distance between the sub networks can reflect the running state of the system. Based on the distance of sub networks, the similarity of sensor networks with continuous changes is calculated and the similarity correlation sequence is formed. through the matching between the similarity correlation sequence and the historical experience sequence, we can judge whether the system dynamic condition is abnormal. By the simulation experiment data, we verify the effectiveness of the proposed method.

关键词： Anomaly Detection Correlation Network Correlation Coefficient thermal System

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Intelligent Sweeper Path Tracking control Based on Optimal Iterative learning 9

Intelligent Sweeper Path Tracking Control Based on Optimal I...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Yao, Wen-long Pang, Zhen Chi, Ronghu Shao, Wei Yang, Dejing Qingdao Univ Sci & Technol Sch Automat & Elect Engn Qingdao 266100 Peoples R China Beijing Inst Technol Sch Aerosp Engn Beijing 100000 Peoples R China Shandong JinKaiFeng Machinery Technol Co Ltd Yishui 276400 Peoples R China

ISBN: (纸本)9781728159225

this paper studies the path tracking control system of intelligent sweeper. According to the fact that the intelligent sweeper mainly carries out the cleaning and sprinkling work in a fixed section periodically and has strong repeatability, this paper studies the path tracking control problem of the intelligent sweeper based on the optimal iterative learning control method. Firstly, the traditional intelligent sweeper path tracking system is transformed into the pre-sighting deviation angle tracking system. And the dynamic linearization data model is obtained by using the improved iterative dynamic linearization method. Secondly, an iterative expansion observer is added in this paper to deal with uncertain disturbances such as turbulence and measurement error in the path tracking control system of intelligent sweeper. It compensates for the unknown disturbance. Finally, the parameter iteration update rate and the optimal learning control rate of the intelligent sweeper control system are proposed. the optimal iterative control method with an iterative expansion observer can effectively utilize the repeated information in the path tracking process of the intelligent sweeper and effectively estimate the unknown disturbance. And it only utilizes the input and output information of the system, avoiding the difficult problem of modeling. Simulation results show the effectiveness of the proposed method.

关键词： Path Tracking Intelligent Sweeper Iterative learning control Anti-interference Iterative Extended State Observer

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Cluster-based Relevance Analysis Between Construction Mode and BCR for Optimizing the DAS 9

Cluster-based Relevance Analysis Between Construction Mode a...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Zhu, Jiran Leng, Hua Tang, Haiguo Fan, Min Liu, Yaling Yang, Qing Tongji Univ Coll Elect & Informat Engn Jiading Shanghai 201804 Peoples R China State Grid Corp Hunan Elect Power Corp Res Inst Changsha 410007 Hunan Peoples R China Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Chongqing Univ Sch Automat Chongqing 400044 Peoples R China Chongqing Univ Minist Educ Key Lab Complex Syst Safety & Control Chongqing Peoples R China

ISBN: (纸本)9781728159225

Distribution automation system (DAS) is the key of intelligent power distribution. With the construction and operation of DAS, studying on the optimization of DAS has received much attention from both academia and industry. this study proposed cluster-based relevance analysis between construction mode and benefit-cost ratio (BCR) for optimizing the DAS. this method clusters the DASs of different cities, and analyzes the clustering results. then, the method analyzes BCR of DAS in different categories and uses comparative analysis, grey relational analysis (GRA) and sensitivity analysis to analyze the relevance between the construction mode and BCR of typical city's DAS and determine the major factors affecting the BCR comprehensively. Finally, it integrates all analysis results to make optimization suggestions for DAS. the case study shows that the method is effective and feasible, which can provide direction and reference basis for the optimization of DAS in cities of different scale.

关键词： distribution automation system clustering relevance analysis benefit-cost ratio optimization

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Experiment Verification of High Order Differential Feedback control for Quadrotor UAV 9

Experiment Verification of High Order Differential Feedback ...

引用

9th ieee data driven control and learning systems conference, ddcls 2020

作者： Ma, Shengli Qi, Guoyuan Guo, Xitong Li, Xia Tiangong University School of Electrical Engineering and Automation Tianjin300387 China Tiangong University School of Mechanical Engineering Tianjin300387 China

ISBN: (纸本)9781728159225

An outer-loop model-free controller called high order differential feedback control (HODFC) that can compute the velocity of position and yaw is applied to accomplish the flight tasks based on indoor optical positioning system. A high precision observer called high order differentiator (HOD) is introduced to observe the differential states of the system output and given input. A filtering signal of control output is incorporated in the control law to estimate the information related to system model. the remarkable features of the HODFC includes model-free performance, pole assignment based on theory, the disturbance suppression. Comparison results of the HODFC and the proportional-integral-derivative (PID) trajectory tracking experiment in height, yaw and x-y plane, and the disturbance experiments are presented to illustrate the superior performance of the HODFC method over the PID method. © 2020 ieee.

关键词： Unmanned aerial vehicles (UAV)

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A data-driven Operating Performance Assessment Method based on Weighted Multi-Sphere Support Vector data Description 9

A Data-Driven Operating Performance Assessment Method based ...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Zhang, Chuanfang Peng, Kaixiang Dong, Jie Univ Sci & Technol Beijing Sch Automat & Elect Engn Key Lab Knowledge Automat Ind Proc Minist Educ Beijing 100083 Peoples R China Univ Sci & Technol Beijing Natl Engn Res Ctr Adv Rolling Technol Beijing 100083 Peoples R China

ISBN: (纸本)9781728159225

In modern hot rolling process, operating performance assessment is of great practical significance for guiding the production adjustment for operators. From the perspective of classification, operating performance assessment is a multi-class classification problem. Since support vector data description (SVDD) is a one-class classifier, conventional methods usually construct an independent SVDD model for each class, which ignores the correlation among different classes. the hyperspheres of different classes may not be isolated but overlapped. If a test sample exists in the overlapping region, how to determine which class it belongs to is a knotty problem. Moreover, conventional methods treat all samples equally, but in practice, the sample number of different classes can be imbalanced, which will affect the classification performance of SVDD. In this study, an operating performance assessment method based on weighted multi-sphere SVDD (WMSVDD) is proposed for solving the aforementioned issues. WMSVDD considers the interactions among different classes in a unified way, optimizes the hyperspheres of different classes globally, and introduces a weight coefficient to the model for eliminating the affects of uneven class sizes. Simulation results on a real hot rolling process illustrate the effectiveness of the proposed method comparing to the traditional multi-class SVDD.

关键词： Hot rolling process data-driven operating performance assessment support vector data description multi-class classification

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Satellite Micro Anomaly Detection Based on Telemetry data 9

Satellite Micro Anomaly Detection Based on Telemetry Data

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9th ieee data driven control and learning systems conference, ddcls 2020

作者： Sun, Chao Chen, Shaojun Mingzhang, M. Du, Ying Ruan, Chuanmin 63758 Unit of Pla Xiamen361023 China Guangdong University of Petrochemical Technology Guangzhou525000 China

ISBN: (纸本)9781728159225

the military requirements of space security defense and space fast response are increasingly urgent. Accurate and effective micro anomaly detection of on-orbit satellites is an important technical way of satellites life cycle health management. Under this military background, the micro anomaly detection of the key components of the satellite is proposed and carried out. In order to solve the problems of low diagnostic accuracy of the traditional Voherra series model in satellite telemetry signal micro anomaly detection, o-Voherra series anomaly detection model for the feature extraction of telemetry data based on the optimized sequence model is proposed. Firstly, the feature of satellite telemetry data is extracted by using the constructed optimized sequence model. Secondly, phase space reconstruction of telemetry data after preprocessing and feature extraction. Finally, the telemetry data micro anomaly detection are realized by the proposed o-Voherra series model. through the remote sensing data experiment of the key components of the satellite after desensitization, the proposed model can accurately realize the micro anomaly detection of the key components of the satellite. © 2020 ieee.

关键词： Anomaly detection

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