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2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)最新文献

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A Data-driven System-level Health State Prognostics Method for Large-scale Spacecraft Systems 大型航天器系统数据驱动的系统级健康状态预测方法
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8515929
Runfeng Chen, Hong Yang
{"title":"A Data-driven System-level Health State Prognostics Method for Large-scale Spacecraft Systems","authors":"Runfeng Chen, Hong Yang","doi":"10.1109/DDCLS.2018.8515929","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515929","url":null,"abstract":"Large-scale spacecraft, such as space station, highlights the systems’ reliability and safety. Using prognostics to predict the trend of the system health state evolution can help find out the potential dangers and prevent the unexpected failure from happening. With the adoption of data-driven ideology, a system-level health state prognostics method is proposed to predict the trend information. First, the characteristics of the large-scale spacecraft and the system-level health definition are analyzed. Then the details of the solution method are described. The novelty of this method is to use the network science knowledge to extract the system-level features. The adopted predicting method is briefly introduced. Finally, a real case study with on-orbit telemetry data is presented, and relevant conclusions are drawn for reference.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"44 1","pages":"565-568"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86773457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Test and Evaluation Framework for Unmanned Surface Vehicle 无人水面航行器测试与评估框架
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8516078
Weiwei Kong, Weiqiang Feng, Yi Zheng, Tianjiang Hu
{"title":"A Test and Evaluation Framework for Unmanned Surface Vehicle","authors":"Weiwei Kong, Weiqiang Feng, Yi Zheng, Tianjiang Hu","doi":"10.1109/DDCLS.2018.8516078","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8516078","url":null,"abstract":"Unmanned Surface Vehicle(USV) in today’s military and commercial application is growing exponentially. Benefiting from the autonomous capability, this unmanned platform can execute various tasks without human directly control. So evaluation of their autonomy and other capabilities are critical to realize the autonomous operation ability of unmanned systems. We present the quantitative indices, typical scenes and a practical framework to test and evaluate the performance of an USV. Then a test and evaluation (T&E) framework was established for data collection. By setting up a simulation environment, it can be seen that the proposed framework gives quantified results with different testing assignments.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"42 1","pages":"1134-1139"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86985074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
On-line Active Fault Detection Based on Set-membership Ellipsoid and Moving Window 基于集隶属椭球和移动窗口的在线主动故障检测
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8515992
Junde Wang, Jing Wang, Jinglin Zhou
{"title":"On-line Active Fault Detection Based on Set-membership Ellipsoid and Moving Window","authors":"Junde Wang, Jing Wang, Jinglin Zhou","doi":"10.1109/DDCLS.2018.8515992","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515992","url":null,"abstract":"On-line active fault detection (AFD) and its optimization problems are proposed based on the set-membership ellipsoid technique in order to solve the problem of on-line fault detection. The design of auxiliary input signal should satisfy two conditions: the signal amplitude is small enough without obvious impact on the system, and it simultaneously separates the system output in the normal and fault operation. Here we describe the output set as an ellipsoid under the framework of set-membership. The system model of moving window is established based on the parity space, and the equivalent optimization design of auxiliary input signal is solved based on this model. The proposed method can significantly reduce the complexity of the optimization calculation and conveniently obtain the auxiliary input signal on-line. The system fault is detected more intuitively by comparing the degree of separation between the output ellipsoid of the actual system and that of the identification normal (or fault) model. The simulation results on a general example verify the effectiveness of the proposed method.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"44 1","pages":"420-425"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87062699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Finite-level Quantized Iterative Learning Control by Encoding-Decoding Mechanisms 基于编解码机制的有限级量化迭代学习控制
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8515988
Chao Zhang, D. Shen
{"title":"Finite-level Quantized Iterative Learning Control by Encoding-Decoding Mechanisms","authors":"Chao Zhang, D. Shen","doi":"10.1109/DDCLS.2018.8515988","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515988","url":null,"abstract":"This paper studies the zero-error tacking problem of finite-level quantized iterative learning control using an encoding-decoding method, where both measurement and actuator side quantization and transmission are considered. In particular, the system output is encoded, quantized, transmitted and decoded in sequence for input updating of the next iteration. Then the generated input is transmitted through networks following the same procedure as the output transmission for plant input updating. The zero-error convergence of the proposed scheme is strictly proved and a numerical simulation is provided to demonstrate the effectiveness of the proposed scheme.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"97 1","pages":"289-294"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86513919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Networked Iterative Learning Control for Nonlinear Switched Discrete-time Systems with Random Measurement Packet Losses 具有随机测量丢包的非线性开关离散系统的网络迭代学习控制
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8516018
Ang-Ji Lin, Shu-Ting Sun, Xiao-dong Li
{"title":"Networked Iterative Learning Control for Nonlinear Switched Discrete-time Systems with Random Measurement Packet Losses","authors":"Ang-Ji Lin, Shu-Ting Sun, Xiao-dong Li","doi":"10.1109/DDCLS.2018.8516018","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8516018","url":null,"abstract":"For nonlinear switched discrete-time systems with random measurement packet losses modeled by a Bernoulli-type stochastic sequence, this paper presents a P-type networked Iterative Learning Control (ILC) algorithm with an attenuating forgetting factor. In this ILC scheme, the random measurement packet losses are replaced by the desired output data. Under a given switching rule, the convergence of ILC tracking error in mathematical expectation in each of subsystems is proved by mathematical induction, and the convergent condition of the proposed networked P-type ILC algorithm is given. An illustrative simulation is used to verify the effectiveness of the proposed ILC algorithm.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"16 1","pages":"748-756"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87694563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A KNN-SVR Data Mending Method for Insufficient Data of Magnetic Flux Leakage Detection 漏磁检测数据不足的KNN-SVR数据修补方法
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8516108
Xinbo Zhang, Jian Feng, Zhiqiang Yao, Jinhai Liu, Huaguang Zhang
{"title":"A KNN-SVR Data Mending Method for Insufficient Data of Magnetic Flux Leakage Detection","authors":"Xinbo Zhang, Jian Feng, Zhiqiang Yao, Jinhai Liu, Huaguang Zhang","doi":"10.1109/DDCLS.2018.8516108","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8516108","url":null,"abstract":"In magnetic flux leakage (MFL) detection, transient fault appears unavoidably on individual sensor when we collect magnetic flux leakage signals, which makes MFL data insufficient. Data mending for insufficient data concerns the accuracy of the defects inversion. A precise data mending method based on K Nearest Neighbor-Support Vector Regression (KNN-SVR) is introduced, which effectively reduces the training cost of SVR and greatly improves the accuracy of the algorithm. The method is tested by experiment data obtained. The results demonstrate that the proposed method can improve the accuracy rate of data mending of insufficient data with an acceptable time cost.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"5 1","pages":"442-445"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82470660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
The Position Tracking Control System of Induction Motors Based on Stator-Flux-Oriented Vector Control 基于定子磁链定向矢量控制的感应电机位置跟踪控制系统
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8516000
K. Zhuang
{"title":"The Position Tracking Control System of Induction Motors Based on Stator-Flux-Oriented Vector Control","authors":"K. Zhuang","doi":"10.1109/DDCLS.2018.8516000","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8516000","url":null,"abstract":"Asynchronous motor is a common motor in electric vehicle. In this paper, the position tracking control system based on stator flux oriented vector control (SFOVC) combining advantages of rotor flux oriented vector control and direct torque control is studied. A continuous closed-loop controller is adopted to correct the calculated position angle of stator flux and the torque ripple is small. This method is less affected by the parametric variation of rotor, with accurate stator flux observation and high position tracking accuracy. Simulation results demonstrate the effectiveness of this new control strategy.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"36 1","pages":"708-713"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84224562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Generalized CCA with Applications for Fault Detection and Estimation 广义CCA及其在故障检测和估计中的应用
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8515936
Zhi-wen Chen, S. Ding, Kai Zhang, Chunhua Yang, Tao Peng
{"title":"Generalized CCA with Applications for Fault Detection and Estimation","authors":"Zhi-wen Chen, S. Ding, Kai Zhang, Chunhua Yang, Tao Peng","doi":"10.1109/DDCLS.2018.8515936","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515936","url":null,"abstract":"Canonical correlation analysis (CCA) is a well-established multivariate analysis method for finding the relationship between two data sets, which has been explored for fault detection recently. In this paper, we revisit the generalized canonical correlation analysis (CCA) form and discuss its applications for fault detection and estimation. The motivation of using CCA for fault detection is to reduce process uncertainty by taking the correlation coefficients into account. Then, the fault detectability in terms of fault detection rate is increased. Finally, the generalized CCA-based fault detection method is validated on the benchmark, which is a simulation of high-speed trains traction drive control system. The achieved results show that the proposed method is able to successfully detect the faults.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"31 1","pages":"545-550"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90244017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Reliable Control of Nonlinear System with Input Saturation by Adaptive Iterative Learning Control 输入饱和非线性系统的自适应迭代学习可靠控制
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8515942
Ruikun Zhang, R. Chi
{"title":"Reliable Control of Nonlinear System with Input Saturation by Adaptive Iterative Learning Control","authors":"Ruikun Zhang, R. Chi","doi":"10.1109/DDCLS.2018.8515942","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515942","url":null,"abstract":"In this paper, reliable control strategy is studied for nonlinear system with input saturation by adaptive iterative learning control. The system dynamic function is described by a class of nonlinearly parameterized functions with input saturation and actuator faults. In order to address nonlinearity of system, input saturation and the actuator fault term, we design the adaptive iterative learning reliable controller (AILRC), which is a feedback P-type ILC controller. Based on the constructed composite energy function (CEF) and some necessary assumptions, the convergence analysis is given, which shows that the system tracking error converges to zero when the iteration number tends to infinity. Finally, simulation is given to illustrate the correctness of the proposed AILRC.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"11 1","pages":"1001-1005"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90357563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research of Two Phase Flow Signal Denoising Based on Fractional Wavelet Transform 基于分数阶小波变换的两相流信号去噪研究
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2018-05-01 DOI: 10.1109/DDCLS.2018.8515916
Chunling Fan, D. Chen, Lichao Fan
{"title":"Research of Two Phase Flow Signal Denoising Based on Fractional Wavelet Transform","authors":"Chunling Fan, D. Chen, Lichao Fan","doi":"10.1109/DDCLS.2018.8515916","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515916","url":null,"abstract":"The wavelet transform(WT) is only limited to the time-frequency analysis of the signal, and denoising method based on WT will ignore the details of the signal, which can result in the loss of useful components in the signal. Although the fractional Fourier transform(FRFT) breaks through the limitation of the time-frequency domain, that is it can analyze the signal in the fractional domain, it cannot represent the local characteristics of the signal. In this paper, we propose a method of fractional wavelet transform(FRWT), which not only retains the advantages of multi-resolution analysis of wavelet analysis, but also retains the function of FRFT signal in the fractional order domain, in addition, the method can make up for the defects of FRFT which can not characterize the local information of the signal. We apply this method to the denoising of two-phase flow signals and find that achieve a better performance.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"418 1","pages":"698-703"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84911453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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