Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8516000
K. Zhuang
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.
{"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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8516038
Ma Yabin, Chen Chen, Shu Qiqi, Wang Jian, Li Hongliang, Huang Darong
A novel method based on Hilbert Transform (HT) and Empirical Mode Decomposition (EMD) algorithm is proposed in this paper, which separates time series into intrinsic mode functions (IMFs) with different time scales and applies the Hilbert transformation for every IMF to obtain the Hilbert spectrum. Firstly, relevant theories of the proposed method are introduced. Then, based on these theoretical introductions, the fault vibration signals of rolling bearing are dealt with related algorithm. The research results demonstrate that the characteristic frequency of bearing fault can be obtained by proposed method, which is more effective compared with existing algorithm.
{"title":"Fault Diagnosis of Rolling Bearing based on EMD Combined with HHT Envelope and Wavelet Spectrum Transform","authors":"Ma Yabin, Chen Chen, Shu Qiqi, Wang Jian, Li Hongliang, Huang Darong","doi":"10.1109/DDCLS.2018.8516038","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8516038","url":null,"abstract":"A novel method based on Hilbert Transform (HT) and Empirical Mode Decomposition (EMD) algorithm is proposed in this paper, which separates time series into intrinsic mode functions (IMFs) with different time scales and applies the Hilbert transformation for every IMF to obtain the Hilbert spectrum. Firstly, relevant theories of the proposed method are introduced. Then, based on these theoretical introductions, the fault vibration signals of rolling bearing are dealt with related algorithm. The research results demonstrate that the characteristic frequency of bearing fault can be obtained by proposed method, which is more effective compared with existing algorithm.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"26 1","pages":"481-485"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78794807","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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8515913
N. Li, Yujie Sun
In order to increase the accuracy of traffic simulation and better reproduce the real traffic condition at signalized intersections, this paper proposed a parameter calibration method based on the traffic distribution rules at signalized intersections. First, after qualitatively analyzing the traffic condition at signalized intersections based on dynamic traffic features, this paper selected the key parameters that need to be calibrated. Then, regarding the selected key parameters, this paper first designed and implemented the collecting method. Then filtered and analyzed the data, and acquired the distribution pattern of each key parameter at signalized intersection. Finally, in order to validate the calibration process based on vehicle types through simulation, this paper chose travel time and number of stops as validation parameters. The results showed that there had been a great increase in the accuracy after calibration. The maximum inaccuracy among all evaluation parameters was 14.6%, which indicated that the calibration process based on traffic characteristics distribution at signalized intersections was effective.
{"title":"VISSIM Parameter Calibration Based on Traffic Characteristics Distribution at Signalized Intersections","authors":"N. Li, Yujie Sun","doi":"10.1109/DDCLS.2018.8515913","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515913","url":null,"abstract":"In order to increase the accuracy of traffic simulation and better reproduce the real traffic condition at signalized intersections, this paper proposed a parameter calibration method based on the traffic distribution rules at signalized intersections. First, after qualitatively analyzing the traffic condition at signalized intersections based on dynamic traffic features, this paper selected the key parameters that need to be calibrated. Then, regarding the selected key parameters, this paper first designed and implemented the collecting method. Then filtered and analyzed the data, and acquired the distribution pattern of each key parameter at signalized intersection. Finally, in order to validate the calibration process based on vehicle types through simulation, this paper chose travel time and number of stops as validation parameters. The results showed that there had been a great increase in the accuracy after calibration. The maximum inaccuracy among all evaluation parameters was 14.6%, which indicated that the calibration process based on traffic characteristics distribution at signalized intersections was effective.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"97 1","pages":"150-153"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84826288","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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8515916
Chunling Fan, D. Chen, Lichao Fan
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.
{"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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8516018
Ang-Ji Lin, Shu-Ting Sun, Xiao-dong Li
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.
{"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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8516002
Danfeng Chen, Cong Wang, Wenbo Zhu
For nonlinear dynamical systems, structural stability is a fundamental concept. It provides a qualitative tool for analyzing the equivalent relation between a nonlinear dynamical system and its perturbed system. Currently, most researches about structural stability, including some applications in practical systems, are mainly limited to qualitative analysis. In this paper, our focus is on the quantitative property of structural stability. A new measure will be proposed from the perspective of structural stability and gap metric under the Deterministic Learning theory, which provides more incentives for further applications in pattern recognition, classification as well as fault detection. Simulation studies are included to further demonstrate the effectiveness of this measure.
{"title":"A New Measure of Dynamic Similarity for Nonlinear Systems based on Gap Metric and Deterministic Learning Theory","authors":"Danfeng Chen, Cong Wang, Wenbo Zhu","doi":"10.1109/DDCLS.2018.8516002","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8516002","url":null,"abstract":"For nonlinear dynamical systems, structural stability is a fundamental concept. It provides a qualitative tool for analyzing the equivalent relation between a nonlinear dynamical system and its perturbed system. Currently, most researches about structural stability, including some applications in practical systems, are mainly limited to qualitative analysis. In this paper, our focus is on the quantitative property of structural stability. A new measure will be proposed from the perspective of structural stability and gap metric under the Deterministic Learning theory, which provides more incentives for further applications in pattern recognition, classification as well as fault detection. Simulation studies are included to further demonstrate the effectiveness of this measure.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"35 1","pages":"521-526"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88186049","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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8515999
Zunshui Cheng, Tiansun Wang, Youming Xin
We deal with high-order distributed consensus protocols in multi agent networks. It is shown that the inner coupling strengths play a key role in reaching consensus for high-order systems. Scheme for choosing coupling strengths is derived for the third-order consensus and the fourth-order consensus. We found that high-order consensus can not be achieved even if inner coupling strengths are very large when they are selected incorrectly. The high-order consensus of complex networks are particularly targeted. This result helps investigate large scale multi-agent networks.
{"title":"High-Order Distributed Consensus in Multi-Agent Networks","authors":"Zunshui Cheng, Tiansun Wang, Youming Xin","doi":"10.1109/DDCLS.2018.8515999","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515999","url":null,"abstract":"We deal with high-order distributed consensus protocols in multi agent networks. It is shown that the inner coupling strengths play a key role in reaching consensus for high-order systems. Scheme for choosing coupling strengths is derived for the third-order consensus and the fourth-order consensus. We found that high-order consensus can not be achieved even if inner coupling strengths are very large when they are selected incorrectly. The high-order consensus of complex networks are particularly targeted. This result helps investigate large scale multi-agent networks.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"11 1","pages":"965-969"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88315341","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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8516062
Qiongxia Yu, Xuhui Bu, R. Chi, Z. Hou
High-speed trains always operate from the same departure station to the same terminal station and hence iterative learning control (ILC) is an appropriate approach for automatic train control. However, due to complex environment and unknown uncertainties, the train may not arrive at the terminal station on time, or earlier and later than the schedule time in each operation. To address this problem, a modified proportional-type (P-type) ILC is presented where the trial length in each operation can be randomly varying. Moreover, the convergence condition in 2-norm is also derived through rigorous analysis. The effectiveness of the modified P-type ILC is further verified through simulations.
{"title":"Modified P-Type ILC for High-Speed Trains with Varying Trial Lengths","authors":"Qiongxia Yu, Xuhui Bu, R. Chi, Z. Hou","doi":"10.1109/DDCLS.2018.8516062","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8516062","url":null,"abstract":"High-speed trains always operate from the same departure station to the same terminal station and hence iterative learning control (ILC) is an appropriate approach for automatic train control. However, due to complex environment and unknown uncertainties, the train may not arrive at the terminal station on time, or earlier and later than the schedule time in each operation. To address this problem, a modified proportional-type (P-type) ILC is presented where the trial length in each operation can be randomly varying. Moreover, the convergence condition in 2-norm is also derived through rigorous analysis. The effectiveness of the modified P-type ILC is further verified through simulations.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"34 1","pages":"1006-1010"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78943223","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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8515997
W. Zhou, Miao Yu
This technical note addresses an adaptive iterative learning control (AILC) problem for nonlinear dynamical systems with partially unknown iteration-varying parameter. Referring to the scheme of state-space, an AILC effort is presented for randomly varying reference tracking together with initial shift problem in iteration domain. Furthermore, the AILC technique is extended to systems with several parameters in discussion. A simulation example confirms the validity of the proposed method.
{"title":"Adaptive Iterative Learning Control Mechanism for Nonlinear Systems subject to High-Order Internal Model","authors":"W. Zhou, Miao Yu","doi":"10.1109/DDCLS.2018.8515997","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515997","url":null,"abstract":"This technical note addresses an adaptive iterative learning control (AILC) problem for nonlinear dynamical systems with partially unknown iteration-varying parameter. Referring to the scheme of state-space, an AILC effort is presented for randomly varying reference tracking together with initial shift problem in iteration domain. Furthermore, the AILC technique is extended to systems with several parameters in discussion. A simulation example confirms the validity of the proposed method.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"31 1","pages":"599-604"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72948754","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}
Pub Date : 2018-05-01DOI: 10.1109/DDCLS.2018.8515987
Xiaocheng Zhang, Wenchao Xue, H. Fang, Xingkang He
This paper studies the state estimation problem for a class of continuous-time stochastic systems with unknown nonlinear dynamics and measurement noise. Enlightened by the extended state observer (ESO) in timely estimating both the internal unknown dynamics and the external disturbance of systems, the paper constructs the extended state based KalmanBucy filter (ESKBF) to achieve better filtering performance. It is shown that ESKBF can provide the upper bound of the covariance matrix of estimation error, which is critical in evaluating the filtering precision. Besides, the stability of ESKBF is rigorously proven in the presence of unknown nonlinear dynamics, while the stability of traditional Kalman-Bucy filter is hard to be guaranteed under the same condition. Moreover, the asymptotic optimality of ESKBF for time-invariant system under constant disturbance is given. Finally, numerical simulations show the effectiveness of the method.
{"title":"On Extended State Based Kalman-Bucy Filter","authors":"Xiaocheng Zhang, Wenchao Xue, H. Fang, Xingkang He","doi":"10.1109/DDCLS.2018.8515987","DOIUrl":"https://doi.org/10.1109/DDCLS.2018.8515987","url":null,"abstract":"This paper studies the state estimation problem for a class of continuous-time stochastic systems with unknown nonlinear dynamics and measurement noise. Enlightened by the extended state observer (ESO) in timely estimating both the internal unknown dynamics and the external disturbance of systems, the paper constructs the extended state based KalmanBucy filter (ESKBF) to achieve better filtering performance. It is shown that ESKBF can provide the upper bound of the covariance matrix of estimation error, which is critical in evaluating the filtering precision. Besides, the stability of ESKBF is rigorously proven in the presence of unknown nonlinear dynamics, while the stability of traditional Kalman-Bucy filter is hard to be guaranteed under the same condition. Moreover, the asymptotic optimality of ESKBF for time-invariant system under constant disturbance is given. Finally, numerical simulations show the effectiveness of the method.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"81 1","pages":"1158-1163"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76716184","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}
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