Pub Date : 2017-05-01DOI: 10.1109/DDCLS.2017.8068055
Jun-Zhou Yue, Qiao Zhu
This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feeedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Because the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is used to put a equivalent disturbance into the input channel. In this situation, the vibration control can be realized by setting the control input be the identified EID. Then, for the disturbance with known frequencies, the AFC is introduced to reject the disturbance but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of disturbance in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis method is adopted to precisely identify the unknown frequencies of the disturbance. Finally, experiments results demonstrate the efficiency of the AFC algorithm.
{"title":"Active vibration control of piezoelectricity cantilever beam using an adaptive feedforward control method","authors":"Jun-Zhou Yue, Qiao Zhu","doi":"10.1109/DDCLS.2017.8068055","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068055","url":null,"abstract":"This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feeedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Because the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is used to put a equivalent disturbance into the input channel. In this situation, the vibration control can be realized by setting the control input be the identified EID. Then, for the disturbance with known frequencies, the AFC is introduced to reject the disturbance but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of disturbance in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis method is adopted to precisely identify the unknown frequencies of the disturbance. Finally, experiments results demonstrate the efficiency of the AFC algorithm.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126332239","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068146
Mingxuan Sun, Jianyong Chen, He Li
This paper presents a finite-time control strategy for uncertain systems with unknown time-invariant parameters. The finite-time adaptive robust controller is designed via Lyapunov approach, where projection-type integral and incremental adaptation laws are applied in estimation of the time-invariant parametric uncertainties, respectively. The terminal attractor is suggested in the adaptive robust controller, and with the proposed control schemes, the finite time convergence can be realized. The bounded error convergence result is obtained in the presence of disturbances. Otherwise, the zero-error convergence can be achieved. The numerical results demonstrate the effectiveness of the proposed control schemes.
{"title":"Finite-time adaptive robust control","authors":"Mingxuan Sun, Jianyong Chen, He Li","doi":"10.1109/DDCLS.2017.8068146","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068146","url":null,"abstract":"This paper presents a finite-time control strategy for uncertain systems with unknown time-invariant parameters. The finite-time adaptive robust controller is designed via Lyapunov approach, where projection-type integral and incremental adaptation laws are applied in estimation of the time-invariant parametric uncertainties, respectively. The terminal attractor is suggested in the adaptive robust controller, and with the proposed control schemes, the finite time convergence can be realized. The bounded error convergence result is obtained in the presence of disturbances. Otherwise, the zero-error convergence can be achieved. The numerical results demonstrate the effectiveness of the proposed control schemes.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126786134","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068117
Hongqi Zhang, Linqing Wang, Jun Zhao, Wei Wang
Blast furnace gas (BFG) system of steel enterprise generally accompanies with multi-dimension and nonlinear features. It's a hard assignment for energy scheduling operators to make real-time scheduling decision when monitoring such system. In this study, a novel dimensionality reduction method named Space Direction Neighborhood Preserving Embedding (SDNPE) is proposed for the BFG system monitoring and scheduling units determination. To maintain the system dynamic characteristic in the low dimension space, such method constructs a neighborhood graph that searches for nearest neighbors with respect to both the neighbors in spatial scales and fluctuation tendency of the gas flow data. Then, for the BFG system monitoring and scheduling units determination, Hotelling's T2 chart and score chart are constructed upon the SDNPE model. Experiments with real-time data of an iron enterprise in China demonstrated the effectiveness of the proposed method.
{"title":"Space direction neighborhood preserving embedding-based monitoring and scheduling guidance for blast furnace gas system","authors":"Hongqi Zhang, Linqing Wang, Jun Zhao, Wei Wang","doi":"10.1109/DDCLS.2017.8068117","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068117","url":null,"abstract":"Blast furnace gas (BFG) system of steel enterprise generally accompanies with multi-dimension and nonlinear features. It's a hard assignment for energy scheduling operators to make real-time scheduling decision when monitoring such system. In this study, a novel dimensionality reduction method named Space Direction Neighborhood Preserving Embedding (SDNPE) is proposed for the BFG system monitoring and scheduling units determination. To maintain the system dynamic characteristic in the low dimension space, such method constructs a neighborhood graph that searches for nearest neighbors with respect to both the neighbors in spatial scales and fluctuation tendency of the gas flow data. Then, for the BFG system monitoring and scheduling units determination, Hotelling's T2 chart and score chart are constructed upon the SDNPE model. Experiments with real-time data of an iron enterprise in China demonstrated the effectiveness of the proposed method.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129440087","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068075
Jialu Zhang, Yong Fang, Yuzho Wu
In this paper, we consider iterative learning control(ILC) for discrete-time multi-agent system formation with one-step random time-delay. Random delays during transmission seriously affect the convergence performance of multi-agent formation. Based on one-step random time-delay model, the transition matrix of system is derived, which contains the impact factors of random delays. A learning control scheme is proposed and the convergence of system tracking errors is guaranteed. Simulation results show that the convergence rate is reduced when the probabilities of time-delay are getting higher.
{"title":"An ILC method of formation control for multi-agent system with one-step random time-delay","authors":"Jialu Zhang, Yong Fang, Yuzho Wu","doi":"10.1109/DDCLS.2017.8068075","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068075","url":null,"abstract":"In this paper, we consider iterative learning control(ILC) for discrete-time multi-agent system formation with one-step random time-delay. Random delays during transmission seriously affect the convergence performance of multi-agent formation. Based on one-step random time-delay model, the transition matrix of system is derived, which contains the impact factors of random delays. A learning control scheme is proposed and the convergence of system tracking errors is guaranteed. Simulation results show that the convergence rate is reduced when the probabilities of time-delay are getting higher.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"11 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134334688","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068102
Lin Zhao, Jinpeng Yu
This paper studies the adaptive bipartite consensus tracking problems for second-order coopetition multi-agent systems with input saturation. A fuzzy-based command filtered backstepping scheme is developed, which can guarantee the bipartite position tracking errors converging to the desired neighborhood and all the closed-loop signals are bounded although the nonlinear dynamics are unknown and the input saturation exists. An example is included to verify the proposed method.
{"title":"Adaptive bipartite consensus tracking control for coopetition multi-agent systems with input saturation","authors":"Lin Zhao, Jinpeng Yu","doi":"10.1109/DDCLS.2017.8068102","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068102","url":null,"abstract":"This paper studies the adaptive bipartite consensus tracking problems for second-order coopetition multi-agent systems with input saturation. A fuzzy-based command filtered backstepping scheme is developed, which can guarantee the bipartite position tracking errors converging to the desired neighborhood and all the closed-loop signals are bounded although the nonlinear dynamics are unknown and the input saturation exists. An example is included to verify the proposed method.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"3 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131436240","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}
The adaptive elastic net has been widely studied in the microarray classification due to the elegant performances in gene selection. However, the classification accuracy will be affected if the noise is included. As such, this paper proposes a weighted adaptive elastic net for the binary microarray classification with noise by using the distances from the sample points to both class centers. Furthermore, the performance of adaptive gene selection is proved and the solution path algorithm is developed. Finally, the results on two cancer data added 4 additional samples illustrate that the weighted adaptive elastic net can achieve considerable classification accuracy and select the genes related with diseases.
{"title":"Microarray classification with noise via weighted adaptive elastic net","authors":"Juntao Li, Jingxuan Wang, Yuhan Zheng, Huimin Xiao","doi":"10.1109/DDCLS.2017.8068109","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068109","url":null,"abstract":"The adaptive elastic net has been widely studied in the microarray classification due to the elegant performances in gene selection. However, the classification accuracy will be affected if the noise is included. As such, this paper proposes a weighted adaptive elastic net for the binary microarray classification with noise by using the distances from the sample points to both class centers. Furthermore, the performance of adaptive gene selection is proved and the solution path algorithm is developed. Finally, the results on two cancer data added 4 additional samples illustrate that the weighted adaptive elastic net can achieve considerable classification accuracy and select the genes related with diseases.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133943097","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068069
Yu Pang, L. Jia, Zhan Liu, Q. Gao
Many sets of wind turbines of the wind farm in Shan Xi province run above the rated wind speed, especially in the condition of wind speed 17m/s or above, wind turbine nacelle occurs vibration in the vertical direction of transmission chain which is characterized emergency, intermittent, accidental, and distinctive. Moreover, vibration cycle is not obvious and vibration strength is large. Severe vibration does harm to wind turbine that then will be able to lead wind turbine halt. According to this phenomenon, a method of emergency fault diagnosis for wind turbine nacelle based on empirical mode decomposition (EMD) is presented in this paper to discriminate a variety of factors carefully that have led to excessive vibration. In particular, the results are shown in this paper that strong tower shadow effect may cause excessive vibration of wind turbine nacelle, and then gives rise to shut down. In the meantime, curve theory analysis of the blade's aerodynamic characteristics is deduced in this paper. It demonstrates that the proposed method EMD works well in the face of fault diagnosis for wind turbine nacelle with a better overall performance.
{"title":"Emergency fault diagnosis for wind turbine nacelle","authors":"Yu Pang, L. Jia, Zhan Liu, Q. Gao","doi":"10.1109/DDCLS.2017.8068069","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068069","url":null,"abstract":"Many sets of wind turbines of the wind farm in Shan Xi province run above the rated wind speed, especially in the condition of wind speed 17m/s or above, wind turbine nacelle occurs vibration in the vertical direction of transmission chain which is characterized emergency, intermittent, accidental, and distinctive. Moreover, vibration cycle is not obvious and vibration strength is large. Severe vibration does harm to wind turbine that then will be able to lead wind turbine halt. According to this phenomenon, a method of emergency fault diagnosis for wind turbine nacelle based on empirical mode decomposition (EMD) is presented in this paper to discriminate a variety of factors carefully that have led to excessive vibration. In particular, the results are shown in this paper that strong tower shadow effect may cause excessive vibration of wind turbine nacelle, and then gives rise to shut down. In the meantime, curve theory analysis of the blade's aerodynamic characteristics is deduced in this paper. It demonstrates that the proposed method EMD works well in the face of fault diagnosis for wind turbine nacelle with a better overall performance.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130279978","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068114
Yuan Gao, H. Hu, L. Yu, H. Yuan, X. Dai
Considering the time-varying scaling function matrix and system disturbances, a new sliding mode control strategy is proposed to realize modified function projective synchronization (MFPS) of two different fractional-order hyperchaotic systems, meanwhile improve the control robustness of synchronization system. From the MFPS error equations, combining a proper fractional-order exponential reaching raw, an active controller for MFPS is derived out via sliding mode control technology. By mean of the stability theorem, the asymptotic stability of synchronization error system is proved. Simulation results of the MFPS between fractional-order hyperchaoticLorenz system and Chen system demonstrate the validity of the presented method.
{"title":"Modified function projective synchronization of fractional-order hyperchaotic systems based on active sliding mode control","authors":"Yuan Gao, H. Hu, L. Yu, H. Yuan, X. Dai","doi":"10.1109/DDCLS.2017.8068114","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068114","url":null,"abstract":"Considering the time-varying scaling function matrix and system disturbances, a new sliding mode control strategy is proposed to realize modified function projective synchronization (MFPS) of two different fractional-order hyperchaotic systems, meanwhile improve the control robustness of synchronization system. From the MFPS error equations, combining a proper fractional-order exponential reaching raw, an active controller for MFPS is derived out via sliding mode control technology. By mean of the stability theorem, the asymptotic stability of synchronization error system is proved. Simulation results of the MFPS between fractional-order hyperchaoticLorenz system and Chen system demonstrate the validity of the presented method.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132842028","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068148
Bo Zhang, Meng Zhou, Min Fan, Zhihong Liu, Qi Han
This paper proposes an overall design for a smart power utilization system, and presents a realizable method based on practices in pilot districts in Chongqing. This design can effectively achieve data transmission and communication among many subsystems, while information management, monitoring, and controlling of smart power utilization districts in the subsystems are divided into different security zones. This system has two outstanding characteristics. One is that monitoring and accurate fault location for user's meters and power distribution equipment are realized through regional power distribution automation. The other is that electric vehicle charge pile management can make full use of peak and valley load shifting and realize efficient coordinate regulation by distribution load. This smart power utilization system has been successfully put into use in Jiaxinqinyuan and Fubaoquan districts in Chongqing.
{"title":"Design and application of smart power utilization system in pilot districts of Chongqing","authors":"Bo Zhang, Meng Zhou, Min Fan, Zhihong Liu, Qi Han","doi":"10.1109/DDCLS.2017.8068148","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068148","url":null,"abstract":"This paper proposes an overall design for a smart power utilization system, and presents a realizable method based on practices in pilot districts in Chongqing. This design can effectively achieve data transmission and communication among many subsystems, while information management, monitoring, and controlling of smart power utilization districts in the subsystems are divided into different security zones. This system has two outstanding characteristics. One is that monitoring and accurate fault location for user's meters and power distribution equipment are realized through regional power distribution automation. The other is that electric vehicle charge pile management can make full use of peak and valley load shifting and realize efficient coordinate regulation by distribution load. This smart power utilization system has been successfully put into use in Jiaxinqinyuan and Fubaoquan districts in Chongqing.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"151 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114048650","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 : 2017-05-01DOI: 10.1109/DDCLS.2017.8068154
S. Bi, Qi Diao, Xiaofeng Chai, Cunwu Han
Habituation is non-associative learning mechanism of biological neurons. This paper studied the simplified description of associative learning mechanism, and based on the classical M-P (McCulloch — Pitts) neuron model, put forward study neurons model with the ability of habituation learning, including habituation neurons. At the same time, in this paper, based on the simplified description of Learning neurons, the mathematical model of habituation neurons is designed, and habituation neurons are applied to deep convolution neural networks. It has been verified by experiment that habituation neurons have typical habituation learning ability, and can optimize the performance of convolution networks.
{"title":"On a neural network model based on non-associative learning mechanism and its application","authors":"S. Bi, Qi Diao, Xiaofeng Chai, Cunwu Han","doi":"10.1109/DDCLS.2017.8068154","DOIUrl":"https://doi.org/10.1109/DDCLS.2017.8068154","url":null,"abstract":"Habituation is non-associative learning mechanism of biological neurons. This paper studied the simplified description of associative learning mechanism, and based on the classical M-P (McCulloch — Pitts) neuron model, put forward study neurons model with the ability of habituation learning, including habituation neurons. At the same time, in this paper, based on the simplified description of Learning neurons, the mathematical model of habituation neurons is designed, and habituation neurons are applied to deep convolution neural networks. It has been verified by experiment that habituation neurons have typical habituation learning ability, and can optimize the performance of convolution networks.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116681616","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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