Pub Date : 2016-12-01DOI: 10.1109/ICICIP.2016.7885908
Tong Wang, Wenqiang Ji, Jianbin Qiu
In this paper, the filtering problem is studied for a class of networked multirate nonlinear systems, where not only the network-induced delays but also the packet dropouts are considered. The objective is to design the corresponding filter to guarantee that the estimation errors under the effect of stochastic disturbance are bounded. The filter is designed via the idea that the associated multirate nonlinear system can be expressed as the nonlinear system with mixed delays. Finally, the simulation study of continuous stirred tank reactor (CSTR) system in double-layer architecture further demonstrates the proposed method.
{"title":"Robust filtering for multirate nonlinear networked control systems","authors":"Tong Wang, Wenqiang Ji, Jianbin Qiu","doi":"10.1109/ICICIP.2016.7885908","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885908","url":null,"abstract":"In this paper, the filtering problem is studied for a class of networked multirate nonlinear systems, where not only the network-induced delays but also the packet dropouts are considered. The objective is to design the corresponding filter to guarantee that the estimation errors under the effect of stochastic disturbance are bounded. The filter is designed via the idea that the associated multirate nonlinear system can be expressed as the nonlinear system with mixed delays. Finally, the simulation study of continuous stirred tank reactor (CSTR) system in double-layer architecture further demonstrates the proposed method.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124064423","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885910
Ying Tian, Xiaoqian Yang, Yang Ou, G. You
Coverage control in high dense wireless sensor network is an important way to make the network more efficient, which can schedule the sensors in active or sleeping state at the right time on the precondition of maintaining the network coverage. Aiming to make the best of redundant coverage of the high dense network, an area control protocol based on probabilistic coverage model is designed. To simplify the area coverage judgment, the area coverage problem is transformed into the several points coverage judgment, an area judging rule is presented base on the previous work. And then, using the promoted judging rule, a node self-schedule scheme is designed, which can turn the sensor into active state or sleep according to the information received from its active neighbors. Comparing with other coverage control protocol, our promoted protocol can maintain the network coverage quality and prolong the network lifetime more efficiently.
{"title":"An area coverage control protocol based on probabilistic coverage for wireless sensor networks","authors":"Ying Tian, Xiaoqian Yang, Yang Ou, G. You","doi":"10.1109/ICICIP.2016.7885910","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885910","url":null,"abstract":"Coverage control in high dense wireless sensor network is an important way to make the network more efficient, which can schedule the sensors in active or sleeping state at the right time on the precondition of maintaining the network coverage. Aiming to make the best of redundant coverage of the high dense network, an area control protocol based on probabilistic coverage model is designed. To simplify the area coverage judgment, the area coverage problem is transformed into the several points coverage judgment, an area judging rule is presented base on the previous work. And then, using the promoted judging rule, a node self-schedule scheme is designed, which can turn the sensor into active state or sleep according to the information received from its active neighbors. Comparing with other coverage control protocol, our promoted protocol can maintain the network coverage quality and prolong the network lifetime more efficiently.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117242106","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885903
Lili Cai, Degang Wang, Wenyan Song, Hongxing Li
Interval regression analysis is an effective method of handling uncertain and imprecise data. In this paper, a kind of spline fuzzy model is designed for modeling interval data. Spline function is chosen as the membership function, and the coefficients of this model are taken as interval-valued numbers. A target function based on approximation errors and specificity is proposed to improve the quality of estimated interval data. Accordingly, gradient descent algorithm is employed to tune these interval weights. Some numerical simulations are carried out to validate the effectiveness of the proposed spline interval regression model.
{"title":"Nonlinear interval regression analysis based on spline fuzzy model with interval coefficients","authors":"Lili Cai, Degang Wang, Wenyan Song, Hongxing Li","doi":"10.1109/ICICIP.2016.7885903","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885903","url":null,"abstract":"Interval regression analysis is an effective method of handling uncertain and imprecise data. In this paper, a kind of spline fuzzy model is designed for modeling interval data. Spline function is chosen as the membership function, and the coefficients of this model are taken as interval-valued numbers. A target function based on approximation errors and specificity is proposed to improve the quality of estimated interval data. Accordingly, gradient descent algorithm is employed to tune these interval weights. Some numerical simulations are carried out to validate the effectiveness of the proposed spline interval regression model.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114383597","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885897
Huanyu Zhao, Hao Shen
This paper studies the consensus problem for a class of discrete-time linear heterogeneous networked agents. The heterogeneous networked agents considered is converted into a equivalent error system by a model transformation. We analyze whether the original networked system can achieve consensus by analyzing whether the error system is stable. A sufficient condition for the heterogeneous networked agents to achieve consensus is obtained. The results obtained are based on matrix theory and algebraic graph theory. At the last section, we give an example to show the usefulness of the obtained results.
{"title":"Consensus for a class of discrete-time heterogeneous networked agents","authors":"Huanyu Zhao, Hao Shen","doi":"10.1109/ICICIP.2016.7885897","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885897","url":null,"abstract":"This paper studies the consensus problem for a class of discrete-time linear heterogeneous networked agents. The heterogeneous networked agents considered is converted into a equivalent error system by a model transformation. We analyze whether the original networked system can achieve consensus by analyzing whether the error system is stable. A sufficient condition for the heterogeneous networked agents to achieve consensus is obtained. The results obtained are based on matrix theory and algebraic graph theory. At the last section, we give an example to show the usefulness of the obtained results.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129217794","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885884
Tianyi Gao, Shen Yin
A data-driven model predictive control (MPC) in modified partial least squares (PLS) framework is proposed in this paper after a brief summary of MPC strategy in PLS framework. A theoretical comparison between data-driven MPC strategy in these two framework is presented, which demonstrates that MPC in modified PLS framework benefits in both computation complexity and robustness. The feature of modeling rapidly makes it possible to update the correlation model online. The reliability of the model is guaranteed by the model update strategy to a certain degree. Performance of the proposed control strategy is verified through simulations of a numerical example. It can be illuminated from the simulation that the proposed method performances well.
{"title":"A novel model predictive control strategy in modified PLS framework","authors":"Tianyi Gao, Shen Yin","doi":"10.1109/ICICIP.2016.7885884","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885884","url":null,"abstract":"A data-driven model predictive control (MPC) in modified partial least squares (PLS) framework is proposed in this paper after a brief summary of MPC strategy in PLS framework. A theoretical comparison between data-driven MPC strategy in these two framework is presented, which demonstrates that MPC in modified PLS framework benefits in both computation complexity and robustness. The feature of modeling rapidly makes it possible to update the correlation model online. The reliability of the model is guaranteed by the model update strategy to a certain degree. Performance of the proposed control strategy is verified through simulations of a numerical example. It can be illuminated from the simulation that the proposed method performances well.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125747408","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885878
Jian Hou, Wei-Xue Liu
The density peak based clustering algorithm is a simple yet effective clustering approach. This algorithm firstly calculates the local density of each data and the distance to the nearest neighbor with higher density. Based on the assumption that cluster centers are density peaks and they are relatively far from each other, this algorithm isolates the candidates of cluster centers from the non-center data. After the cluster centers are identified, the other data are assigned labels equaling to those of their nearest neighbors with higher density. In this way the clustering can be accomplished efficiently and clusters of arbitrary shapes can be obtained. The key of the density peak based clustering algorithm lies in the density calculation method. In this paper we study the influence of the data amount used in density calculation on the clustering results of the density peak based algorithm. As a result, we arrive at some conclusions on the selection of the data amount, which can be useful in applying this algorithm in real tasks.
{"title":"Evaluating the density parameter in density peak based clustering","authors":"Jian Hou, Wei-Xue Liu","doi":"10.1109/ICICIP.2016.7885878","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885878","url":null,"abstract":"The density peak based clustering algorithm is a simple yet effective clustering approach. This algorithm firstly calculates the local density of each data and the distance to the nearest neighbor with higher density. Based on the assumption that cluster centers are density peaks and they are relatively far from each other, this algorithm isolates the candidates of cluster centers from the non-center data. After the cluster centers are identified, the other data are assigned labels equaling to those of their nearest neighbors with higher density. In this way the clustering can be accomplished efficiently and clusters of arbitrary shapes can be obtained. The key of the density peak based clustering algorithm lies in the density calculation method. In this paper we study the influence of the data amount used in density calculation on the clustering results of the density peak based algorithm. As a result, we arrive at some conclusions on the selection of the data amount, which can be useful in applying this algorithm in real tasks.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131380179","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885898
Yao Cheng, Xin Gao, Tianyi Gao, Zelin Ren
Aimed to build a health monitoring scheme of complex mechatronic systems, a quality prediction on Tennessee Eastman (TE) process based on support vector machine (SVM) is proposed in this paper after a brief investigation on the regression ability of SVM. The SVM model is builded using the datasets generated by TE process simulation platform. Furthermore the prediction precision of SVM is testified using the simulation of TE process compared with other prediction methods. It indicates from the results that SVM is more beneficial according to the root mean square errors (RMSE) between the actual and the predicted data.
{"title":"Study on support vector machine based quality prediction of complex mechatronic systems","authors":"Yao Cheng, Xin Gao, Tianyi Gao, Zelin Ren","doi":"10.1109/ICICIP.2016.7885898","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885898","url":null,"abstract":"Aimed to build a health monitoring scheme of complex mechatronic systems, a quality prediction on Tennessee Eastman (TE) process based on support vector machine (SVM) is proposed in this paper after a brief investigation on the regression ability of SVM. The SVM model is builded using the datasets generated by TE process simulation platform. Furthermore the prediction precision of SVM is testified using the simulation of TE process compared with other prediction methods. It indicates from the results that SVM is more beneficial according to the root mean square errors (RMSE) between the actual and the predicted data.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132781800","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885891
Li Li, Qianqian Ma, Hongwei Xia, G. Ma, Dali Zhang
The paper concerns the issue of H∞ fuzzy filter design for T-S fuzzy-model based system involving time-delay. In the light of the Lyapunov stability theory, improved stability criteria for the filtering system are developed, and corresponding H∞ fuzzy filter design approaches are proposed as well, all the derived results are given as the feasibility of LMIs. Besides, the novel imperfect premise matching methodology is adopted to derive the H∞ fuzzy filter, which allows the H∞ fuzzy filter and the T-S fuzzy model have distinct membership functions and different number of fuzzy rules, such design can provide larger design flexibility and better robustness property. Finally, two numerical examples are offered to clarify the validity and the superiority of the designed method.
{"title":"New H∞ filter design approach for time-delay fuzzy-model-based system under imperfect premise matching","authors":"Li Li, Qianqian Ma, Hongwei Xia, G. Ma, Dali Zhang","doi":"10.1109/ICICIP.2016.7885891","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885891","url":null,"abstract":"The paper concerns the issue of H∞ fuzzy filter design for T-S fuzzy-model based system involving time-delay. In the light of the Lyapunov stability theory, improved stability criteria for the filtering system are developed, and corresponding H∞ fuzzy filter design approaches are proposed as well, all the derived results are given as the feasibility of LMIs. Besides, the novel imperfect premise matching methodology is adopted to derive the H∞ fuzzy filter, which allows the H∞ fuzzy filter and the T-S fuzzy model have distinct membership functions and different number of fuzzy rules, such design can provide larger design flexibility and better robustness property. Finally, two numerical examples are offered to clarify the validity and the superiority of the designed method.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131761454","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885886
Qianqian Ma, Li Li, Hongwei Xia, Mingyang Yang, G. Ma
This paper investigates stability and stabilization analyses issue for T-S fuzzy-model-based systems involving distributed time-delay. The novel imperfect premise matching methodology is employed to derive fuzzy controller, unlike conventional PDC method, this novel technique allows the designed fuzzy controller and the T-S fuzzy model to have distinct membership functions and number of rules, as a result, great flexibility and better robustness can be achieved. Moreover, with the introduction of one novel inequality which is tighter than other existing ones, relaxed LMI-based stability and stabilization criteria are obtained in term of the Lyapunov stability theory. Lastly, two numerical examples are offered to prove the valadity of the derived results.
{"title":"New results on stability and stabilization analyses for T-S fuzzy systems with distributed time-delay under imperfect premise matching","authors":"Qianqian Ma, Li Li, Hongwei Xia, Mingyang Yang, G. Ma","doi":"10.1109/ICICIP.2016.7885886","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885886","url":null,"abstract":"This paper investigates stability and stabilization analyses issue for T-S fuzzy-model-based systems involving distributed time-delay. The novel imperfect premise matching methodology is employed to derive fuzzy controller, unlike conventional PDC method, this novel technique allows the designed fuzzy controller and the T-S fuzzy model to have distinct membership functions and number of rules, as a result, great flexibility and better robustness can be achieved. Moreover, with the introduction of one novel inequality which is tighter than other existing ones, relaxed LMI-based stability and stabilization criteria are obtained in term of the Lyapunov stability theory. Lastly, two numerical examples are offered to prove the valadity of the derived results.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114216663","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 : 2016-12-01DOI: 10.1109/ICICIP.2016.7885896
Xu-Lei Yang, Chengan Guo
Liver segmentation in abdominal CT images is vital prior to liver disease diagnosis and computer-aided diagnosis. Since an abdominal CT image is some complex in which the pixels of the liver region and some other adjacent parts often distribute in the same value range, commonly used value-based segmentation methods have difficulty in dealing with this situation. In order to overcome this shortcoming, in this paper we present a spatial-domain segmentation method in which both the value information of the pixels and the spatial relationship between them are utilized in the segmentation process and meanwhile the spatial information, such as the area, boundary or location, of the target is extracted, thus the target region to be segmented can be distinguished from the other parts in same value range by use of the spatial information. Furthermore, a parallel algorithm is designed and implemented on GPU for improving the computation efficiency of the spatial-domain segmentation method. Experiment results obtained in the work confirm the effectiveness of the new segmentation algorithm.
{"title":"Parallel spatial-domain liver segmentation of CT abdominal images","authors":"Xu-Lei Yang, Chengan Guo","doi":"10.1109/ICICIP.2016.7885896","DOIUrl":"https://doi.org/10.1109/ICICIP.2016.7885896","url":null,"abstract":"Liver segmentation in abdominal CT images is vital prior to liver disease diagnosis and computer-aided diagnosis. Since an abdominal CT image is some complex in which the pixels of the liver region and some other adjacent parts often distribute in the same value range, commonly used value-based segmentation methods have difficulty in dealing with this situation. In order to overcome this shortcoming, in this paper we present a spatial-domain segmentation method in which both the value information of the pixels and the spatial relationship between them are utilized in the segmentation process and meanwhile the spatial information, such as the area, boundary or location, of the target is extracted, thus the target region to be segmented can be distinguished from the other parts in same value range by use of the spatial information. Furthermore, a parallel algorithm is designed and implemented on GPU for improving the computation efficiency of the spatial-domain segmentation method. Experiment results obtained in the work confirm the effectiveness of the new segmentation algorithm.","PeriodicalId":226381,"journal":{"name":"2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123615036","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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