Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5192457
Hongjun Chu, Lixin Gao
The global robust stability problem is considered for a class of uncertain stochastic Cohen-Grossberg neural networks with Markovian jumping parameters and time-delay in this paper. The time delays are mode-dependent mixed delays including discrete delays and distributed delays. The jumping parameters considered here are generated from a continuous-time discrete-state homogenous Markov chain, which are governed by a Markov process with discrete and finite state space. Based on the Lyapunov method and stochastic analysis approaches, a stability criterion is established, which can be expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is given to demonstrate the effectiveness of the proposed results.
{"title":"A global robust stability criterion for jumping stochastic Cohen- Grossberg neural networks with mode-dependent mixed delays","authors":"Hongjun Chu, Lixin Gao","doi":"10.1109/CCDC.2009.5192457","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5192457","url":null,"abstract":"The global robust stability problem is considered for a class of uncertain stochastic Cohen-Grossberg neural networks with Markovian jumping parameters and time-delay in this paper. The time delays are mode-dependent mixed delays including discrete delays and distributed delays. The jumping parameters considered here are generated from a continuous-time discrete-state homogenous Markov chain, which are governed by a Markov process with discrete and finite state space. Based on the Lyapunov method and stochastic analysis approaches, a stability criterion is established, which can be expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is given to demonstrate the effectiveness of the proposed results.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133255752","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5192277
Weihong Wang, Song Wang
To develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems, is one key challenge in content-based image retrieval(CBIR). In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image testbed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building web-scale CBIR systems.
{"title":"A method using locality-sensitive hashing for large-scale content-based image retrieval","authors":"Weihong Wang, Song Wang","doi":"10.1109/CCDC.2009.5192277","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5192277","url":null,"abstract":"To develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems, is one key challenge in content-based image retrieval(CBIR). In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image testbed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building web-scale CBIR systems.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131439671","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5192223
F. Du, W. Du
To aim at time-variant or uncertain network delay in the wireless networked control systems (WNCS), as well as Smith predictor model and real model of the controlled plant might be mismatch, a new Smith dynamic predictor combined with fuzzy immune control is proposed. Because new Smith dynamic predictor hides predictor model of the network delay into real network data transmission process, further the network delay no longer need to be measured, identified or estimated on-line. It is applicable to some occasions that wireless network delay is random, time-variant or uncertain, possibly large compared to one, even tens sampling periods, at the same time, there are some data dropouts in closed loop. Based on IEEE 802.15.4 (ZigBee), the results of simulation show validity of the control scheme, and indicate that system has better dynamic performance and robustness.
{"title":"Fuzzy immune control and new Smith predictor for wireless networked control systems","authors":"F. Du, W. Du","doi":"10.1109/CCDC.2009.5192223","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5192223","url":null,"abstract":"To aim at time-variant or uncertain network delay in the wireless networked control systems (WNCS), as well as Smith predictor model and real model of the controlled plant might be mismatch, a new Smith dynamic predictor combined with fuzzy immune control is proposed. Because new Smith dynamic predictor hides predictor model of the network delay into real network data transmission process, further the network delay no longer need to be measured, identified or estimated on-line. It is applicable to some occasions that wireless network delay is random, time-variant or uncertain, possibly large compared to one, even tens sampling periods, at the same time, there are some data dropouts in closed loop. Based on IEEE 802.15.4 (ZigBee), the results of simulation show validity of the control scheme, and indicate that system has better dynamic performance and robustness.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123184118","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5191976
Xiaoh Wang
A soft-sensing method for oil, protein and starch content in the corn is developed using near-infrared reflectance spectroscopy(NIRS) and least square support vector regression(LS-SVR) techniques, and the feasibility of using different NIR spectrometers for analysis is also examined. Firstly, 90 corn samples are scanned using NIR spectrometers. Then, the original NIRS are processed with multiplicative scatter correction(MSC), Savitzky-Golay second derivative analysis and principal component analysis(PCA). Finally, the soft-sensing model for corn composition content is built using LS-SVR algorithm. The research results show that correlation coefficient (Rc) of NIRS calibrated and actual oil, protein and starch content measured by chemical method are 0.947, 0.969 and 0.948 respectively. It is proved that soft-sensing method has strong robustness for agricultural products.
{"title":"A soft-sensing method for corn composition content using NIRS and LS-SVR","authors":"Xiaoh Wang","doi":"10.1109/CCDC.2009.5191976","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5191976","url":null,"abstract":"A soft-sensing method for oil, protein and starch content in the corn is developed using near-infrared reflectance spectroscopy(NIRS) and least square support vector regression(LS-SVR) techniques, and the feasibility of using different NIR spectrometers for analysis is also examined. Firstly, 90 corn samples are scanned using NIR spectrometers. Then, the original NIRS are processed with multiplicative scatter correction(MSC), Savitzky-Golay second derivative analysis and principal component analysis(PCA). Finally, the soft-sensing model for corn composition content is built using LS-SVR algorithm. The research results show that correlation coefficient (Rc) of NIRS calibrated and actual oil, protein and starch content measured by chemical method are 0.947, 0.969 and 0.948 respectively. It is proved that soft-sensing method has strong robustness for agricultural products.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127863143","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5195108
Du Zhaoping, Zhang Qingling, Li Gang, Qiao Aichun
The stability problem for singular networked control systems (NCSs) with time-varying delay is considered. Supposed that the sensor is clock-driven, the controller and actuator are event-driven, and the time-varying delay is less than one sampling period. Then, the considered system is modeled as discrete system with input delay. Based on Lyapunov stability theory and linear matrix inequality (LMI) technology, the stability criterion is derived, and the resultant state feedback controller is also given at the same time.
{"title":"Stability analysis for a class of singular networked control systems with time-varying delay","authors":"Du Zhaoping, Zhang Qingling, Li Gang, Qiao Aichun","doi":"10.1109/CCDC.2009.5195108","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5195108","url":null,"abstract":"The stability problem for singular networked control systems (NCSs) with time-varying delay is considered. Supposed that the sensor is clock-driven, the controller and actuator are event-driven, and the time-varying delay is less than one sampling period. Then, the considered system is modeled as discrete system with input delay. Based on Lyapunov stability theory and linear matrix inequality (LMI) technology, the stability criterion is derived, and the resultant state feedback controller is also given at the same time.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131304831","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5192316
Rui Zhang, Yuanwei Jing, Zhanshan Wang
In this paper, the global exponential stability is discussed for Cohen-Grossgerg neural network with time varying delays. On the basis of the linear matrix inequalities (LMIs) technique, and Lyapunov functional method combined with the Bellman inequality and Jensen inequality technique, we have obtained two main conditions to ensure the global exponential stability of the equilibrium point for this system, one of which is dependent on the change rate of time varying delays, and the other is dependent on the upper bound of time varying delays. The proposed results are less restrictive than those given in the earlier literatures, easier to check in practice, and suitable of the cases of slow or fast time varying delays. Remarks are made with other previous works to show the superiority of the obtained results, and the simulation examples are used to demonstrate the effectiveness of our results.
{"title":"Global exponential stability of Cohen-Grossberg neural network with time varying delays","authors":"Rui Zhang, Yuanwei Jing, Zhanshan Wang","doi":"10.1109/CCDC.2009.5192316","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5192316","url":null,"abstract":"In this paper, the global exponential stability is discussed for Cohen-Grossgerg neural network with time varying delays. On the basis of the linear matrix inequalities (LMIs) technique, and Lyapunov functional method combined with the Bellman inequality and Jensen inequality technique, we have obtained two main conditions to ensure the global exponential stability of the equilibrium point for this system, one of which is dependent on the change rate of time varying delays, and the other is dependent on the upper bound of time varying delays. The proposed results are less restrictive than those given in the earlier literatures, easier to check in practice, and suitable of the cases of slow or fast time varying delays. Remarks are made with other previous works to show the superiority of the obtained results, and the simulation examples are used to demonstrate the effectiveness of our results.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124188310","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5191803
Jinfang Zhang, Wei Wang, Jian-hang Zhang, G. Hou
A predictive control algorithm for probability density function (PDF) is presented based on the rational square-root B-spline based PDF model. The rational square-root PDF model is studied first, based on the analysis of the relationship between the pseudo weight and the actual weight, the rational square-root B-spline model can be easily set up; then the predictive model is deduced; a performance index is chosen next to design the predictive controller; and simulation study is performed for the molecular weight distribution (MWD) control of a styrene polymerization process to test the validity of the predictive control algorithm.
{"title":"Probability density function predictive control based on the rational square-root B-spline model","authors":"Jinfang Zhang, Wei Wang, Jian-hang Zhang, G. Hou","doi":"10.1109/CCDC.2009.5191803","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5191803","url":null,"abstract":"A predictive control algorithm for probability density function (PDF) is presented based on the rational square-root B-spline based PDF model. The rational square-root PDF model is studied first, based on the analysis of the relationship between the pseudo weight and the actual weight, the rational square-root B-spline model can be easily set up; then the predictive model is deduced; a performance index is chosen next to design the predictive controller; and simulation study is performed for the molecular weight distribution (MWD) control of a styrene polymerization process to test the validity of the predictive control algorithm.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124193524","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5195298
Lou Guo-huan, Wu Hongbin
This paper presents an improved fuzzy PID controller in order to improve the control performance for complex systems, in which the normal PID controller is not suitable in such case. By using genetic algorithm to optimize the fuzzy control rules, the proportional, integral and differential gains of the PID controller are tuned online. Experimental results show that this method is effective.
{"title":"Study of the fuzzy PID control based on genetic algorithm","authors":"Lou Guo-huan, Wu Hongbin","doi":"10.1109/CCDC.2009.5195298","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5195298","url":null,"abstract":"This paper presents an improved fuzzy PID controller in order to improve the control performance for complex systems, in which the normal PID controller is not suitable in such case. By using genetic algorithm to optimize the fuzzy control rules, the proportional, integral and differential gains of the PID controller are tuned online. Experimental results show that this method is effective.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124202912","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5194882
Jia Wang
Other than feedback linearization method used in 2 dimensional space, a new control strategy of multi-agent system in three dimensional space is proposed in this paper. Based on sliding mode control, artificial potentials are combined used in the control strategy. It can be widely adopted to deal with the nonlinear plant in three dimensional space, and used for tracking static or moving goals robustly with obstacles in circumstances. The stability of the control strategy is proven by choosing proper Lyapunov function and also illuminated by some simulations.
{"title":"Multi-agent system tracking using sliding mode control combined with artificial potential","authors":"Jia Wang","doi":"10.1109/CCDC.2009.5194882","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5194882","url":null,"abstract":"Other than feedback linearization method used in 2 dimensional space, a new control strategy of multi-agent system in three dimensional space is proposed in this paper. Based on sliding mode control, artificial potentials are combined used in the control strategy. It can be widely adopted to deal with the nonlinear plant in three dimensional space, and used for tracking static or moving goals robustly with obstacles in circumstances. The stability of the control strategy is proven by choosing proper Lyapunov function and also illuminated by some simulations.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124357716","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 : 2009-06-17DOI: 10.1109/CCDC.2009.5194964
Zhao Tongzhou, Wang Yanli, Wang Hai-hui, Gao Sheng, Song Hongxian
A face recognition method by using large and representative datasets is presented in this paper. The importance of research on face recognition is fueled by both its scientific challenges and its potential applications. In this contribution, we proposes several approaches to deal with some of the difficulties that one encounters when trying to recognize frontal faces in unconstrained domains and when only one sample per class is available to the learning system. It is possible for an automatic recognition system to compensate for imprecisely localized, partially expression variant faces even when only one single training sample per class is available. Finally, we have shown that the results of an appearance-based approach totally depend on the differences that exist between the facial expressions displayed on the learning and testing images.
{"title":"Face recognition method by using large and representative datasets","authors":"Zhao Tongzhou, Wang Yanli, Wang Hai-hui, Gao Sheng, Song Hongxian","doi":"10.1109/CCDC.2009.5194964","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5194964","url":null,"abstract":"A face recognition method by using large and representative datasets is presented in this paper. The importance of research on face recognition is fueled by both its scientific challenges and its potential applications. In this contribution, we proposes several approaches to deal with some of the difficulties that one encounters when trying to recognize frontal faces in unconstrained domains and when only one sample per class is available to the learning system. It is possible for an automatic recognition system to compensate for imprecisely localized, partially expression variant faces even when only one single training sample per class is available. Finally, we have shown that the results of an appearance-based approach totally depend on the differences that exist between the facial expressions displayed on the learning and testing images.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124364644","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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