Pub Date : 2010-06-15DOI: 10.1109/ICIEA.2010.5514937
Chia-Hung Wang, Tzu-lun Hung, T. Sun
The drawback in using the light emitting diode as a light source is that its light output power is highly temperature dependent. This paper puts forth the novel idea of neglecting the photo diode as a luminance sensor and taking advantage of pulse-width modulation at the same time. A light emitting diode power controller based on automatic power control technology is introduced. The controller can reduce the power dependence of the electrical component on temperature and regulate light emitting diode brightness according to the pulse-width modulation. In this way, the current flowing through the electrical component can be switched off to reduce the power consumption and to prevent electrical component over heating. Finally, the comparisons between voltage source with ballast resistor, automatic current control and proposed photo-power control are discussed in this paper. All these three compensated mechanisms are without photodiode. The experimental results show the proposed method is effective in providing constant luminous intensity.
{"title":"PWM photo-power control for light-emitting diode lighting system without photo-diode detection","authors":"Chia-Hung Wang, Tzu-lun Hung, T. Sun","doi":"10.1109/ICIEA.2010.5514937","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5514937","url":null,"abstract":"The drawback in using the light emitting diode as a light source is that its light output power is highly temperature dependent. This paper puts forth the novel idea of neglecting the photo diode as a luminance sensor and taking advantage of pulse-width modulation at the same time. A light emitting diode power controller based on automatic power control technology is introduced. The controller can reduce the power dependence of the electrical component on temperature and regulate light emitting diode brightness according to the pulse-width modulation. In this way, the current flowing through the electrical component can be switched off to reduce the power consumption and to prevent electrical component over heating. Finally, the comparisons between voltage source with ballast resistor, automatic current control and proposed photo-power control are discussed in this paper. All these three compensated mechanisms are without photodiode. The experimental results show the proposed method is effective in providing constant luminous intensity.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"201202 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123357733","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5516640
Wang Yunzhi, Hu Yaoguang, Jia Yanhua, Zhang Ruijun
In view of the common issue of product-mix resource allocation decision under limited manufacturing resource, this article proposes a new approach based on game theory. Firstly, a quantification method is applied to represent the utility of manufacturing resource and strategy profile, and then a multi-dimension game model is presented using these quantified manufacturing data as element of game theory. By solving the game model, the Nash equilibrium solution is regarded as optimal resource allocation strategy. The goal of the solution is to maximize the individual profit of each product. The desired equilibrium will meet the requirements for resource by the greatest degree to make each product achieve optimal production status, simultaneously the enterprise will get higher rate of return on investment.
{"title":"A game theoretic approach to product-mix resource allocation","authors":"Wang Yunzhi, Hu Yaoguang, Jia Yanhua, Zhang Ruijun","doi":"10.1109/ICIEA.2010.5516640","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5516640","url":null,"abstract":"In view of the common issue of product-mix resource allocation decision under limited manufacturing resource, this article proposes a new approach based on game theory. Firstly, a quantification method is applied to represent the utility of manufacturing resource and strategy profile, and then a multi-dimension game model is presented using these quantified manufacturing data as element of game theory. By solving the game model, the Nash equilibrium solution is regarded as optimal resource allocation strategy. The goal of the solution is to maximize the individual profit of each product. The desired equilibrium will meet the requirements for resource by the greatest degree to make each product achieve optimal production status, simultaneously the enterprise will get higher rate of return on investment.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"498 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123061083","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5514820
R. Xie, Xinmin Wang, Yan Li, Kairui Zhao
As the iterations are much, and the adjustment speed is slow, the improvements are made to the standard BP neural network algorithm. The momentum term of the weight adjustment rule is improved, make the weight adjustment speed more quicker and the weight adjustment process more smoother. The simulation of a concrete example shows that the iterations of the improved BP neural network algorithm can be calculated and compared. Finally, choosing a certain type of airplane as the controlled object, the improved BP neural network algorithm is used to design the control law for control command tracking, the simulation results show that the improved BP neural network algorithm can realize quicker convergence rate and better tracking accuracy.
{"title":"Research and application on improved BP neural network algorithm","authors":"R. Xie, Xinmin Wang, Yan Li, Kairui Zhao","doi":"10.1109/ICIEA.2010.5514820","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5514820","url":null,"abstract":"As the iterations are much, and the adjustment speed is slow, the improvements are made to the standard BP neural network algorithm. The momentum term of the weight adjustment rule is improved, make the weight adjustment speed more quicker and the weight adjustment process more smoother. The simulation of a concrete example shows that the iterations of the improved BP neural network algorithm can be calculated and compared. Finally, choosing a certain type of airplane as the controlled object, the improved BP neural network algorithm is used to design the control law for control command tracking, the simulation results show that the improved BP neural network algorithm can realize quicker convergence rate and better tracking accuracy.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121769942","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5516944
Huixin Chen, Xin-wei Wang, Chun-Li Liu, Fang Wen, R. Ruan
In this paper the modeling and simulation of a class of discrete-time stochastic bilinear systems are studied, the extended least squares (ELS) algorithm are used to estimate unknown parameters of the system, and two simulation examples show that the ELS algorithms of the modeling and simulation are effective for discrete-time stochastic bilinear systems with correlated noises and unknown parameters. The ELS algorithm is applied to adaptive tracking of a class of the systems and two simulation examples of the adaptive tracking are presented to show that the proposed adaptive tracking algorithm is of the good performance.
{"title":"Modeling and simulation of a class of stochastic bilinear systems","authors":"Huixin Chen, Xin-wei Wang, Chun-Li Liu, Fang Wen, R. Ruan","doi":"10.1109/ICIEA.2010.5516944","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5516944","url":null,"abstract":"In this paper the modeling and simulation of a class of discrete-time stochastic bilinear systems are studied, the extended least squares (ELS) algorithm are used to estimate unknown parameters of the system, and two simulation examples show that the ELS algorithms of the modeling and simulation are effective for discrete-time stochastic bilinear systems with correlated noises and unknown parameters. The ELS algorithm is applied to adaptive tracking of a class of the systems and two simulation examples of the adaptive tracking are presented to show that the proposed adaptive tracking algorithm is of the good performance.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123889383","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5514901
T. Chern, P. Pan, Yu-Lun Chern, D. Tsay
This paper presents a brushless DC motor (BLDCM) control system that does not require Hall sensor and speed encoder for an air conditioner fan motor. Using low cost circuits, the zero-crossing points are detected to estimate the commutated timing and speed information. Hall element shortcoming can therefore be eliminated. A modified six-step square wave pattern with pulse-width modulation is developed to simplify the conventional coordinate transformations technique. To verify the proposed method, a prototype fan motor controller is constructed and tested. Experimental results show that the proposed method has high efficiency and good performance.
{"title":"Sensorless speed control of BLDC motor using six step square wave and rotor position detection","authors":"T. Chern, P. Pan, Yu-Lun Chern, D. Tsay","doi":"10.1109/ICIEA.2010.5514901","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5514901","url":null,"abstract":"This paper presents a brushless DC motor (BLDCM) control system that does not require Hall sensor and speed encoder for an air conditioner fan motor. Using low cost circuits, the zero-crossing points are detected to estimate the commutated timing and speed information. Hall element shortcoming can therefore be eliminated. A modified six-step square wave pattern with pulse-width modulation is developed to simplify the conventional coordinate transformations technique. To verify the proposed method, a prototype fan motor controller is constructed and tested. Experimental results show that the proposed method has high efficiency and good performance.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126282149","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5515902
Xuefei Mao, Shao-de Zhang, Xueqin Mao
The paper works out an online self-learning control plant for multiple support vector machine inverse control. The multiple support vector machine model applies subtractive clustering algorithm by which the input space is divided into several small local spaces. By means of least squares support vector machine, the sub-models are established. The prediction output of each sub-model is connected by principal components regression method so that identification of the inverse dynamics model of the system is achieved. Combining inverse model of the system as a system controller with the controlled plant, a SVM direct inverse control system is constituted. In order to overcome the influence of inverse model identification error, a SVM direct inverse control system with the PID compensation is designed in the paper. The simulation research proves that the control strategy can provide the system with good tracking performance, resistance to interference and a better robustness.
{"title":"A design of inverse control system based on multiple support vector machine","authors":"Xuefei Mao, Shao-de Zhang, Xueqin Mao","doi":"10.1109/ICIEA.2010.5515902","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5515902","url":null,"abstract":"The paper works out an online self-learning control plant for multiple support vector machine inverse control. The multiple support vector machine model applies subtractive clustering algorithm by which the input space is divided into several small local spaces. By means of least squares support vector machine, the sub-models are established. The prediction output of each sub-model is connected by principal components regression method so that identification of the inverse dynamics model of the system is achieved. Combining inverse model of the system as a system controller with the controlled plant, a SVM direct inverse control system is constituted. In order to overcome the influence of inverse model identification error, a SVM direct inverse control system with the PID compensation is designed in the paper. The simulation research proves that the control strategy can provide the system with good tracking performance, resistance to interference and a better robustness.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125781474","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5517024
Cher Ming Tan, K. See, Jun-Wu Zhang, Mingjie Xu, C. Boon, K. Yeo, M. Do
Electrical energy is vital to our daily activities. However, energy cost is increasing while much energy is being wasted into the environment. If we can capture these wasted energies, efficiency of energy utilization will be enhanced, and this is the idea of energy harvesting.
{"title":"A possible reality on battery-less low-power portable electronics","authors":"Cher Ming Tan, K. See, Jun-Wu Zhang, Mingjie Xu, C. Boon, K. Yeo, M. Do","doi":"10.1109/ICIEA.2010.5517024","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5517024","url":null,"abstract":"Electrical energy is vital to our daily activities. However, energy cost is increasing while much energy is being wasted into the environment. If we can capture these wasted energies, efficiency of energy utilization will be enhanced, and this is the idea of energy harvesting.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125871225","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5515097
Liang Ma, Wang Ran, T. Zheng
This paper presents mathematical modeling procedure of three-phase grid-connected photovoltaic inverter. It presents synchronous PI current control strategy and the method for adjuster design. The typical waveforms of grid voltage, grid current and harmonics of grid current are carried out on a 100kW photovoltaic inverter, which can provide some guidelines for engineers to analyze, design and implement.
{"title":"Modeling and control of 100kW three-phase grid-connected photovoltaic inverter","authors":"Liang Ma, Wang Ran, T. Zheng","doi":"10.1109/ICIEA.2010.5515097","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5515097","url":null,"abstract":"This paper presents mathematical modeling procedure of three-phase grid-connected photovoltaic inverter. It presents synchronous PI current control strategy and the method for adjuster design. The typical waveforms of grid voltage, grid current and harmonics of grid current are carried out on a 100kW photovoltaic inverter, which can provide some guidelines for engineers to analyze, design and implement.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129300612","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5516852
K. Xi, Yan Tang, Jiankun Hu, F. Han
In this paper, we investigate face recognition based access control approaches dedicatedly designed for camera-equipped mobile devices. We developed a Hierarchical Correlation based Face Verification (HCFV) scheme which is deployable for the most resource constrained mobile devices such as low-end mobile phones with available memory size less than 1MB. The novelty of HCFV is to perform the Partial Correlation Output Peak Analysis (analyze the relations among multiple cross-correlation peaks which are generated from selected sub-regions of a face). The experimental results on the public domain database Yale Face Database demonstrate that the proposed scheme has achieved better performance than using conventional correlation based schemes directly on either full-size or downsized images. Furthermore, in order to investigate the applicability and implementability issues, we have also implemented HCFV on the Nokia S60 CLDC emulator using Java ME programming technology. The experiment shows that HFVC consumes approximately 1/10 memory, 1/6 storage space, and 3.5% processing time in comparison with the result using the conventional correlation methods.
{"title":"A correlation based face verification scheme designed for mobile device access control: From algorithm to Java ME implementation","authors":"K. Xi, Yan Tang, Jiankun Hu, F. Han","doi":"10.1109/ICIEA.2010.5516852","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5516852","url":null,"abstract":"In this paper, we investigate face recognition based access control approaches dedicatedly designed for camera-equipped mobile devices. We developed a Hierarchical Correlation based Face Verification (HCFV) scheme which is deployable for the most resource constrained mobile devices such as low-end mobile phones with available memory size less than 1MB. The novelty of HCFV is to perform the Partial Correlation Output Peak Analysis (analyze the relations among multiple cross-correlation peaks which are generated from selected sub-regions of a face). The experimental results on the public domain database Yale Face Database demonstrate that the proposed scheme has achieved better performance than using conventional correlation based schemes directly on either full-size or downsized images. Furthermore, in order to investigate the applicability and implementability issues, we have also implemented HCFV on the Nokia S60 CLDC emulator using Java ME programming technology. The experiment shows that HFVC consumes approximately 1/10 memory, 1/6 storage space, and 3.5% processing time in comparison with the result using the conventional correlation methods.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129292601","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 : 2010-06-15DOI: 10.1109/ICIEA.2010.5516872
M. Ghahramani, H. L. Wang, W. Yau, E. Teoh
All family members resemble each other in different ways which is recognizable by our brain. In this paper, we have developed family classification using AdaBoost, Support Vector Machines and K-Nearest Neighbor classifiers with different patches of training data. In some cases family classification involve unseen data classification in which the classifiers' performance drop significantly. Therefore Mixture of Experts is conducted to improve their performance. To have a fair comparison of mentioned approaches 3 different families from 3 different ethnic groups are used. Experimental results show that we can achieve an average accuracy rate of 76 percent and up to 27 percent accuracy improvement by using majority voting of mixture of experts depending on the family data.
{"title":"Unseen family member classification using mixture of experts","authors":"M. Ghahramani, H. L. Wang, W. Yau, E. Teoh","doi":"10.1109/ICIEA.2010.5516872","DOIUrl":"https://doi.org/10.1109/ICIEA.2010.5516872","url":null,"abstract":"All family members resemble each other in different ways which is recognizable by our brain. In this paper, we have developed family classification using AdaBoost, Support Vector Machines and K-Nearest Neighbor classifiers with different patches of training data. In some cases family classification involve unseen data classification in which the classifiers' performance drop significantly. Therefore Mixture of Experts is conducted to improve their performance. To have a fair comparison of mentioned approaches 3 different families from 3 different ethnic groups are used. Experimental results show that we can achieve an average accuracy rate of 76 percent and up to 27 percent accuracy improvement by using majority voting of mixture of experts depending on the family data.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129704064","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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