In this paper, parameter of ADRC for spacecraft attitude maneuvering is optimizated. Nonlinear dynamics model of spacecraft attitude describes attitude motion. Particle Swarm Optimization Algorithm is used for parameter optimization of ADRC. The controller index which describes attitude adjustment capacity of three axes is designed. The influence of controller parameter is quantifiable on the control performance. The selection of parameter based on traditonal experience is avoided. Simulation results show that: the particle swarm optimization algorithm for system updates through the position and velocity. The system can quickly converge to the global optimal solution, and the parameter of ADRC is optimized.
{"title":"Parameter Optimization of ADRC for Spacecraft Attitude Maneuver Based on Particle Swarm Optimization Algorithm","authors":"Ping Wang, Hua Wang, Guoyu Bai, Lin Su","doi":"10.1109/IHMSC.2014.149","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.149","url":null,"abstract":"In this paper, parameter of ADRC for spacecraft attitude maneuvering is optimizated. Nonlinear dynamics model of spacecraft attitude describes attitude motion. Particle Swarm Optimization Algorithm is used for parameter optimization of ADRC. The controller index which describes attitude adjustment capacity of three axes is designed. The influence of controller parameter is quantifiable on the control performance. The selection of parameter based on traditonal experience is avoided. Simulation results show that: the particle swarm optimization algorithm for system updates through the position and velocity. The system can quickly converge to the global optimal solution, and the parameter of ADRC is optimized.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115520657","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}
In recent years, with the rapid development of the Internet on a global scale and the prompt popularization of various App applications, the Internet is increasingly becoming an integral part of people's lives. Meanwhile various network problems caused by abnormal network behavior have become more prominent than any time before. Furthermore we also have a lot of personal information on the Internet, which will bring us significant losses if are gave away. For that, to find an effective method to detect the abnormal network behavior is becoming more and more important. This paper first introduces a new detection method based on compound session, and then shows the effectiveness of the proposed method. A further objective of this method is to identify the infected host.
{"title":"An Abnormal Network Behavior Detection System Based on Compound Session","authors":"Gang He, Xiaochen Liu, Xiaochun Wu, Dechen Yu","doi":"10.1109/IHMSC.2014.111","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.111","url":null,"abstract":"In recent years, with the rapid development of the Internet on a global scale and the prompt popularization of various App applications, the Internet is increasingly becoming an integral part of people's lives. Meanwhile various network problems caused by abnormal network behavior have become more prominent than any time before. Furthermore we also have a lot of personal information on the Internet, which will bring us significant losses if are gave away. For that, to find an effective method to detect the abnormal network behavior is becoming more and more important. This paper first introduces a new detection method based on compound session, and then shows the effectiveness of the proposed method. A further objective of this method is to identify the infected host.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124118913","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}
A new search algorithm for phased array radar which is based on radio frequency stealth is proposed in this paper. When there is no indication information, parameters including the dwelling time and the average power are optimized by sequential quadratic programming (SQP), and a minimum energy cost model is set up by using Grey Relational Grade (GRG). The surveillance area is divided into several subareas according to the elevation angle. The radar can radiate adaptively according to the different priorities. Compared with other search algorithms, the simulation results show that our algorithm can consume less energy and provide better performance in term of radio frequency stealth and detection.
{"title":"Optimal Search Algorithm for Phased Array Radar without Indication Information","authors":"Zhenkai Zhang, Jiehao Zhu, Hailin Li","doi":"10.1109/IHMSC.2014.85","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.85","url":null,"abstract":"A new search algorithm for phased array radar which is based on radio frequency stealth is proposed in this paper. When there is no indication information, parameters including the dwelling time and the average power are optimized by sequential quadratic programming (SQP), and a minimum energy cost model is set up by using Grey Relational Grade (GRG). The surveillance area is divided into several subareas according to the elevation angle. The radar can radiate adaptively according to the different priorities. Compared with other search algorithms, the simulation results show that our algorithm can consume less energy and provide better performance in term of radio frequency stealth and detection.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124187480","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}
Combustion process in utility boiler is very complicated and not fully understood until now. One operating challenge in boiler operation is the unreliable oxygen sensor could result in flame extinction of burners. An on-line virtual sensor is desirable for the unreliable oxygen sensor. This work elaborates how to build a Neural Network-based oxygen virtual sensor by make full use of the mass data available in DCS and prior knowledge for selecting model inputs. The framework can be easily transplanted to other similar applications.
{"title":"Application of Neural Network as Oxygen Virtual Sensor in Utility Boiler","authors":"Honggang Wang, Xu Fu, Yuyang Zhou","doi":"10.1109/IHMSC.2014.82","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.82","url":null,"abstract":"Combustion process in utility boiler is very complicated and not fully understood until now. One operating challenge in boiler operation is the unreliable oxygen sensor could result in flame extinction of burners. An on-line virtual sensor is desirable for the unreliable oxygen sensor. This work elaborates how to build a Neural Network-based oxygen virtual sensor by make full use of the mass data available in DCS and prior knowledge for selecting model inputs. The framework can be easily transplanted to other similar applications.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"151 5-6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124353345","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}
In order to realize movement target detection and tracking, the sonar image sequence movement target detection based on Surfacelet transform at complex background is proposed. Firstly, sonar image characteristic area extract based on Surfacelet transform, secondly, extract characteristic quantities and confirm correspondence between frames of characteristic quantities, at last, calculate motion parameters and put into motion model to estimate the entire image motion vectors, and complete the moving object detection. The experiments show that the method can complete to extract movement targets correctly.
{"title":"The Sonar Image Sequence Movement Target Detection Based on Surfacelet Transform at Complex Background","authors":"C. Tang, Dan-dan Liu, Ao Li","doi":"10.1109/IHMSC.2014.162","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.162","url":null,"abstract":"In order to realize movement target detection and tracking, the sonar image sequence movement target detection based on Surfacelet transform at complex background is proposed. Firstly, sonar image characteristic area extract based on Surfacelet transform, secondly, extract characteristic quantities and confirm correspondence between frames of characteristic quantities, at last, calculate motion parameters and put into motion model to estimate the entire image motion vectors, and complete the moving object detection. The experiments show that the method can complete to extract movement targets correctly.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114742370","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}
In the past few years, the network is an essential part in human's life. More and more people choose shopping, chatting and video online. All the online activities produce tons of data which contain our behavior characteristics. Traditional data analyses just focus on one kind of feature, while they neglect the behavior information generated by merging multiple features. Based on the basic data set, this paper provides a new method for analyzing data, called Compound Session. After acquiring the Compound Session data, we continue to process data from the perspective of enterprise user and produce three types of analysis tables. Due to huge amounts of data from more than two thousand enterprises, we propose to process data on the cloud computing platform called Hadoop.
{"title":"Analysis of Enterprise User Behavior on Hadoop","authors":"Gang He, Siying Ren, Dechen Yu, Xiaochun Wu","doi":"10.1109/IHMSC.2014.158","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.158","url":null,"abstract":"In the past few years, the network is an essential part in human's life. More and more people choose shopping, chatting and video online. All the online activities produce tons of data which contain our behavior characteristics. Traditional data analyses just focus on one kind of feature, while they neglect the behavior information generated by merging multiple features. Based on the basic data set, this paper provides a new method for analyzing data, called Compound Session. After acquiring the Compound Session data, we continue to process data from the perspective of enterprise user and produce three types of analysis tables. Due to huge amounts of data from more than two thousand enterprises, we propose to process data on the cloud computing platform called Hadoop.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114758820","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 increasing development of satellite remote sensing technology has provided a large amount of cheap and stable data sources for land cover/use observations. In mountainous area, it is usually to cloud-contained remote sensing images because of complex weather. Therefore, how to get land cover/use thematic maps in mountainous areas is a challenging topic. In this paper, an approach of classification for cloud-contained areas is proposed. The overall idea is described as follows. Firstly, investigate the variances between cloud cover areas and underlying surfaces, design classification methods with SVM, and implement precise detection of cloud cover areas. Secondly, use Kriging interpolation to build image inpainting models with time series landuse classification results. According to time series analysis theories, Kriging interpolation algorithm to enhance the precision in cloudcontained area will be built. Lastly, select a specific area and utilize domestic remote sensing images to test the feasibility and robustness of the proposed method and adjust model parameters.
{"title":"Land Use/Cover Classification of Cloud-Contaminated Area by Multitemporal Remote Sensing Images","authors":"Shaohong Shen, Xiaocong Mo, Zhang Qian","doi":"10.1109/IHMSC.2014.46","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.46","url":null,"abstract":"The increasing development of satellite remote sensing technology has provided a large amount of cheap and stable data sources for land cover/use observations. In mountainous area, it is usually to cloud-contained remote sensing images because of complex weather. Therefore, how to get land cover/use thematic maps in mountainous areas is a challenging topic. In this paper, an approach of classification for cloud-contained areas is proposed. The overall idea is described as follows. Firstly, investigate the variances between cloud cover areas and underlying surfaces, design classification methods with SVM, and implement precise detection of cloud cover areas. Secondly, use Kriging interpolation to build image inpainting models with time series landuse classification results. According to time series analysis theories, Kriging interpolation algorithm to enhance the precision in cloudcontained area will be built. Lastly, select a specific area and utilize domestic remote sensing images to test the feasibility and robustness of the proposed method and adjust model parameters.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114381581","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}
To decrease the influence of friction on torque tracking accuracy and improve the rapidity of system response when load simulator works at low frequency and low speed, a novel method based on fuzzy neural network (FNN) PID controller and friction torque compensation is put forward. The FNN PID consists of FNN and neural network (NN) PID. The parameters of the controller were optimized by the mixed learning method integrating of offline genetic algorithm (GA) and online error back propagation (BP) algorithm. The friction torque model is identified by LuGre model. The loading motor is a double-stator motor in which the outer stator system serves as compensating the friction torque and the inner stator system as loading torque. Simulation results show that the control system has good dynamic and static performance.
{"title":"Research on the Fuzzy Neural Network PID Control of Load Simulator Based on Friction Torque Compensation","authors":"Zhisheng Ni, Mingyan Wang","doi":"10.1109/IHMSC.2014.78","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.78","url":null,"abstract":"To decrease the influence of friction on torque tracking accuracy and improve the rapidity of system response when load simulator works at low frequency and low speed, a novel method based on fuzzy neural network (FNN) PID controller and friction torque compensation is put forward. The FNN PID consists of FNN and neural network (NN) PID. The parameters of the controller were optimized by the mixed learning method integrating of offline genetic algorithm (GA) and online error back propagation (BP) algorithm. The friction torque model is identified by LuGre model. The loading motor is a double-stator motor in which the outer stator system serves as compensating the friction torque and the inner stator system as loading torque. Simulation results show that the control system has good dynamic and static performance.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114950061","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}
Customer knowledge management emphasizes collecting, storage, analysis and use of customer knowledge. This is closely related to customer relationship management. This paper, by analyzing the connection between the customer relationship management and customer knowledge management, constructs the model of customer knowledge management based on CRM, to help enterprises to track the whole process of knowledge from produce to be used, so as to provide service for making the decision, and have a guiding significance to establish a perfect customer relationship management system.
{"title":"Research on Customer Knowledge Management Based on CRM","authors":"Guoao Xu","doi":"10.1109/IHMSC.2014.59","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.59","url":null,"abstract":"Customer knowledge management emphasizes collecting, storage, analysis and use of customer knowledge. This is closely related to customer relationship management. This paper, by analyzing the connection between the customer relationship management and customer knowledge management, constructs the model of customer knowledge management based on CRM, to help enterprises to track the whole process of knowledge from produce to be used, so as to provide service for making the decision, and have a guiding significance to establish a perfect customer relationship management system.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123597092","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}
With the information demand increasing, the method which based on Nyquist sampling is expensive and low efficiency in ultra wideband signal processing. To extract before transmission data storage can cause a lot of waste resources. Compressive Sensing can make sampling and compression at the same time. The sampling frequency is far less than the Nyquist sampling frequency as long as the signal is sparse in a domain. It can deal with discrete signal directly and take a few values for processing from n dimension discrete signal. Some algorithm is used to recover on the receiving-end. A compressive Sensing method is proposed in this paper to reduce the requirement of the system in sampling rate. Firstly, the CS basic theory is introduced and three key technologies are summarized: sparse representation of signals, the design of the measurement matrix, compressive sensing reconstruction algorithm. Then the application of compressive sensing technology in specific areas is introduced.
{"title":"Analysis in Theory and Technology Application of Compressive Sensing","authors":"Jin Jiang, Changxing Chen","doi":"10.1109/IHMSC.2014.53","DOIUrl":"https://doi.org/10.1109/IHMSC.2014.53","url":null,"abstract":"With the information demand increasing, the method which based on Nyquist sampling is expensive and low efficiency in ultra wideband signal processing. To extract before transmission data storage can cause a lot of waste resources. Compressive Sensing can make sampling and compression at the same time. The sampling frequency is far less than the Nyquist sampling frequency as long as the signal is sparse in a domain. It can deal with discrete signal directly and take a few values for processing from n dimension discrete signal. Some algorithm is used to recover on the receiving-end. A compressive Sensing method is proposed in this paper to reduce the requirement of the system in sampling rate. Firstly, the CS basic theory is introduced and three key technologies are summarized: sparse representation of signals, the design of the measurement matrix, compressive sensing reconstruction algorithm. Then the application of compressive sensing technology in specific areas is introduced.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116803559","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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