A multivariable inverse nonlinear control scheme is developed to decouple the strongly nonlinear double extraction steam turbo unit, improving the transient stability of the power and heating system. Computer simul...A multivariable inverse nonlinear control scheme is developed to decouple the strongly nonlinear double extraction steam turbo unit, improving the transient stability of the power and heating system. Computer simulation tests show that not only does the control scheme achieve satisfactory decoupling of the high and low pressure turbines and the electric power, remarkably improving the transient stability, but also the design is very intuitive and concise.展开更多
Ear recognition is a new kind of biometric identification technology now.Feature extraction is a key step in pattern recognition technology,which determines the accuracy of classification results.The method of single ...Ear recognition is a new kind of biometric identification technology now.Feature extraction is a key step in pattern recognition technology,which determines the accuracy of classification results.The method of single feature extraction can achieve high recognition rate under certain conditions,but the use of double feature extraction can overcome the limitation of single feature extraction.In order to improve the accuracy of classification results,this paper proposes a new method,that is,the method of complementary double feature extraction based on Principal Component Analysis(PCA)and Fisherface,and we apply it to human ear image recognition.The experiment was carried out on the ear image library provided by the University of Science and Technology Beijing.The results show that the ear recognition rate of the proposed method is significantly higher than the single feature extraction using PCA,Fisherface,or Independent component analysis(ICA)alone.展开更多
Due to higher demands on product diversity,flexible shift between productions of different products in one equipment becomes a popular solution,resulting in existence of multiple operation modes in a single process.In...Due to higher demands on product diversity,flexible shift between productions of different products in one equipment becomes a popular solution,resulting in existence of multiple operation modes in a single process.In order to handle such multi-mode process,a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode.In addition,both low and high order information are considered in each layer.The common and specific information within each mode can be captured and separated into several subspaces according to the different order information.The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman(TE)benchmark.Compared with previous methods,superiority of the proposed method is validated by the better monitoring results.展开更多
文摘A multivariable inverse nonlinear control scheme is developed to decouple the strongly nonlinear double extraction steam turbo unit, improving the transient stability of the power and heating system. Computer simulation tests show that not only does the control scheme achieve satisfactory decoupling of the high and low pressure turbines and the electric power, remarkably improving the transient stability, but also the design is very intuitive and concise.
基金National Key R&D Program of China(No:2019YFD0901605).
文摘Ear recognition is a new kind of biometric identification technology now.Feature extraction is a key step in pattern recognition technology,which determines the accuracy of classification results.The method of single feature extraction can achieve high recognition rate under certain conditions,but the use of double feature extraction can overcome the limitation of single feature extraction.In order to improve the accuracy of classification results,this paper proposes a new method,that is,the method of complementary double feature extraction based on Principal Component Analysis(PCA)and Fisherface,and we apply it to human ear image recognition.The experiment was carried out on the ear image library provided by the University of Science and Technology Beijing.The results show that the ear recognition rate of the proposed method is significantly higher than the single feature extraction using PCA,Fisherface,or Independent component analysis(ICA)alone.
基金the National Natural Science Foundation of China(61903352)China Postdoctoral Science Foundation(2020M671721)+4 种基金Zhejiang Province Natural Science Foundation of China(LQ19F030007)Natural Science Foundation of Jiangsu Province(BK20180594)Project of department of education of Zhejiang province(Y202044960)Project of Zhejiang Tongji Vocational College of Science and Technology(TRC1904)Foundation of Key Laboratory of Advanced Process Control for Light Industry(Jiangnan University),Ministry of Education,P.R.China,APCLI1803.
文摘Due to higher demands on product diversity,flexible shift between productions of different products in one equipment becomes a popular solution,resulting in existence of multiple operation modes in a single process.In order to handle such multi-mode process,a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode.In addition,both low and high order information are considered in each layer.The common and specific information within each mode can be captured and separated into several subspaces according to the different order information.The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman(TE)benchmark.Compared with previous methods,superiority of the proposed method is validated by the better monitoring results.
