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学科=自动化与计算机技术—控制科学与工程

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Sequential fusion estimation for multisensor systems with non-Gaussian noises被引量：2: 《Science China(Information Sciences)》2020年第12期149-161,共13页Liping YAN Chenying DI Q.M.Jonathan WU Yuanqing XIA; supported by Beijing Natural Science Foundation(Grant No.4202071)。; The sequential fusion estimation for multisensor systems disturbed by non-Gaussian but heavytailed noises is studied in this paper.Based on multivariate t-distribution and the approximate t-filter,the sequential fusio...; 关键词：state estimation sequential fusion non-Gaussian disturbance heavy-tailed noise multivariate t-distribution

Multi-objective PID control for non-Gaussian stochastic distribution system based on two-step intelligent models被引量：3: 《Science in China(Series F)》2009年第10期1754-1765,共12页YI Yang ZHANG TianPing GUO Lei; Supported by the National Natural Science Foundation of China (Grant Nos. 60774013, 60874045, 60904030); A new method for controlling the shape of the conditional output probability density function （PDF） for general nonlinear dynamic stochastic systems is proposed based on B-spline neural network （NN） model and T-S ...; 关键词：probability density function non-Gaussian stochastic systems PID controller B-spline NN L1 performance index T-S fuzzy model

Statistic PID Tracking Control for Non-Gaussian Stochastic Systems Based on T-S Fuzzy Model被引量：3: 《International Journal of Automation and computing》2009年第1期81-87,共7页Yang Yi Hong Shen Lei Gu; supported by National Natural Science Foundationof China (No. 60472065, No. 60774013).; A new robust proportional-integral-derivative （PID） tracking control framework is considered for stochastic systems with non-Gaussian variable based on B-spline neural network approximation and T-S fuzzy model ident...; 关键词：Non-Gaussian systems probability density function statistic tracking control T-S fuzzy model proportional-integralderivative control.

Batch process monitoring based on multilevel ICA-PCA被引量：3: 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2008年第8期1061-1069,共9页Zhi-qiang GE Zhi-huan SONG; Project (No. 60774067) supported by the National Natural ScienceFoundation of China; In this paper, we describe a new batch process monitoring method based on multilevel independent component analysis and principal component analysis (MLICA-PCA). Unlike the conventional multi-way principal component a...; 关键词：MULTILEVEL Independent component analysis （ICA） Principal component analysis （PCA） Batch process monitoring NON-GAUSSIAN

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