文献类型：期刊文献

英文题名：Embedded Interval Type-2 T-S Fuzzy Time/Space Separation Modeling Approach for Nonlinear Distributed Parameter System

作者：Wang, Mengling[1,2,3];Li, Ning[2,3];Li, Shaoyuan[2,3];Shi, Hongbo[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China;[3]Minist Educ, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China

年份：2011

卷号：50

期号：24

起止页码：13954

外文期刊名：INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

收录：;EI(收录号：20115114619279);WOS:【SCI-EXPANDED(收录号:WOS:000297946400044)】；

基金：This work was supported by the National Nature Science Foundation of China (Nos. 60825302, 61074079, 61074061), the High Technology Research and Development Program of China (No.2007AA041403), the Program of Shanghai Subject Chief Scientist, and 'Shu Guang' Project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation.

语种：英文

外文关键词：Nonlinear equations - Functions - Separation

摘要：Challenging modeling problems include how to obtain a simple and accurate model for a partial differential equation (PDE) unknown nonlinear distributed parameter system (DPS). In this paper, a time/space separation modeling approach based on the interval type-2 T-S fuzzy model (IT2 T-S model) is proposed for nonlinear DPS. First, the spatial-temporal output is divided into a few dominant spatial basis functions and low-dimensional time series by a linear time/space separation method. Second, the interval type-2 T-S fuzzy model is determined from the low-dimensional time series to reconstruct the system dynamics through the spatial basis functions. As the IT2 T-S model employs an interval linear model in the consequent part, the relationship between the input and spatial output can be determined by linear expressions through type reduction and linear time/space reconstruction. Thus, the obtained model is suitable for control design. The simulation presents the accuracies and effectiveness of the proposed modeling methodologies.