Title :
Online Multivariable Identification of a MIMO Distillation Column Using Evolving Takagi-Sugeno Fuzzy Model
Author :
Borhan, Molazem Sanandaji ; Karim, Salahshoor
Author_Institution :
Pet. Univ. of Technol., Tehran
Abstract :
In this paper, an evolving Takagi-Sugeno (eTS) fuzzy model has been utilized for online identification of a multi-input, multi-output (MIMO) distillation column. In this approach, the rule-base structure and the model parameters of the consequent parts of fuzzy IF-THEN rules gradually evolve during the online identification process. In addition, an exponential time-varying weight is included in the original rule generation condition in order to control the rate of rule generation at the start of the training process and consequently reduce the total number of generated rules in comparison with the original MIMO eTS algorithm. Recursive-Least Squares (RLS) algorithm is employed to estimate the consequent part of each rule. The results show that the modified condition reduces the total number of generated rules for a certain data set with lower RMSE error in comparison with the original eTS method. ,
Keywords :
distillation equipment; fuzzy set theory; fuzzy systems; identification; least squares approximations; mean square error methods; recursive estimation; MIMO distillation column; MIMO eTS algorithm; RMSE error; Takagi-Sugeno fuzzy model; exponential time-varying weight; fuzzy IF-THEN rules; online multivariable identification; recursive-least squares algorithm; rule generation condition; rule-base structure; training process; Automation; Distillation equipment; Fuzzy control; Fuzzy sets; Fuzzy systems; Input variables; MIMO; Nonlinear systems; Resonance light scattering; Takagi-Sugeno model; Distillation Column; Evolving Takagi-sugeno; Fuzzy Systems; Systen Identification;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4347522
