A method to solve the inverse problem of fuzzification of any nonlinear system

Author

Ramu, G. Venkata ; Ananthi, S. ; Padmanabhan, K.

Author_Institution

Instrum. Dept., Univ. of Madras, Chennai, India

fYear

2012

fDate

18-20 July 2012

Firstpage

394

Lastpage

398

Abstract

In this paper, the inverse problem of fixing the parameters of a fuzzy based inference system for a certain nonlinear function is described with a solution which is handled using the Adaptive Neuro fuzzy inference method. The description gives the exact procedure for doing this for any given nonlinearity of single or more variables. The program for this purpose is based on the existing functions available with MATLAB tool box for Fuzzy logic. The method will be applicable only for the Takagi Sugeno model and not for the Mamdani Model fuzzy system.

Keywords

adaptive control; fuzzy control; fuzzy logic; fuzzy reasoning; inverse problems; neurocontrollers; nonlinear control systems; MATLAB tool box; Mamdani model fuzzy system; Takagi Sugeno model; adaptive neuro fuzzy inference method; fuzzification inverse problem; fuzzy based inference system; fuzzy logic; nonlinear function; nonlinear system; Equations; Fuzzy logic; Input variables; Inverse problems; MATLAB; Mathematical model; Transfer functions; ANFIS; Fuzzification and Mamdani Model; Fuzzy Inference System; TSK Mode;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications (ICIEA), 2012 7th IEEE Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4577-2118-2

Type

conf

DOI

10.1109/ICIEA.2012.6360759

Filename

6360759