ANFIS Controller with Fuzzy Subtractive Clustering Method to Reduce Coupling Effects in Twin Rotor MIMO System (TRMS) with Less Memory and Time Usage

In this paper, adaptive neural fuzzy inference system (ANFIS) and fuzzy subtractive clustering method (FSCM) were used to solve non-linearity, trajectory, and interaction problems of twin rotor MIMO system (TRMS). Basically, four fuzzy logic controllers (FLC) have been proposed to match the control...

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Bibliographic Details
Published in2009 International Conference on Advanced Computer Control pp. 19 - 23
Main Authors Mahmoud, T.S., Marhaban, M.H., Hong, T.S., Sokchoo Ng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2009
Subjects
ANFIS
Clustering methods
Control systems
Data mining
Fuzzy control
Fuzzy logic
Fuzzy Logic Control
Fuzzy Subtractive Clustering Method
Fuzzy systems
MATLAB
MIMO
Power capacitors
Transmission line measurements
Twin Rotor MIMO System (TRMS)
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Summary:In this paper, adaptive neural fuzzy inference system (ANFIS) and fuzzy subtractive clustering method (FSCM) were used to solve non-linearity, trajectory, and interaction problems of twin rotor MIMO system (TRMS). Basically, four fuzzy logic controllers (FLC) have been proposed to match the control objectives on TRMS. The four FLCs are considered as high consumers of memory and processing time relatively. New developed controllers are extracted to cope with these problems with less memory and time. Learning data were extracted from training the used conventional FLCs. Simulation results under MATLAB/Simulinkreg proved the improvement of response and simplicity of controller.
ISBN:9781424433308
076953516X
9780769535166
1424433304
DOI:10.1109/ICACC.2009.92