DocumentCode :
2652020
Title :
ANFIS Controller with Fuzzy Subtractive Clustering Method to Reduce Coupling Effects in Twin Rotor MIMO System (TRMS) with Less Memory and Time Usage
Author :
Mahmoud, Thair Sh ; Marhaban, Mohammed H. ; Hong, Tang S. ; Ng, Sokchoo
Author_Institution :
Dept. of Electr. & Electron. Eng., UPM, Serdang
fYear :
2009
fDate :
22-24 Jan. 2009
Firstpage :
19
Lastpage :
23
Abstract :
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.
Keywords :
MIMO systems; adaptive control; control nonlinearities; fuzzy control; fuzzy reasoning; machine control; mathematics computing; neurocontrollers; pattern clustering; position control; rotors; ANFIS controller; MATLAB-Simulink; adaptive neural fuzzy inference system; fuzzy logic controllers; fuzzy subtractive clustering method; twin rotor MIMO system; Clustering methods; Control systems; Data mining; Fuzzy control; Fuzzy logic; Fuzzy systems; MATLAB; MIMO; Power capacitors; Transmission line measurements; ANFIS; Fuzzy Logic Control; Fuzzy Subtractive Clustering Method; Twin Rotor MIMO System (TRMS);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Control, 2009. ICACC '09. International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-3330-8
Type :
conf
DOI :
10.1109/ICACC.2009.92
Filename :
4777302
Link To Document :
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