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  Adaptive Neuro-Fuzzy Inference System based control of six DOF robot manipulator
 
 
Titel: Adaptive Neuro-Fuzzy Inference System based control of six DOF robot manipulator
Auteur: Srinivasan Alavandar
M. J. Nigam
Verschenen in: Journal of engineering science and technology review
Paginering: Jaargang 1 (2008) nr. 1 pagina's 106-111
Jaar: 2008
Inhoud: The dynamics of robot manipulators are highly nonlinear with strong couplings existing between joints and are frequently subjected to structured and unstructured uncertainties. Fuzzy Logic Controller can very well describe the desired system behavior with simple “if-then” relations owing the designer to derive “if-then” rules manually by trial and error. On the other hand, Neural Networks perform function approximation of a system but cannot interpret the solution obtained neither check if its solution is plausible. The two approaches are complementary. Combining them, Neural Networks will allow learning capability while Fuzzy-Logic will bring knowledge representation (Neuro-Fuzzy). This paper presents the control of six degrees of freedom robot arm (PUMA Robot) using Adaptive Neuro Fuzzy Inference System (ANFIS) based PD plus I controller. Numerical simulation using the dynamic model of six DOF robot arm shows the effectiveness of the approach in trajectory tracking problems. Comparative evaluation with respect to PID, Fuzzy PD+I controls are presented to validate the controller design. The results presented emphasize that a satisfactory tracking precision could be achieved using ANFIS controller than PID and Fuzzy PD+I controllers
Uitgever: Education Institute of Kavala
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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