Design of Hybrid Neural Fuzzy Controller for Human Robotic Leg System

Autor: Ekhlas H. Karam, Ayam M Abbass, Noor S. Abdul-Jaleel
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Al-Khawarizmi Engineering Journal, Vol 14, Iss 1 (2018)
Druh dokumentu: article
ISSN: 1818-1171
2312-0789
DOI: 10.22153/kej.2018.08.007
Popis: In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and FPD-ID controllers.
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