Design of Hybrid Neural Fuzzy Controller for Human Robotic Leg System

Authors

  • Ekhlas H. Karam Department of Computer Engineering/ University of Al-Mustansyria
  • Ayam M Abbass Department of Computer Engineering/ University of Al-Mustansyria
  • Noor S. Abdul-Jaleel Department of Electrical Engineering/ University of Al-Mustansyria

DOI:

https://doi.org/10.22153/kej.2018.08.007

Abstract

 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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Published

2018-04-08

How to Cite

Karam, E. H., Abbass, A. M., & Abdul-Jaleel, N. S. (2018). Design of Hybrid Neural Fuzzy Controller for Human Robotic Leg System. Al-Khwarizmi Engineering Journal (Alkej), 14(1), 145–155. https://doi.org/10.22153/kej.2018.08.007

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Articles