Cover
Vol. 13 No. 1 (2017)

Published: July 31, 2017

Pages: 114-122

Original Article

Neural Network-Based Adaptive Control of Robotic Manipulator: Application to a Three Links Cylindrical Robot

Abdul-Basset A. AL-Hussein 1
1Electrical Engineering Department Basrah University Basrah, Iraq
History
  • Received: May 31, 2017
  • Available Online: July 31, 2017
DOI

https://doi.org/10.37917/ijeee.13.1.13

Abstract

A composite PD and sliding mode neural network (NN)-based adaptive controller, for robotic manipulator trajectory tracking, is presented in this paper. The designed neural networks are exploited to approximate the robotics dynamics nonlinearities, and compensate its effect and this will enhance the performance of the filtered error based PD and sliding mode controller. Lyapunov theorem has been used to prove the stability of the system and the tracking error boundedness. The augmented Lyapunov function is used to derive the NN weights learning law. To reduce the effect of breaching the NN learning law excitation condition due to external disturbances and measurement noise; a modified learning law is suggested based on e-modification algorithm. The controller effectiveness is demonstrated through computer simulation of cylindrical robot manipulator.

Keywords

References

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