Journal article Open Access

Sliding Mode with Adaptive Control of Robot Manipulator Trajectory Tracking using Neural Network Approximation

Monisha Pathak; Mrinal Buragohain

Sponsor(s)
Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)

This paper briefly discusses about the Robust Controller based on Adaptive Sliding Mode Technique with RBF Neural Network (ASMCNN) for Robotic Manipulator tracking control in presence of uncertainities and disturbances. The aim is to design an effective trajectory tracking controller without any modelling information. The ASMCNN is designed to have robust trajectory tracking of Robot Manipulator, which combines Neural Network Estimation with Adaptive Sliding Mode Control. The RBF model is utilised to construct a Lyapunov function-based adaptive control approach. Simulation of the tracking control of a 2dof Robotic Manipulator in the presence of unpredictability and external disruption demonstrates the usefulness of the planned ASMCNN.

Files (550.6 kB)
Name Size
F30050810621.pdf
md5:8782e7d6db33189eb012c08dee9166ed
550.6 kB Download
16
16
views
downloads
Views 16
Downloads 16
Data volume 8.8 MB
Unique views 15
Unique downloads 16

Share

Cite as