5411870
doi
10.35940/ijeat.F3005.0810621
oai:zenodo.org:5411870
Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
Publisher
Mrinal Buragohain
Department of Electrical Engineering, Jorhat Engineering College, Jorhat, Assam, India.
Sliding Mode with Adaptive Control of Robot Manipulator Trajectory Tracking using Neural Network Approximation
Monisha Pathak
Department of Instrumentation Engineering, Jorhat Engineering College, Jorhat, Assam, India.
issn:2249-8958
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Sliding Mode Control, Robot manipulator, Trajectory Tracking, Neural Network.
<p>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.</p>
Zenodo
2021-08-30
info:eu-repo/semantics/article
5411869
1630720120.950244
550560
md5:8782e7d6db33189eb012c08dee9166ed
https://zenodo.org/records/5411870/files/F30050810621.pdf
public
2249-8958
Is cited by
issn
International Journal of Engineering and Advanced Technology (IJEAT)
10
6
120-123
2021-08-30