Journal article Open Access

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

Monisha Pathak; Mrinal Buragohain

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    <subfield code="a">Sliding Mode Control, Robot manipulator,  Trajectory Tracking, Neural Network.</subfield>
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    <subfield code="u">Department of Electrical Engineering, Jorhat Engineering College, Jorhat, Assam, India.</subfield>
    <subfield code="a">Mrinal Buragohain</subfield>
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    <subfield code="u">Department of Instrumentation Engineering, Jorhat Engineering College, Jorhat, Assam, India.</subfield>
    <subfield code="a">Monisha Pathak</subfield>
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    <subfield code="a">&lt;p&gt;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.&lt;/p&gt;</subfield>
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