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Adaptive sliding mode control with radial basis function neural network for time dependent disturbances and uncertainties

Shanta, Mst. Nafisa Tamanna and Zainul Azlan, Norsinnira (2016) Adaptive sliding mode control with radial basis function neural network for time dependent disturbances and uncertainties. ARPN Journal of Engineering and Applied Sciences, 11 (6). pp. 4123-4129.

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Abstract

A radial basis function neural network (RBFNN) based adaptive sliding mode controller is presented in this paper to cater for a 3-DOF robot manipulator with time-dependent uncertainties and disturbance. RBF is one of the most popular intelligent methods to approximate uncertainties due to its simple structure and fast learning capacity. By choosing a proper Lyapunov function, the stability of the controller can be proven and the update laws of the RBFN can be derived easily. Simulation test has been conducted to verify the effectiveness of the controller. The result shows that the controller has successfully compensate the time-varying uncertainties and disturbances with error less than 0.001 rad.

Item Type: Article (Journal)
Additional Information: 4494/51750
Uncontrolled Keywords: radial basis function network, adaptive control, sliding mode control, time-varying uncertainties and disturbances, robot manipulator
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Norsinnira Zainul Azlan
Date Deposited: 23 Aug 2016 08:52
Last Modified: 11 Jan 2017 08:37
URI: http://irep.iium.edu.my/id/eprint/51750

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