Dimensional Analysis of Acid Etching Effects on Vertically Grown Carbon Nanofibers Using Atomic Force Microscopy

This paper presents a discrete-time decentralized control scheme for trajectory tracking of a two degrees of freedom (DOF) robot manipulator. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feed...

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Bibliographic Details
Main Authors: Uchechukwu C. Wejinya, Siva Naga Sandeep Chalamalasetty, Zhuxin Dong, Meyya Meyyappan, Sunny E. Iyuke
Format: Article
Language:English
Published: Wiley 2013-07-01
Series:Nanomaterials and Nanotechnology
Subjects:
Online Access:http://www.intechopen.com/journals/nanomaterials_and_nanotechnology/dimensional-analysis-of-acid-etching-effects-on-vertically-grown-carbon-nanofibers-using-atomic-forc
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Summary:This paper presents a discrete-time decentralized control scheme for trajectory tracking of a two degrees of freedom (DOF) robot manipulator. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The weights for each neural network are adapted online by an extended Kalman filter training algorithm. The motion for each joint is controlled independently using only local angular position and velocity measurements. The stability analysis for the closed-loop system via the Lyapunov approach is included. Finally, the real-time results show the feasibility of the proposed control scheme robot manipulator.
ISSN:1847-9804