Abstract
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.
Highlights
Carbon nanofibers might have been discovered as early as 1889 [1], two major breakthroughs brought life to this artless material
In 1985, Buckminster fullerene C60 was discovered by a team headed by Kroto [2] followed by the illustration of IIjima [3] that carbon nanotubes are formed during the arc discharge synthesis of C60
A 2 μm square area was selected in which nanofibers were found, and was rescanned
Summary
Carbon nanofibers might have been discovered as early as 1889 [1], two major breakthroughs brought life to this artless material. In 1985, Buckminster fullerene C60 was discovered by a team headed by Kroto [2] followed by the illustration of IIjima [3] that carbon nanotubes are formed during the arc discharge synthesis of C60. These illustrations encouraged scientists to look into the applications of this exciting material. Carbon nanofiber research has a never ending horizon with application in the fields of biology, medicine, astronomy, electronics, etc. In the field of electronics, the main research focuses on the integration www.intechopen.com
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