Izvorni znanstveni članak
Dimensional Analysis of Acid Etching Effects on Vertically Grown Carbon Nanofibers Using Atomic Force Microscopy
Uchechukwu C. Wejinya
; Department of Mechanical Engineering, University of Arkansas, Fayetteville, AR, USA
Siva Naga Sandeep Chalamalasetty
; Department of Microelectronics and Photonics, University of Arkansas, Fayetteville, AR, USA
Zhuxin Dong
; Department of Mechanical Engineering, University of Arkansas, Fayetteville, AR, USA
Meyya Meyyappan
; NASA Ames Research Center, Moffet Field, CA, USA
Sunny E. Iyuke
; School of Chemical & Metallurgical Engineering, University of the Witwatersrand, Johannesburg, South Africa
Sažetak
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.
Ključne riječi
decentralized control; high-order neural networks; extended Kalman filter; backstepping
Hrčak ID:
142693
URI
Datum izdavanja:
1.1.2013.
Posjeta: 1.063 *