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

Nanomaterials and Nanotechnology

Meyya Meyyappan¹  Sunny E. Iyuke¹  Siva Naga Sandeep Chalamalasetty¹  Zhuxin Dong¹  Uchechukwu C. Wejinya¹ 

关键词: Decentralized control;    High-Order Neural Networks;    Extended Kalman Filter;    Backstepping;   

DOI  :  10.5772/56763

来源: InTech

【 摘 要 】

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.

【 授权许可】

Unknown