Adaptive Neural Network Finite-Time Control for Uncertain Robotic Manipulators |
| |
Authors: | Haitao Liu Tie Zhang |
| |
Affiliation: | 1. Guangdong Ocean University, Zhanjiang, 524088, Guangdong, China 2. South China University of Technology, Guangzhou, 510640, Guangdong, China
|
| |
Abstract: | An adaptive neural network finite-time controller (NNFTC) for a class of uncertain nonlinear systems is proposed by using the backstepping method, which employs an adaptive neural network (NN) system to approximate the structure uncertainties and uses a variable structure term to compensate the approximation errors, thus improving the robustness of the system to external disturbances. The controller is then applied to uncertain robotic manipulators, with a control objective of driving the system state to the original equilibrium point. It is proved that the closed-loop system is finite-time stable. Moreover, simulated and experimental results indicate that the proposed NNFTC is effective and robust. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|