Adaptive Neural Network Finite-Time Control for Uncertain Robotic Manipulators

2013 ◽  
Vol 75 (3-4) ◽  
pp. 363-377 ◽  
Author(s):  
Haitao Liu ◽  
Tie Zhang
Keyword(s):  
Neural Network ◽  
Finite Time ◽  
Robotic Manipulators ◽  
Adaptive Neural Network ◽  
Time Control

scholarly journals Neural network adaptive command filtered control of robotic manipulators with input saturation

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141989477
Author(s):  
Lin Wang ◽  
Chunzhi Yang
Keyword(s):  
Neural Network ◽  
Finite Time ◽  
Tracking Error ◽  
Input Saturation ◽  
Robotic Manipulators ◽  
Small Region ◽  
Network Control ◽  
External Disturbances ◽  
Time Control ◽  
The Neural Network

This paper investigates finite-time control of uncertain robotic manipulators with external disturbances by means of neural network control and backstepping technique. To solve the “explosion of terms” in traditional backstepping control, a second-order command filter is designed, and the virtual input and its first-order derivative can be obtained accurately in a finite time. The parameters of the neural network are updated by using the tracking error signals. The proposed controller can guarantee that the tracking error converges to a small region of the origin in some finite time. Finally, we give a simulation study to show the effectiveness of the proposed method.

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