Fuzzy-neural-network inherited backstepping control for robot manipulator

2014 ◽  
Author(s):  
Rong-Jong Wai ◽  
Rajkumar Muthusamy
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Robot Manipulator ◽  
Backstepping Control ◽  
Fuzzy Neural

Design of fuzzy system-fuzzy neural network-backstepping control for complex robot system

2021 ◽  
Vol 546 ◽  
pp. 1230-1255
Author(s):  
Kunming Zheng ◽  
Qiuju Zhang ◽  
Youmin Hu ◽  
Bo Wu
Keyword(s):  
Neural Network ◽  
Fuzzy System ◽  
Fuzzy Neural Network ◽  
Backstepping Control ◽  
Robot System ◽  
Fuzzy Neural

scholarly journals Fuzzy-neural network compensator for Robot manipulator controlled by PD-like fuzzy system

2012 ◽  
Vol 8 (8) ◽  
pp. 35-44
Author(s):  
Turki Abdalla ◽  
Basil Jasim
Keyword(s):  
Neural Network ◽  
Fuzzy System ◽  
Fuzzy Neural Network ◽  
Robot Manipulator ◽  
Fuzzy Neural ◽  
Error Space ◽  
Reference Trajectories ◽  
Neural Network Compensator ◽  
Input Error ◽  
Computed Torque

In this paper, high tracking performance control structure for rigid robot manipulator is proposed. PD-like Sugano type fuzzy system is used as a main controller, while fuzzy-neural network (FNN) is used as a compensator for uncertainties by minimizing suitable function. The output of FNN is added to the reference trajectories to modify input error space, so that the system robust to any change in system parameters. The proposed structure is simulated and compared with computed torque controller. The simulation study has showed the validity of our structure, also showed its superiority to computed torque controller.

Sign in / Sign up

Export Citation Format

Share Document