Decentralized neural network control for guaranteed tracking error constraint of a robot manipulator

2015 ◽  
Vol 13 (4) ◽  
pp. 906-915 ◽  
Author(s):  
Seong-Ik Han ◽  
Jang-Myung Lee
Keyword(s):  
Neural Network ◽  
Robot Manipulator ◽  
Tracking Error ◽  
Network Control ◽  
Neural Network Control ◽  
Error Constraint

scholarly journals Adaptive Finite-time Dynamic Surface Neural Network Control of an Uncertain Robot with Output Constraint and Input Saturation

2021 ◽  
Author(s):  
Zhao Zhang ◽  
Lingxi Peng ◽  
Zhijia Zhao
Keyword(s):  
Neural Network ◽  
Finite Time ◽  
Control Method ◽  
Tracking Error ◽  
Input Saturation ◽  
Network Control ◽  
Neural Network Control ◽  
Dynamic Surface ◽  
Time Dynamic ◽  
Output Constraints

Abstract In this study, a finite-time dynamic surface neural network control is developed for an uncertain n-link robot subject to input saturation and output constraints. First, a barrier Lyapunov function and a hyperbolic tangent function are applied to solve the system constraints using a dynamic surface control. Subsequently, a radial basis function neural network is utilized to handle system uncertainties. Then, a finite-time filter is employed in the design to achieve the fast convergence and a Nussbaum function is employed to optimize the design process. Finally, the simulation results show that the dynamic tracking error is proved to converging to zero, and the proposed control method is effective and never violates the constraints.

scholarly journals Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control

2020 ◽  
Vol 5 (2) ◽  
pp. 3050-3057 ◽  
Author(s):  
Julian Nubert ◽  
Johannes Kohler ◽  
Vincent Berenz ◽  
Frank Allgower ◽  
Sebastian Trimpe
Keyword(s):  
Neural Network ◽  
Robot Manipulator ◽  
Network Control ◽  
Neural Network Control ◽  
Fast Tracking
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