scholarly journals Finite-Time Neural Network Backstepping Control of an Uncertain Fractional-Order Duffing System With Input Saturation

2020 ◽  
Vol 8 ◽  
Author(s):  
Hui Lv ◽  
Xiulan Zhang
Keyword(s):  
Neural Network ◽  
Fractional Order ◽  
Finite Time ◽  
Input Saturation ◽  
Backstepping Control ◽  
Duffing System

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.

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