Control of time varying nonlinear system of supporting robot based on neural network

2017 ◽  
Author(s):  
Yuhao Zhu ◽  
Xie Li ◽  
Hui Zheng ◽  
Zhen Yang ◽  
You Wu ◽  
...  
Keyword(s):  
Neural Network ◽  
Nonlinear System ◽  
Time Varying

scholarly journals Dynamic Neural Network Identification and Decoupling Control Approach for MIMO Time-Varying Nonlinear Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Zhixi Shen ◽  
Kai Zhao
Keyword(s):  
Neural Network ◽  
Nonlinear System ◽  
Nonlinear Systems ◽  
Lyapunov Stability Theory ◽  
Adaptive Controller ◽  
Time Varying ◽  
Dynamic Neural Networks ◽  
Control Approach ◽  
The Neural Network ◽  
And Control

Overcoming the coupling among variables is greatly necessary to obtain accurate, rapid and independent control of the real nonlinear systems. In this paper, the main methodology, on which the method is based, is dynamic neural networks (DNN) and adaptive control with the Lyapunov methodology for the time-varying, coupling, uncertain, and nonlinear system. Under the framework, the DNN is developed to accommodate the identification, and the weights of DNN are iteratively and adaptively updated through the identification errors. Based on the neural network identifier, the adaptive controller of complex system is designed in the latter. To guarantee the precision and generality of decoupling tracking performance, Lyapunov stability theory is applied to prove the error between the reference inputs and the outputs of unknown nonlinear system which is uniformly ultimately bounded (UUB). The simulation results verify that the proposed identification and control strategy can achieve favorable control performance.

Real-domain QR decomposition models employing zeroing neural network and time-discretization formulas for time-varying matrices

2021 ◽  
Vol 448 ◽  
pp. 217-227
Author(s):  
Zhenyu Li ◽  
Yunong Zhang ◽  
Liangjie Ming ◽  
Jinjin Guo ◽  
Vasilios N. Katsikis
Keyword(s):  
Neural Network ◽  
Time Discretization ◽  
Qr Decomposition ◽  
Time Varying ◽  
Real Domain ◽  
Decomposition Models
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