Further Investigations on Noise-Tolerant Zeroing Neural Network for Time-Varying Quadratic Programming with Robotic Applications

Author(s):  
Mei Liu ◽  
Shuai Li ◽  
Yinyan Zhang ◽  
Long Jin
2021 ◽  
Author(s):  
Miaomiao Zhang

<div>In this paper, a varying-gain zeroing (or Zhang) neural network (VG-ZNN) is proposed to obtain the online solution of the time-varying linear equation and inequality system. Distinguished from the fixed-value design parameter in</div><div>the original zeroing (or Zhang) neural network (ZNN) models, the design parameter of the VG-ZNN model is a nonlinear function that changes with time. The VG-ZNN model composed of the new time-varying design parameter we proposed can achieve fixed-time convergence and tolerate time-varying bounded noise and time-varying derivable noise. The theoretical detailed analysis of the convergence and robustness of the VG-ZNN model are given.</div>


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