Multilayer minimum projection method for nonsmooth strict control Lyapunov function design

2010 ◽  
Vol 59 (9) ◽  
pp. 563-570 ◽  
Author(s):  
Hisakazu Nakamura ◽  
Yoshiro Fukui ◽  
Nami Nakamura ◽  
Hirokazu Nishitani
Keyword(s):  
Lyapunov Function ◽  
Projection Method ◽  
Control Lyapunov Function ◽  
Strict Control ◽  
Function Design

Minimum Projection Method for nonsmooth control Lyapunov function design on general manifolds

2009 ◽  
Vol 58 (10-11) ◽  
pp. 716-723 ◽  
Author(s):  
Hisakazu Nakamura ◽  
Yuh Yamashita ◽  
Hirokazu Nishitani
Keyword(s):  
Lyapunov Function ◽  
Projection Method ◽  
Control Lyapunov Function ◽  
Function Design

scholarly journals Predefined-Time Antisynchronization of Two Different Chaotic Neural Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Lixiong Lin
Keyword(s):  
Neural Networks ◽  
Lyapunov Function ◽  
Time Stability ◽  
Stabilization Time ◽  
Control Lyapunov Function ◽  
Practical Advantage ◽  
Chaotic Neural Networks ◽  
Time Period ◽  
Function Design ◽  
Definition Of

This paper is concerned with antisynchronization in predefined time for two different chaotic neural networks. Firstly, a predefined-time stability theorem based on Lyapunov function is proposed. With the help of the definition of predefined time, it is convenient to establish a direct relationship between the tuning gain of the system and the fixed stabilization time. Then, the antisynchronization is achieved between two different chaotic neural networks via active control Lyapunov function design. The designed controller presents the practical advantage that the least upper bound for the settling time can be explicitly defined during the control design. With the help of the designed controller, the antisynchronization errors converge within a predefined-time period. Numerical simulations are presented in order to show the reliability of the proposed method.

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