Estimation of the Domain of Attraction of Discrete-Time Impulsive Cohen-Grossberg Neural Networks Model With Impulse Input Saturation

Author(s):  
Zixiang Shen ◽  
Chuandong Li ◽  
Yi Li
2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Zhenhua Zhou ◽  
Mao Wang ◽  
Qitian Yin

This paper is concerned with the problem of designing robust H-infinity output feedback controller and resilient filtering for a class of discrete-time singular piecewise-affine systems with input saturation and state constraints. Based on a singular piecewise Lyapunov function combined with S-procedure and some matrix inequality convexifying techniques, the H-infinity stabilization condition is established and the resilient H-infinity filtering error dynamic system is investigated, and, meanwhile, the domain of attraction is well estimated. Under energy bounded disturbance, the input saturation disturbance tolerance condition is proposed; then, the resilient H-infinity filter is designed in some restricted region. It is shown that the controller gains and filter design parameters can be obtained by solving a family of LMIs parameterized by one or two scalar variables. Meanwhile, by using the corresponding optimization methods, the domain of attraction and the disturbance tolerance level is maximized, and the H-infinity performanceγis minimized. Numerical examples are given to illustrate the effectiveness of the proposed design methods.


Author(s):  
Sadek Belamfedel Alaoui ◽  
El Houssaine Tissir ◽  
Noreddine Chaibi ◽  
Fatima El Haoussi

Designing robust active queue management subjected to network imperfections is a challenging problem. Motivated by this topic, we addressed the problem of controller design for linear systems with variable delay and unsymmetrical constraints by the scaled small gain theorem. We designed two mechanisms: robust enhanced proportional derivative; and robust enhanced proportional derivative subjected to input saturation. Discussion of their practical implementations along with extensive comparisons by MATLAB and NS3 illustrate the improved performance and the enlargement of the domain of attraction regarding some literature results.


2021 ◽  
Author(s):  
M. Hernandez–Gonzalez ◽  
E.A. Hernandez–Vargas

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