scholarly journals Adaptive Neural Network-Based Event-Triggered Control of Single-Input Single-Output Nonlinear Discrete-Time Systems

2016 ◽  
Vol 27 (1) ◽  
pp. 151-164 ◽  
Author(s):  
Avimanyu Sahoo ◽  
Hao Xu ◽  
Sarangapani Jagannathan
Keyword(s):  
Neural Network ◽  
Discrete Time ◽  
Adaptive Neural Network ◽  
Single Input Single Output ◽  
Single Output ◽  
Discrete Time Systems ◽  
Single Input ◽  
Time Systems ◽  
Event Triggered

scholarly journals Stabilization of Positive Linear Discrete-Time Systems by Using a Brauer’s Theorem

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Begoña Cantó ◽  
Rafael Cantó ◽  
Snezhana Kostova
Keyword(s):  
Discrete Time ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Closed Loop System ◽  
Single Input Single Output ◽  
Single Output ◽  
Discrete Time Systems ◽  
Single Input ◽  
Linear State ◽  
Time Systems

The stabilization problem of positive linear discrete-time systems (PLDS) by linear state feedback is considered. A method based on a Brauer’s theorem is proposed for solving the problem. It allows us to modify some eigenvalues of the system without changing the rest of them. The problem is studied for the single-input single-output (SISO) and for multi-input multioutput (MIMO) cases and sufficient conditions for stability and positivity of the closed-loop system are proved. The results are illustrated by numerical examples and the proposed method is used in stochastic systems.

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