A Thermodynamic-Based Control Architecture for Semistability and Consensus of Discrete-Time Nonlinear Network Systems

2021 ◽  
Author(s):  
Wassim M. Haddad ◽  
Junsoo Lee
Keyword(s):  
Discrete Time ◽  
Control Architecture ◽  
Network Systems ◽  
Nonlinear Network

scholarly journals Relative Degrees and Implicit Function-Based Control of Discrete-Time Noncanonical Form Neural Network Systems

2020 ◽  
Vol 50 (2) ◽  
pp. 514-524
Author(s):  
Yanjun Zhang ◽  
Gang Tao ◽  
Mou Chen ◽  
Wei Lin ◽  
Zhengqiang Zhang
Keyword(s):  
Neural Network ◽  
Discrete Time ◽  
Implicit Function ◽  
Network Systems ◽  
Noncanonical Form

Pinning Control of Higher Order Nonlinear Network Systems

2021 ◽  
Vol 5 (4) ◽  
pp. 1225-1230
Author(s):  
Davide Liuzza ◽  
Pietro De Lellis
Keyword(s):  
Pinning Control ◽  
Higher Order ◽  
Network Systems ◽  
Nonlinear Network

scholarly journals Input-to-State Stability for Dynamical Neural Networks with Time-Varying Delays

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Weisong Zhou ◽  
Zhichun Yang
Keyword(s):  
Sufficient Conditions ◽  
Network Models ◽  
Functional Method ◽  
Linear Matrix ◽  
Time Varying ◽  
Neural Network Models ◽  
Network Systems ◽  
Nonlinear Network ◽  
Dynamical Neural Network ◽  
Dynamical Neural Networks

A class of dynamical neural network models with time-varying delays is considered. By employing the Lyapunov-Krasovskii functional method and linear matrix inequalities (LMIs) technique, some new sufficient conditions ensuring the input-to-state stability (ISS) property of the nonlinear network systems are obtained. Finally, numerical examples are provided to illustrate the efficiency of the derived results.

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