Synchronization of Fractional Order Neutral Type Fuzzy Cellular Neural Networks with Discrete and Distributed Delays via State Feedback Control

2021 ◽  
Author(s):  
M. Syed Ali ◽  
M. Hymavathi
Keyword(s):  
Neural Networks ◽  
Feedback Control ◽  
Fractional Order ◽  
State Feedback ◽  
Neutral Type ◽  
Cellular Neural Networks ◽  
State Feedback Control ◽  
Distributed Delays ◽  
Fuzzy Cellular Neural Networks

scholarly journals Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying Delays

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1146
Author(s):  
Călin-Adrian Popa ◽  
Eva Kaslik
Keyword(s):  
Neural Networks ◽  
Feedback Control ◽  
Fractional Order ◽  
Finite Time ◽  
State Feedback ◽  
Neutral Type ◽  
Leakage Delay ◽  
State Feedback Control ◽  
Time Varying ◽  
Control Scheme

This paper studies fractional-order neural networks with neutral-type delay, leakage delay, and time-varying delays. A sufficient condition which ensures the finite-time synchronization of these networks based on a state feedback control scheme is deduced using the generalized Gronwall–Bellman inequality. Then, a different state feedback control scheme is employed to realize the finite-time Mittag–Leffler synchronization of these networks by using the fractional-order extension of the Lyapunov direct method for Mittag–Leffler stability. Two numerical examples illustrate the feasibility and the effectiveness of the deduced sufficient criteria.

scholarly journals Stability of fractional order fuzzy cellular neural networks with distributed delays via hybrid feedback controllers

2021 ◽  
Author(s):  
Ajendra Sing ◽  
Jitendra Nath Rai
Keyword(s):  
Neural Networks ◽  
Feedback Control ◽  
Fractional Order ◽  
Sufficient Conditions ◽  
Cellular Neural Networks ◽  
Control Technique ◽  
Fuzzy Cellular Neural Networks ◽  
Feedback Controllers ◽  
Lyapunov Approach ◽  
Analysis Techniques

Abstract This article studies the Global Mittag-Leffler stability of fractional order fuzzy cellular neural networks via hybrid feedback controllers. Based on hybrid feedback control technique Lyapunov approach, and some novel analysis techniques of fractional calculation, some sufficient conditions are obtained to guarantee the Global Mittag-lefflers stability. Finally, two simulation example are given to illustrate the effectiveness of the proposed method.

scholarly journals New Results on Synchronization of Fractional-Order Memristor‐Based Neural Networks via State Feedback Control

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiaofan Li ◽  
Yuan Ge ◽  
Hongjian Liu ◽  
Huiyuan Li ◽  
Jian-an Fang
Keyword(s):  
Neural Networks ◽  
Feedback Control ◽  
Fractional Order ◽  
Nonsmooth Analysis ◽  
State Feedback ◽  
Direct Method ◽  
Young Inequality ◽  
State Feedback Control ◽  
Feedback Controllers ◽  
Theoretical Results

This paper addresses the synchronization issue for the drive-response fractional-order memristor‐based neural networks (FOMNNs) via state feedback control. To achieve the synchronization for considered drive-response FOMNNs, two feedback controllers are introduced. Then, by adopting nonsmooth analysis, fractional Lyapunov’s direct method, Young inequality, and fractional-order differential inclusions, several algebraic sufficient criteria are obtained for guaranteeing the synchronization of the drive-response FOMNNs. Lastly, for illustrating the effectiveness of the obtained theoretical results, an example is given.

scholarly journals H∞ state feedback control of commensurate fractional order systems

2013 ◽  
Vol 46 (1) ◽  
pp. 54-59 ◽  
Author(s):  
Lamine Fadiga ◽  
Jocelyn Sabatier ◽  
Christophe Farges
Keyword(s):  
Feedback Control ◽  
Fractional Order ◽  
State Feedback ◽  
State Feedback Control ◽  
Fractional Order Systems
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