Finite-time stability and synchronization of memristor-based fractional-order fuzzy cellular neural networks

Zheng, Mingwen; Peng, Haipeng; Xiao, Jinghua; Yang, Yixian; Zhang, Yanping; Zhao, Hui

doi:10.1016/j.cnsns.2017.11.025

Cited by 131 publications

(42 citation statements)

References 43 publications

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“…Therefore, one can substitutė1 anḋ2 with their hat counterparts calculated from (11) and (12). This leads to (18), which is clearly…”

Section: Identification Of Structures Using Vsmmentioning

confidence: 98%

“…[4][5][6] On the other hand, in the offline methods, the data is processed after the whole measurement is completed. [18][19][20] Although parameter estimation is not the main purpose of the synchronization methods, it turns out that, for certain dynamical systems, they can be efficiently used for online identification of unknown parameters as well. 7 In addition, see the work of Johansson 8 regarding the system identification methods.)…”

Section: Introductionmentioning

confidence: 99%

“…The synchronization theory is also used in the study of memristor-based neural networks in presence of mixed delays and stochastic perturbations and to investigate their finite-time stability problem. [18][19][20] Although parameter estimation is not the main purpose of the synchronization methods, it turns out that, for certain dynamical systems, they can be efficiently used for online identification of unknown parameters as well. [21][22][23] However, despite their partial success in several engineering fields, they are still in the early stages for civil and structural engineering problems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A new method for online identification of civil structures: Virtual synchronization

Ghaderi

Amini

2018

Adaptive Control & Signal

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This paper presents a new approach, named Virtual Synchronization Method (VSM), for online identification of stiffness and viscous damping in a civil structure while it is subjected to a harmonic ground motion acceleration. It is assumed that displacement and velocity of the structure relative to the ground are measured in real time. They are used to define a virtual system similar to the actual structure. Proper controllers and estimation functions are designed to force the states of this virtual system to follow those of the actual structure.Theoretical results are derived to study on what conditions, after the two systems synchronized, the estimation functions converge to the true stiffness and damping of the actual structure. Provided numerical examples show that VSM is a promising method for online identification of civil structures and should be the subject of further studies. KEYWORDS adaptive system identification, online identification of structures, real-time estimation of damping and stiffness, smart structures, Virtual Synchronization Method 16

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“…Therefore, one can substitutė1 anḋ2 with their hat counterparts calculated from (11) and (12). This leads to (18), which is clearly…”

Section: Identification Of Structures Using Vsmmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A new method for online identification of civil structures: Virtual synchronization

Ghaderi

Amini

2018

Adaptive Control & Signal

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show abstract

“…Remark 5. Nowadays, many scholars have investigated the dynamics of fractional-order CNs by estimating the solution of systems directly, see previous studies, [31][32][33] for example. It should be stressed that Lyapunov method is a classical method for the investigations of dynamics of fractional-order CNs.…”

Section: It Is Clear Thatmentioning

confidence: 99%

Synchronization for fractional‐order multi‐linked complex network with two kinds of topological structure via periodically intermittent control

2019

Math Methods in App Sciences

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This paper concentrates on the global synchronization of the fractional‐order multi‐linked complex network (FMCN) via periodically intermittent control. It should be stressed that periodically intermittent control is employed to the FMCN for the first time. Moreover, the network is defined on digraphs with different weights, and two situations on topological structure of the network are discussed, including each digraph being strongly connected, and the biggest one being strongly connected. Based on Lyapunov method and graph theory, some synchronization criteria are obtained under two situations. And, the obtained synchronization criteria have a close relationship with the order of fractional‐order derivative, coupling strength, control gain, control rate, and control period. Besides, for practicability, theoretical results are applied to studying the synchronization of fractional‐order multi‐linked chaotic systems, and some sufficient conditions are provided. For a special case, fractional‐order multi‐linked Lorenz chaotic systems, numerical simulations are given to indicate the feasibility of theoretical results and the effectiveness of control strategy.

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“…On the other hand, the discontinuous controllers were creatively designed to realize the FTS of neural networks with discontinuous right-hand side [18,19]. However, there are a few papers concerning the finite-time stabilization of MNNs [20][21][22][23]. In [20], the authors investigated the FTS of MNNs by designing the discontinuous state feedback controller, but they ignored time delay.…”

Section: Introductionmentioning

confidence: 99%

Finite‐Time Stabilization of Memristive Cohen‐Grossberg Neural Networks with Time‐Varying Delay

Zhang

2018

Complexity

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In this paper, the finite-time stabilization problem for memristive Cohen-Grossberg neural networks with time-varying delay is discussed. By using the novel fixed point theory of set-valued maps, we establish the existence theorem of equilibrium point. In order to realize the finite-time stabilization, two different kinds of discontinuous state feedback controllers whether including time-varying delay are designed. Based on the extended Filippov framework and two different kinds of methods whether using finite-time stability theory, some novel sufficient conditions and the upper bound of the settling time for finite-time stabilization are proposed. Finally, two numerical examples are given to demonstrate the validity of theoretical results.

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Finite-time stability and synchronization of memristor-based fractional-order fuzzy cellular neural networks

Cited by 131 publications

References 43 publications

A new method for online identification of civil structures: Virtual synchronization

A new method for online identification of civil structures: Virtual synchronization

Synchronization for fractional‐order multi‐linked complex network with two kinds of topological structure via periodically intermittent control

Finite‐Time Stabilization of Memristive Cohen‐Grossberg Neural Networks with Time‐Varying Delay

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