Impulsive sampled-data controller design for synchronization of delayed T–S fuzzy Hindmarsh–Rose neuron model

Prasath Nirvin; Fathalla A. Rihan; Rajan Rakkiyappan; Chandrasekar Pradeep

doi:10.1016/j.matcom.2021.03.022

Impulsive sampled-data controller design for synchronization of delayed T–S fuzzy Hindmarsh–Rose neuron model

Prasath Nirvin, Fathalla A. Rihan, Rajan Rakkiyappan, Chandrasekar Pradeep

Department of Mathematical Sciences

Research output: Contribution to journal › Article › peer-review

15 Citations (Scopus)

Abstract

In this paper, the authors investigate the synchronization criteria of fuzzy impulsive sampled data control for Hindmarsh–Rose (H–R) neuronal system with time-delay. For the stability analysis, Lyapunov–Krasovskii functionals (LKF) are employed to deduce the conditions that guarantee the asymptotical stability of the proposed T–S fuzzy H–R neuron system. By utilizing free-matrix based inequality, some sufficient conditions are derived and expressed in terms of linear matrix inequalities. The obtained sufficient conditions can be checked easily by standard available software packages in MATLAB. Finally, some numerical simulations are given to validate the effectiveness of the proposed conditions.

Original language	English
Pages (from-to)	588-602
Number of pages	15
Journal	Mathematics and Computers in Simulation
Volume	201
DOIs	https://doi.org/10.1016/j.matcom.2021.03.022
Publication status	Published - Nov 2022

Keywords

Hindmarsh–Rose (H–R) neuron model
Impulsive control
Linear matrix inequality (LMI)
Synchronization
Takagi–Sugeno (T–S) fuzzy rules

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science
Numerical Analysis
Modelling and Simulation
Applied Mathematics

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10.1016/j.matcom.2021.03.022

Cite this

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title = "Impulsive sampled-data controller design for synchronization of delayed T–S fuzzy Hindmarsh–Rose neuron model",

abstract = "In this paper, the authors investigate the synchronization criteria of fuzzy impulsive sampled data control for Hindmarsh–Rose (H–R) neuronal system with time-delay. For the stability analysis, Lyapunov–Krasovskii functionals (LKF) are employed to deduce the conditions that guarantee the asymptotical stability of the proposed T–S fuzzy H–R neuron system. By utilizing free-matrix based inequality, some sufficient conditions are derived and expressed in terms of linear matrix inequalities. The obtained sufficient conditions can be checked easily by standard available software packages in MATLAB. Finally, some numerical simulations are given to validate the effectiveness of the proposed conditions.",

keywords = "Hindmarsh–Rose (H–R) neuron model, Impulsive control, Linear matrix inequality (LMI), Synchronization, Takagi–Sugeno (T–S) fuzzy rules",

author = "Prasath Nirvin and Rihan, \{Fathalla A.\} and Rajan Rakkiyappan and Chandrasekar Pradeep",

note = "Publisher Copyright: {\textcopyright} 2021 International Association for Mathematics and Computers in Simulation (IMACS)",

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doi = "10.1016/j.matcom.2021.03.022",

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T1 - Impulsive sampled-data controller design for synchronization of delayed T–S fuzzy Hindmarsh–Rose neuron model

AU - Nirvin, Prasath

AU - Rihan, Fathalla A.

AU - Rakkiyappan, Rajan

AU - Pradeep, Chandrasekar

PY - 2022/11

Y1 - 2022/11

N2 - In this paper, the authors investigate the synchronization criteria of fuzzy impulsive sampled data control for Hindmarsh–Rose (H–R) neuronal system with time-delay. For the stability analysis, Lyapunov–Krasovskii functionals (LKF) are employed to deduce the conditions that guarantee the asymptotical stability of the proposed T–S fuzzy H–R neuron system. By utilizing free-matrix based inequality, some sufficient conditions are derived and expressed in terms of linear matrix inequalities. The obtained sufficient conditions can be checked easily by standard available software packages in MATLAB. Finally, some numerical simulations are given to validate the effectiveness of the proposed conditions.

AB - In this paper, the authors investigate the synchronization criteria of fuzzy impulsive sampled data control for Hindmarsh–Rose (H–R) neuronal system with time-delay. For the stability analysis, Lyapunov–Krasovskii functionals (LKF) are employed to deduce the conditions that guarantee the asymptotical stability of the proposed T–S fuzzy H–R neuron system. By utilizing free-matrix based inequality, some sufficient conditions are derived and expressed in terms of linear matrix inequalities. The obtained sufficient conditions can be checked easily by standard available software packages in MATLAB. Finally, some numerical simulations are given to validate the effectiveness of the proposed conditions.

KW - Hindmarsh–Rose (H–R) neuron model

KW - Impulsive control

KW - Linear matrix inequality (LMI)

KW - Synchronization

KW - Takagi–Sugeno (T–S) fuzzy rules

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Impulsive sampled-data controller design for synchronization of delayed T–S fuzzy Hindmarsh–Rose neuron model

Abstract

Keywords

ASJC Scopus subject areas

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