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

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

Mathematics and Computers in Simulation (MATCOM), 2022, vol. 201, issue C, 588-602

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; Takagi–Sugeno (T–S) fuzzy rules; Linear matrix inequality (LMI); Synchronization; Impulsive control (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:201:y:2022:i:c:p:588-602

DOI: 10.1016/j.matcom.2021.03.022

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