Stabilization of delayed semi-Markov jump neural networks with actuator faults: A quantized hybrid control approach

Sakthivel, Rathinasamy and Aravinth, Narayanan and Devi, N. Birundha and Mohammadzadeh, Ardashir and Md Saat, Mohd Shakir (2024) Stabilization of delayed semi-Markov jump neural networks with actuator faults: A quantized hybrid control approach. Nonlinear Analysis: Hybrid Systems, 54. pp. 1-17. ISSN 1751-570X

[img] Text
01013201220241019101429.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB)

Abstract

The presented research is to focus on the issue of fault alarm-based quantized hybrid control strategy for semi-Markov jump neural networks subject to multiple vulnerable factors, namely, actuator faults, quantization effects and time-varying delays. Particularly, the fault-based alarm signal with a threshold value is proposed for controller switching and also for preventing false alarms. Precisely, a logarithmic quantizer is incorporated in the control design to adjust the transmission of signals and to enhance better robustness on system performance. Besides, a mixed H∞ and passivity performance is employed in order to handle the traces of external disturbances. By proposing Lyapunov–Krasovskii functional involving time delays along with Wirtinger based integral inequality, the anticipated control gain parameters that confirm the stochastic stability of the addressed system can be determined with the assistance of linear matrix inequality. The excellent dynamic performances of the proposed control scheme are clarified through two numerical examples, whereas the stability of the system is restrained with the timely alert performance of the configured alarm signal.

Item Type: Article
Uncontrolled Keywords: Semi-Markovian jump neural networks, Hybrid control design, Fault-alarm approach, Actuator fault, Quantization
Divisions: Faculty Of Electronics And Computer Technology And Engineering
Depositing User: Sabariah Ismail
Date Deposited: 11 Feb 2025 08:49
Last Modified: 11 Feb 2025 08:49
URI: http://eprints.utem.edu.my/id/eprint/28334
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item