Resilient fault-tolerant anti-synchronization for stochastic delayed reaction-diffusion neural networks with semi-Markov jump parameters
NEURAL NETWORKS, cilt.125, ss.194-204, 2020 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 125
- Basım Tarihi: 2020
- Doi Numarası: 10.1016/j.neunet.2020.02.015
- Dergi Adı: NEURAL NETWORKS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, BIOSIS, Biotechnology Research Abstracts, Communication Abstracts, Compendex, Computer & Applied Sciences, EMBASE, INSPEC, MEDLINE, Psycinfo, zbMATH
- Sayfa Sayıları: ss.194-204
- Anahtar Kelimeler: Anti-synchronization, Semi-Markov process, Fault-tolerant control, Resilient control, Neural networks, H-INFINITY CONTROL, EXPONENTIAL STABILITY, SYSTEMS, STABILIZATION, CRITERIA
- İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet
Özet
This paper deals with the anti-synchronization issue for stochastic delayed reaction-diffusion neural networks subject to semi-Markov jump parameters. A resilient fault-tolerant controller is utilized to ensure the anti-synchronization in the presence of actuator failures as well as gain perturbations, simultaneously. Firstly, by means of the Lyapunov functional and stochastic analysis methods, a mean-square exponential stability criterion is derived for the resulting error system. It is shown the obtained criterion improves a previously reported result. Then, based on the present analysis result and using several decoupling techniques, a strategy for designing the desired resilient fault-tolerant controller is proposed. At last, two numerical examples are given to illustrate the superiority of the present stability analysis method and the applicability of the proposed resilient fault-tolerant anti-synchronization control strategy, respectively. (c) 2020 Elsevier Ltd. All rights reserved.