Work

Finite-Time Dissipative Fault Estimate and Event-Triggered Fault-Tolerant Synchronization Control for Discrete Semi-Markov Jumping Neural Networks

Year: 2025

Type: article

Abstract: This paper studies discrete-time semi-Markov neural networks (NNs) and proposes a finite-time γ-dissipative fault estimate (FE) and fault-tolerant synchronization control (FTSC) with the event-triggered method. Based on the intermediate variable introduced, an FE scheme is presented to obtain estimate information of faults, states, and intermediate variables. According to the event-triggered condition designed, an FTSC protocol is proposed so that the error system between master system and slave system is stochasticslly synchronized within finite time and meets γ-dissipativity. An example shows the validity of this proposed scheme.

Source: Entropy

DOI: 10.3390/e27121186

Authors: Xiaodan Zhu, Yanjun Wang, Yu Chen

Institution: Ludong University

Language: English

Topic: Neural Networks Stability and Synchronization

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funders: National Natural Science Foundation of China, Natural Science Foundation of Shandong Province