Finite-Time Dissipative Fault Estimate and Event-Triggered Fault-Tolerant Synchronization Control for Discrete Semi-Markov Jumping Neural Networks
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.
Authors
- Xiaodan Zhu (ORCID: https://orcid.org/0000-0002-6177-5729)
- Yu Chen (ORCID: https://orcid.org/0009-0001-4598-052X)
- Yanjun Wang (ORCID: https://orcid.org/0009-0007-4706-8853)
Institutions
- Ludong University (CN)
Publication Details
- Journal
- Entropy
- Published
- 2025-11-22
- DOI
- https://doi.org/10.3390/e27121186
- Primary Topic
- Neural Networks Stability and Synchronization
- Type
- article
- Field-Weighted Citation Impact
- 0.00