Intermittent event-triggered control for exponential synchronization of delayed neural networks on time scales. (English) Zbl 07900572
Summary: This paper studies the exponential synchronization of delayed neural networks (DNNs) on time scales using the intermittent event-triggered control (IETC) method. Initially, considering the time scale situation, an IETC that merges intermittent control and event-triggered control is introduced, and a new differential inequality is developed. Subsequently, an exponential synchronization criterion is established based on the Lyapunov function, the proposed differential inequality and the time scale theory, applicable to continuous, discrete and hybrid time domains. Furthermore, under the event-triggered condition, it is demonstrated that the lower bound of each event-triggered interval exceeds a positive constant, thereby preventing the occurrence of Zeno’s behavior. Finally, the approach efficacy is validated through numerical examples.
MSC:
| 93C65 | Discrete event control/observation systems |
| 93D23 | Exponential stability |
| 93B70 | Networked control |
| 93C43 | Delay control/observation systems |
| 93C70 | Time-scale analysis and singular perturbations in control/observation systems |
Keywords:
intermittent event-triggered control; time scales; delayed neural networks; exponential synchronizationReferences:
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