Sum-based event-triggered dynamic output feedback control for synchronization of fuzzy neural networks with deception attacks

This paper concerns with the event-based dynamic output feedback control for the synchronization of fuzzy neural networks under mixed delay and deception attacks. A weighted sum-based dynamic event-triggered mechanism (WSDETM) is developed to save the communication resources while preserving a satisfactory system performance. A dynamic output feedback controller (DOFC) is designed to achieve exponential synchronization of fuzzy neural networks. To reduce the data traffic, both communication channels from the sensor to DOFC and DOFC to Zero-Order Holder are subject to WSDETM. Different from the traditional deception attacks modeled by Bernoulli process, we adopt the more general Markov process modeling deception attacks. By using the cone-complimentarity linearization algorithm, the DOFC and WSDETM parameters are carried out. The effectiveness of the proposed method is demonstrated with two numerical cases.

Automated summary

This paper proposes an event-based dynamic output feedback control method to achieve fuzzy neural network synchronization under mixed delay and deception attacks. A dynamic event-triggered mechanism is developed to save communication resources while ensuring system performance. The effectiveness of the method is demonstrated through numerical tests.