Journal
NEURAL COMPUTING & APPLICATIONS
Volume 35, Issue 14, Pages 10221-10237Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-023-08231-7
Keywords
Weighted sum-based dynamic event-triggered scheme; T-S fuzzy model; Dynamic output feedback; Deception attacks; Cone-complimentarity linearization algorithm
Categories
Ask authors/readers for more resources
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.
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available