Resilient Adaptive Event-Triggered $H_{\infty }$ Fuzzy Filtering for Cyber-Physical Systems Under Stochastic-Sampling and Denial-of-Service Attacks-Reference-Cited by-同舟云学术

Resilient Adaptive Event-Triggered $H_{\infty }$ Fuzzy Filtering for Cyber-Physical Systems Under Stochastic-Sampling and Denial-of-Service Attacks

Published:2023-01 Issue:1 Volume:31 Page:278-292
ISSN:1063-6706
Container-title:IEEE Transactions on Fuzzy Systems
language:
Short-container-title:IEEE Trans. Fuzzy Syst.

Author:

Xie Xuhuan¹^ORCID,Hu Songlin²^ORCID,Liu Yonggui³^ORCID,Li Qinxue⁴^ORCID

Affiliation:

1. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China

2. Institute of Advanced Technology for Carbon Neutrality, Nanjing University of Posts and Telecommunications, Nanjing, China

3. Key Laboratory of Autonomous Systems and Network Control, Ministry of Education, School of Automation Science and Engineering, South China University of Technology, Guangzhou, China

4. School of Ship and Ocean Engineering, Guangzhou Maritime University, Guangzhou, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/91/10003087/09804802.pdf?arnumber=9804802

Reference56 articles.

1. Ultimate Boundedness Control for Networked Singularly Perturbed Systems with Deception Attacks: A Markovian Communication Protocol Approach

2. Synthesis of Supervisors Robust Against Sensor Deception Attacks

3. Chance-Constrained $H_{∞}$ State Estimation for Recursive Neural Networks Under Deception Attacks and Energy Constraints: The Finite-Horizon Case

4. Secure Fusion Estimation for Bandwidth Constrained Cyber-Physical Systems Under Replay Attacks

5. Static Output Feedback Quantized Control for Fuzzy Markovian Switching Singularly Perturbed Systems with Deception Attacks

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