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Adaptive Event-triggered Control for Networked Switched T-S Fuzzy Systems Subject to False Data Injection Attacks

Abstract

This paper is concerned with the problem of adaptive event-triggered control for networked switched T-S fuzzy systems under false data injection attacks. In order to reduce unnecessary data transmission, an adaptive event-triggering mechanism is proposed, which can dynamically change triggering conditions based on system performance needs. In particular, due to the consideration of network safety, the system will be subjected to the impacts from both attack delays and network transmission delays. Then, by a delay system transformation approach, a time-delay closed-loop switched T-S fuzzy system is obtained. Moreover, by utilizing average dwell time technique, stability conditions are developed for the closed-loop system with the adaptive event-triggering mechanism and false data injection attacks. In addition, a co-design of adaptive event-triggering parameters and controller gains is given. Finally, simulation results are provided to verify the effectiveness of the designed method.

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Correspondence to Yiwen Qi.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Jun Yoneyama under the direction of Editor Euntai Kim. This work was supported in part by the National Natural Science Foundation of China (grant numbers 61873172, 61811530036, 61403261, 61703148), the Overseas Training Program of Universities in Liaoning (grant number 2019GJWYB008), the Liaoning Revitalization Talents Program (grant number XLYC1807101), the Natural Science Foundation of Liaoning Province (grant number 20180550517), the Liaoning BaiQianWan Talents Program (grant number 2018-B-20), the Natural Science Foundation of Heilongjiang Province (grant number F2017023), and the Open Fund of Science and Technology on Thermal Energy and Power Laboratory (grant number TPL2017CA005).

Yiwen Qi received his Ph.D. degree from Harbin Institute of Technology, Harbin, China, in 2012. From 2015 to 2016, he was a Post-Doctoral Fellow at University of Groningen, Groningen, the Netherlands. He is currently a Professor at the School of Automation, Shenyang Aerospace University, Shenyang, China. His research interests include analysis and synthesis of switched control systems, event-triggered control, AI control, and their applications in flight vehicle and aero-engines.

Shuo Yuan received his B.Eng. degree from North China Institute of Science & Technology, Langfang, China, in 2017. He is currently pursuing towards an M.Eng. degree at Shenyang Aerospace University, Shenyang, China. His research interests include event-triggered control and switched fuzzy systems.

Xin Wang received his Ph.D. degree from Northeastern University, Shenyang, China, in 2016. He is currently a Lecturer at the School of Mathematical Science, Heilongjiang University, Harbin, China, and also a Post-Doctoral Fellow at Yeung-nam University, Gyeongsan, Korea. His research interests include fault diagnosis, fault-tolerant control, multiagent coordination, and time-delay systems.

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Qi, Y., Yuan, S. & Wang, X. Adaptive Event-triggered Control for Networked Switched T-S Fuzzy Systems Subject to False Data Injection Attacks. Int. J. Control Autom. Syst. 18, 2580–2588 (2020). https://doi.org/10.1007/s12555-019-0742-9

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Keywords

  • Adaptive event-triggered control
  • average dwell time
  • false data injection attacks
  • switched T-S fuzzy systems