From Distributed Noisy Data to Event-Triggered Pinning Observer-Based Control

Abstract

This paper presents an event-triggered pinning observer-based control of unknown large-scale interconnected systems under false data injection attacks using distributed noisy data without any system identification step. An exogenous system is used to model the false data injection attack. Two event-triggered mechanisms are introduced at the sensor and observer sides to reduce unnecessary computational resource consumption. The corresponding data representations are constructed for unknown systems subject to attacks. Under the framework of the data representation of unknown systems, an event-triggered pinning extended observer-based controller is designed. The global exponential stability of unknown systems is reached under the designed controller. Finally, an example of non-isothermal continuous stirred tank reactors is provided to verify the effectiveness of the obtained results.

Keywords

data fusion / intelligent control / intelligent systems / lyapunov methods

Acknowledgements

This work was supported by National Natural Science Foundation of China (62463007, 62463005, and 62563006), Natural Science Foundation of Hainan Province (625RC710 and 625MS047), Postdoctoral Research Funding of Hainan Province (2025-79), and Postgraduate Innovative Research Funding of Hainan Province (Hyb2025-22, Hys2025-56, and Hys2025-60).

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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