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Adaptive control for nonlinear cyber‐physical systems under false data injection attacks through sensor networks
Author(s) -
Ren XiuXiu,
Yang GuangHong
Publication year - 2019
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4749
Subject(s) - backstepping , control theory (sociology) , nonlinear system , cyber physical system , bounded function , computer science , lyapunov stability , stability (learning theory) , adaptive control , transformation (genetics) , lyapunov function , scheme (mathematics) , control (management) , control engineering , engineering , mathematics , artificial intelligence , machine learning , gene , mathematical analysis , biochemistry , chemistry , physics , quantum mechanics , operating system
Summary This paper considers the adaptive control problem for a class of nonlinear cyber‐physical systems with unknown nonlinearities and false data injection attacks, where the sensors are corrupted by attackers. To mitigate the effects caused by the considered attacks, a novel coordinate transformation is developed in the backstepping control design. In addition, to deal with the multiple unknown time‐varying state feedback gains caused by the sensor attacks, the new types of Nussbaum functions are introduced in the adaptive control. By using Lyapunov stability theory, the proposed control scheme can guarantee all the closed‐loop system signals globally bounded. Finally, the examples demonstrate the effectiveness of the proposed method.