• Adaptive performance control o...

*Result*: Adaptive performance control of switched nonlinear systems under false data injection attacks and input saturation constraints.

Title:
Adaptive performance control of switched nonlinear systems under false data injection attacks and input saturation constraints.
Authors:
He W; State Key Laboratory of Chemical Resource Engineering, and the College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China. Electronic address: hewj928@163.com., Wang Y; State Key Laboratory of Chemical Resource Engineering, and the College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China. Electronic address: wang.youqing@ieee.org., Shi Y; State Key Laboratory of Chemical Resource Engineering, and the College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China. Electronic address: yukun_shi@buct.edu.cn.
Source:
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2026 Jun; Vol. 198, pp. 108602. Date of Electronic Publication: 2026 Jan 15.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Pergamon Press Country of Publication: United States NLM ID: 8805018 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-2782 (Electronic) Linking ISSN: 08936080 NLM ISO Abbreviation: Neural Netw Subsets: MEDLINE
Imprint Name(s):
Original Publication: New York : Pergamon Press, [c1988-
MeSH Terms:
Nonlinear Dynamics* , Neural Networks, Computer* , Computer Security*, Computer Simulation ; Algorithms
Contributed Indexing:
Keywords: Disturbance observer; False data injection attack; Input saturation; Prescribed performance; Switched nonlinear systems
Entry Date(s):
Date Created: 20260118 Date Completed: 20260307 Latest Revision: 20260307
Update Code:
20260308
DOI:
10.1016/j.neunet.2026.108602
PMID:
41548442
Database:
MEDLINE

*Further Information*

*Considering the controller-actuator channel subjected to false data injection (FDI) attacks, this study proposes an adaptive performance control strategy for switched nonlinear systems under composite disturbances and input saturation. The strategy achieves disturbance rejection and a more flexible prescribed performance control. In addition, implicit disturbances that are coupled with the system states in switched nonlinear systems lie beyond the capability of existing disturbance observers. Moreover, conventional prescribed performance control methods become ineffective in the presence of input saturation. To overcome these challenges, a novel switched nonlinear disturbance observer is developed to reconstruct implicit mismatched disturbances. This observer employs dynamic high gain technique to address the unknown nonlinearity of disturbances. Additionally, an adaptive update law is designed to compensate for matched disturbances. Then, a modified fixed-time performance function is introduced to balance input saturation with tracking performance. To mitigate the adverse effects of FDI attacks, the neural network approximation technique is applied within the backstepping control process. Finally, the simulation results reveal that the proposed adaptive performance control strategy achieves effective tracking control of switched nonlinear systems.
(Copyright © 2026 Elsevier Ltd. All rights reserved.)*

*Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.*