Security sliding mode control of Lur’e switched systems subject to multi-strategy injection attack

• Published in: Journal of the Franklin Institute Vol. 361; no. 17; p. 107187
• Main Authors: Zhao, Haijuan, Ma, Juan, Xu, Qinqi
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.11.2024
• Subjects: Genetic algorithm; Multi-strategy attacks; Sliding mode control; Switched systems; Switched systems; Genetic algorithm; Sliding mode control; Multi-strategy attacks
• ISSN: 0016-0032
• DOI: 10.1016/j.jfranklin.2024.107187

This paper investigates the sliding mode control (SMC) problem of a class of Lur’e nonlinear switched systems under multi-strategy network attacks. Unlike traditional attacks, multi-strategy attacks select different attack strategies at different attack moments. False data injection (FDI) attacks may randomly occur in the sensor-to-controller (S/C) channel, leading to compromised system states. How to construct suitable sliding surface and optimal sliding matrix to ensure the dynamic performance of nonlinear switched systems in the damaged state is a key challenge. Bernoulli random distribution is used to establish the relationship model between the state of the system and attacked state. Based on this model, a sliding mode controller is designed using available state signals to ensure input-to-state in probability (ISSiP) of the closed-loop switched system and reachability of the sliding surface. A binary genetic algorithm (GA) is employed to search for the ideal sliding matrix, optimizing the sliding mode domain to enhance the system’s control performance. Finally, two numerical examples are given to demonstrate the effectiveness of the obtained results.