Resilient control design of networked vehicle suspension system under False Data Injection Attacks

Authors

  • Yuhui Zhang

DOI:

https://doi.org/10.54097/2dgb4v45

Keywords:

Active vehicle suspension system, resilient controller, FDI attack model, Lyapunov function.

Abstract

Under covert false data injection (FDI) attacks, the robust security control problem of nonlinear active vehicle suspension systems (AVSSs) is examined in this paper. First, the network fuzzy control active suspension model is developed, and the Takagi-Sugeno (T-S) fuzzy technology is applied to address the uncertainty of AVSSs. Secondly, considering the influence of the FDI attack model, a resilient controller is designed for AVSSs. The exponential stability condition of the system under the network assault is then derived concurrently with the design of the Lyapunov function associated with the membership degree. Lastly, a simulation test confirms the developed controller's efficacy.

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References

[1] Sun W, Pan H, Gao H. Filter-based adaptive vibration control for active vehicle suspensions with electrohydraulic actuators[J]. IEEE Transactions on Vehicular Technology, 2015, 65(6): 4619-4626.

[2] Huang W, Zhao J, Yu G, et al. Intelligent vibration control for semiactive suspension systems without prior knowledge of dynamical nonlinear damper behaviors based on improved extreme learning machine[J]. IEEE/ASME Transactions on Mechatronics, 2020, 26(4): 2071-2079.

[3] Bégin M A, Chouinard P, Lebel L P, et al. Experimental assessment of a controlled slippage magnetorheological actuator for active seat suspensions[J]. IEEE/ASME Transactions on Mechatronics, 2018, 23(4): 1800-1810.

[4] Liu Y J, Zhang Y Q, Liu L, et al. Adaptive finite-time control for half-vehicle active suspension systems with uncertain dynamics[J]. IEEE/ASME Transactions on Mechatronics, 2020, 26(1): 168-178.

[5] Fei Z, Wang X, Liu M, et al. Reliable control for vehicle active suspension systems under event-triggered scheme with frequency range limitation[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 51(3): 1630-1641.

[6] Zhang Z, Li H, Wu C, et al. Finite frequency fuzzy control for uncertain active suspension systems with sensor failure[J]. IEEE/CAA Journal of Automatica Sinica, 2018, 5(4): 777-786.

[7] Wang R, Jing H, Wang J, et al. Robust output-feedback based vehicle lateral motion control considering network-induced delay and tire force saturation[J]. Neurocomputing, 2016, 214: 409-419.

[8] Li W, Xie Z, Zhao J, et al. Static-output-feedback based robust fuzzy wheelbase preview control for uncertain active suspensions with time delay and finite frequency constraint[J]. IEEE/CAA Journal of Automatica Sinica, 2020, 8(3): 664-678.

[9] Guo J, Wang J, Luo Y, et al. Takagi–Sugeno fuzzy-based robust integrated lane-keeping and direct yaw moment controller of unmanned electric vehicles[J]. IEEE/ASME Transactions on Mechatronics, 2020, 26(4): 2151-2162.

[10] Shan Y, Xie X, Peng C. Resilient Stabilization of Networked Active Suspension Systems via a Multi-Instantaneous Fuzzy Gain-Scheduling Mechanism[J]. IEEE Transactions on Industrial Informatics, 2024. doi: 10.1109/TMECH.2024.3476245.

[11] Liang J, Feng J, Lu Y, et al. A direct yaw moment control framework through robust TS fuzzy approach considering vehicle stability margin[J]. IEEE/ASME Transactions on Mechatronics, 2023, 29(1): 166-178.

[12] Hussain F, Hussain R, Hassan S A, et al. Machine learning in IoT security: Current solutions and future challenges[J]. IEEE Communications Surveys & Tutorials, 2020, 22(3): 1686-1721.

[13] Shan Y, Xie X P, Mao Z. Co-Design of a Switching-Type Control Scheme for Nonlinear Networked Systems With Protocol-Based Communication and Its Application to Circuits[J]. IEEE Transactions on Automation Science and Engineering, 2024. doi: 10.1109/TMECH.2024.3476245.

[14] Shan Y, Xie X, Sun J, et al. Resilient Design of Networked Security Control for Active Suspension Systems via an Augmented Switching-Type Approach[J]. IEEE/ASME Transactions on Mechatronics, 2024. doi: 10.1109/TMECH.2024.3476245.

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Published

30-03-2025

How to Cite

Zhang, Y. (2025). Resilient control design of networked vehicle suspension system under False Data Injection Attacks. Highlights in Science, Engineering and Technology, 134, 185-193. https://doi.org/10.54097/2dgb4v45