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Memory-based dynamic event-triggered secure control of active suspension systems against deception attacks.

Wangrui Cheng1, Tingting Yin2, Zhou Gu2

  • 1School of Mathematics-Physics and Finance, Anhui Polytechnic University, Wuhu 241000, China.

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|June 18, 2025
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Summary

This study introduces a memory-based dynamic event-triggered control strategy for active quarter-vehicle suspension systems. The approach enhances suspension performance and reduces network load, even during deception attacks.

Keywords:
Deception attacksMemory-based dynamic ETMQuarter-vehicle suspension systems

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Area of Science:

  • Control Systems Engineering
  • Automotive Engineering
  • Networked Systems

Background:

  • Active quarter-vehicle suspension systems (QVSSs) are crucial for vehicle stability and ride comfort.
  • Traditional control strategies can be network-intensive and vulnerable to cyberattacks.
  • Event-triggered mechanisms (ETMs) aim to optimize resource usage but require robust design against false triggers.

Purpose of the Study:

  • To develop a novel memory-based dynamic event-triggered control strategy for QVSSs.
  • To enhance suspension performance while minimizing network resource consumption.
  • To ensure system resilience against deception attacks through an effective ETM.

Main Methods:

  • A memory-based dynamic event-triggered mechanism (ETM) was designed, integrating historical data to suppress false triggers.
  • The ETM dynamically updates triggering conditions for efficient network data scheduling.
  • Sufficient conditions for guaranteeing system performance were mathematically derived.

Main Results:

  • The proposed ETM effectively coordinates sensor data transmission under deception attacks.
  • False triggering is suppressed by leveraging averaged historical release information.
  • Dynamic scheduling of network data transmission was achieved, optimizing resource usage.
  • Satisfactory performance of the QVSS was demonstrated under the developed control strategy.

Conclusions:

  • The memory-based dynamic ETM offers an effective solution for robust and resource-efficient control of active QVSSs.
  • The strategy successfully mitigates the impact of deception attacks on suspension performance.
  • This approach represents a significant advancement in networked control systems for automotive applications.