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<p>The article investigates a novel dynamic event-triggered mechanism (DETM) fuzzy filtering for sideslip angle estimation of a vehicle continuous system, which takes into account network-induced constraints. An uncertain Takagi–Sugeno (T–S) fuzzy model is utilized to describe vehicle dynamics, which explicitly considers the data quantization and hybrid attacks. A DETM strategy is designed to save network resources, which expands the threshold function by adding an internal dynamic variable. The stability of the intelligent vehicle continuous-time dynamic system subject to bounded disturbances is expressed by the methodology of quadratic boundedness (QB), and a novel DETM fuzzy filtering based on QB is proposed that can be tackled by linear matrix inequalities (LMIs) technique. At last, simulation results are shown to validate the benefits of the proposed approach over existing results.</p>

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Event-Triggered Filtering for Vehicle Sideslip Angle Estimation under Data Quantization and Hybrid Attacks using Quadratic Boundedness

  • 期刊论文

  • 发表日期：

    2025年2月19日

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  • Yongzhen Cao,
  • Xiaoming Tang,
  • Hongchun Qu,
  • Shidong Zhai,
  • Jingjie Yuan

摘要

The article investigates a novel dynamic event-triggered mechanism (DETM) fuzzy filtering for sideslip angle estimation of a vehicle continuous system, which takes into account network-induced constraints. An uncertain Takagi–Sugeno (T–S) fuzzy model is utilized to describe vehicle dynamics, which explicitly considers the data quantization and hybrid attacks. A DETM strategy is designed to save network resources, which expands the threshold function by adding an internal dynamic variable. The stability of the intelligent vehicle continuous-time dynamic system subject to bounded disturbances is expressed by the methodology of quadratic boundedness (QB), and a novel DETM fuzzy filtering based on QB is proposed that can be tackled by linear matrix inequalities (LMIs) technique. At last, simulation results are shown to validate the benefits of the proposed approach over existing results.